Processing math: 100%
Research article

Longevity risk analysis: applications to the Italian regional data

  • Received: 03 March 2022 Revised: 27 March 2022 Accepted: 28 March 2022 Published: 30 March 2022
  • JEL Codes: C02, C15, C22

  • Longevity risk is the risk that members of a given population will live longer than expected. When it occurs, pension providers may have to pay pensions for longer than expected, significantly increasing their costs. While this risk is being adequately studied using the national mortality data provided by the Human Mortality Database, relatively few studies exist that analyse sub-national data. This manuscript proposes a comparative study of some stochastic mortality models to measure the longevity risk on Italian mortality data at the regional level. In particular, the use of the Lee-Carter and Li-Lee models is explored. The models are compared in fitting quality, forecasting accuracy and complexity. Numerical experiments and applications to immediate life annuity evaluation are presented.

    Citation: Salvatore Scognamiglio. Longevity risk analysis: applications to the Italian regional data[J]. Quantitative Finance and Economics, 2022, 6(1): 138-157. doi: 10.3934/QFE.2022006

    Related Papers:

    [1] Dina Abuzaid, Samer Al-Ghour . Correction: Supra soft Omega-open sets and supra soft Omega-regularity. AIMS Mathematics, 2025, 10(5): 10624-10625. doi: 10.3934/math.2025483
    [2] Alaa M. Abd El-latif . Novel types of supra soft operators via supra soft sd-sets and applications. AIMS Mathematics, 2024, 9(3): 6586-6602. doi: 10.3934/math.2024321
    [3] Alaa M. Abd El-latif, Mesfer H. Alqahtani . New soft operators related to supra soft δi-open sets and applications. AIMS Mathematics, 2024, 9(2): 3076-3096. doi: 10.3934/math.2024150
    [4] Alaa M. Abd El-latif . Specific types of Lindelöfness and compactness based on novel supra soft operator. AIMS Mathematics, 2025, 10(4): 8144-8164. doi: 10.3934/math.2025374
    [5] Alaa M. Abd El-latif, Mesfer H. Alqahtani . Novel categories of supra soft continuous maps via new soft operators. AIMS Mathematics, 2024, 9(3): 7449-7470. doi: 10.3934/math.2024361
    [6] Samirah Alzahrani, A. A. Nasef, N. Youns, A. I. EL-Maghrabi, M. S. Badr . Soft topological approaches via soft γ-open sets. AIMS Mathematics, 2022, 7(7): 12144-12153. doi: 10.3934/math.2022675
    [7] Dina Abuzaid, Samer Al Ghour . Three new soft separation axioms in soft topological spaces. AIMS Mathematics, 2024, 9(2): 4632-4648. doi: 10.3934/math.2024223
    [8] Tareq M. Al-shami, Abdelwaheb Mhemdi, Alaa M. Abd El-latif, Fuad A. Abu Shaheen . Finite soft-open sets: characterizations, operators and continuity. AIMS Mathematics, 2024, 9(4): 10363-10385. doi: 10.3934/math.2024507
    [9] Tareq M. Al-shami, Abdelwaheb Mhemdi, Radwan Abu-Gdairi, Mohammed E. El-Shafei . Compactness and connectedness via the class of soft somewhat open sets. AIMS Mathematics, 2023, 8(1): 815-840. doi: 10.3934/math.2023040
    [10] Orhan Göçür . Amply soft set and its topologies: AS and PAS topologies. AIMS Mathematics, 2021, 6(4): 3121-3141. doi: 10.3934/math.2021189
  • Longevity risk is the risk that members of a given population will live longer than expected. When it occurs, pension providers may have to pay pensions for longer than expected, significantly increasing their costs. While this risk is being adequately studied using the national mortality data provided by the Human Mortality Database, relatively few studies exist that analyse sub-national data. This manuscript proposes a comparative study of some stochastic mortality models to measure the longevity risk on Italian mortality data at the regional level. In particular, the use of the Lee-Carter and Li-Lee models is explored. The models are compared in fitting quality, forecasting accuracy and complexity. Numerical experiments and applications to immediate life annuity evaluation are presented.



    Molodtsov [1] introduced the concept of soft sets in 1999 as an innovative way to deal with uncertain data while modeling real-world situations in several domains such as data science, engineering, economics, and health sciences. Numerous researchers have used the theory of soft sets as a mathematical tool to solve real-world problems (see [2,3]). Shabir and Naz [4] initiated the structure of soft topology and investigated many related topics. After that, several researchers interested in abstract structures attempted to extend topological concepts to include soft topological spaces. For instance, concepts such as soft compactness [5], soft separation axioms [6,7,8,9,10], lower soft separation axioms [11,12,13,14,15], soft mappings [16,17], and soft metrics [18] were introduced. Furthermore, some researchers have investigated the concept of generalized open sets in soft topologies, such as soft semi-open sets [19], soft somewhat open sets [20], soft Q-sets [21], and lower density soft operators [22].

    Mashhour et al. [23] defined supra-topological spaces by removing the condition of finite intersections in the traditional definition of topologies. Many topological researchers examined topological notions by using supra-topologies to analyze their properties [24,25,26,27,28]. The authors of [28] used supra-topologies to generate new rough set models for describing information systems. Furthermore, the authors of [29] used supra-topologies in digital image processing.

    The concept of supra-soft topological spaces, introduced in 2014 [30], generalizes crisp mathematical structures to include soft ones. It included concepts like continuity [30], compactness [31], separation axioms [32,33,34,35,36], separability [37,38], and generalized open sets [39,40,41]. Research in the field of supra-soft topologies remains vibrant and active.

    This paper proposes new concepts in supra-soft topology that extend traditional supra-topologies through a novel classification known as supra-soft ω-open sets. Some new separation axioms and the development of finer structures using supra-soft ω-open sets connect existing theories to newer aspects of the theory of topological structures. Besides developing our knowledge regarding supra-soft spaces, these results provide fertile ground for future developments of topological methods. In addition, we observe that supra-soft topological structures have not received the attention they deserve, especially since the applications of supra-topological spaces are in many domains [28,29]. Therefore, we expect this paper to offer a new approach to solving practical issues.

    For concepts and expressions not described here, we refer the readers to [42,43].

    Assume that U is a non-empty set and B is a set of parameters. A soft set over U relative to B is a function H:BP(U). SS(U,B) denotes the family of all soft sets over U relative to B. The null soft set and the absolute soft set are denoted by 0B and 1B, respectively. Let HSS(U,B). If H(a)=M for all aB, then H is denoted by CM. If H(a)=M and H(b)= for all bB{a}, then H is denoted by aM. If H(a)={x} and H(b)= for all bB{a}, then H is called a soft point over U relative to B and denoted by ax. SP(U,B) denotes the family of all soft points over U relative to B. If HSS(U,B) and axSP(U,B), then ax is said to belong to H (notation: ax˜H) if xH(a). If {Hα:αΔ}SS(U,B), then the soft union and soft intersection of {Hα:αΔ} are denoted by ˜αΔHα and ˜αΔHα, respectively, and are defined by

    (˜αΔHα)(a)=αΔHα(a) and (˜αΔHα)(a)=αΔHα(a) for all aB.

    The sequel will utilize the following definitions.

    Definition 1.1. [18] A soft set KSS(U,B) is called countable if K(b) is a countable subset of U for each bB. CSS(U,B) denotes the family of all countable soft sets from SS(U,B).

    Definition 1.2. [23] Let U be a set and let be a family of subsets of U. Then is a supra-topology on U if

    (1) {,U}.

    (2) is closed under an arbitrary union.

    We say in this case that (U,) is a supra-topological space (supra-TS, for short). Members of are called supra-open sets in (U,), and their complements are called supra-closed sets in (U,). c denotes the family of all supra-closed sets in (U,).

    Definition 1.3. [23] Let (U,) be a supra-TS and let VU. The supra-closure of V in (U,) is denoted by Cl(V) and defined by

    Cl(V)={W:Wc and VW}.

    Definition 1.4. [30] A subcollection ψSS(U,B) is called a supra-soft topology on U relative to B if

    (1) {0B,1B}ψ.

    (2) ψ is closed under arbitrary soft union.

    We say in this case (U,ψ,B) is a supra-soft topological space (supra-STS, for short). Members of ψ are called supra-soft open sets in (U,ψ,B), and their soft complements are called supra-soft closed sets in (U,ψ,B). ψc will denote the family of all supra-soft closed sets in (U,ψ,B).

    Definition 1.5. [30] Let (U,ψ,B) be a Supra-STS and let KSS(U,B).

    (a) The supra-soft closure of K in (U,ψ,B) is denoted by Clψ(K) and defined by

    Clψ(K)=˜{H:Hψc and K˜H}.

    (b) The supra-soft interior of K in (U,ψ,B) is denoted by Intψ(K) and defined by

    Intψ(K)=˜{T:Tψ and T˜K}.

    Theorem 1.6. [38] For each supra-STS (U,ψ,B) and each bB, the collection {H(b):Hψ} defines a supra-topology on U. This supra-soft topology is denoted by ψb.

    Definition 1.7. [44] A supra-STS (U,ψ,B) is called a supra-soft compact (resp. supra-soft Lindelof) if for every Mψ with ˜MMM=1B, we find a finite (resp. countable) subcollection M1M with ˜KM1M=1B.

    Definition 1.8. [45] Let (U,) be a supra-TS and let VU. Then, V is called a supra-ω-open in (U,) if, for each yV, S and a countable subset NU exist such that ySNV. The collection of all supra-ω-open sets in (U,) is denoted by ω.

    Definition 1.9. [46] A supra-STS (U,) is called supra-Lindelof if, for every M with ˜MMM=U, we find a countable subcollection M1M with ˜KM1M=U.

    Definition 1.10. A supra-STS (U,ψ,B) is called supra-soft countably compact if, for every countable subcollection Mψ with ˜MMM=1B, we find a finite subcollection M1M with ˜KM1M=1B.

    Definition 1.11. [31] Let (U,ψ,B) be a supra-STS, VU, and ψV={G˜CV:Gψ}. Then, (V,ψV,B) is called a supra-soft topological subspace of (U,ψ,B).

    Definition 1.12. A supra-TS (U,) is said to be

    (1) [45] Supra-regular if, whenever Vc and yUV, we find R,W with yR, VW, and RW=;

    (2) Supra-ω-regular if, whenever V(ω)c and yUV, we find R and Wω with yR, VW, and RW=;

    (3) Supra-ω-locally indiscrete (supra-ω-L-I, for short) if (ω)c.

    Definition 1.13.[36] A supra-STS (U,ψ,B) is called supra-soft regular if, whenever Lψc and by˜1BL, we find G,Hψ with by˜G, L˜H, and G˜H=0B.

    Definition 1.14. [37] Let (U,ψ,B) and (V,ϕ,D) be two supra-STSs. Then the supra-soft topology on U×V relative to B×D that has ψ×ϕ as a supra-soft base will be denoted by pr(ψ×ϕ).

    Theorem 2.1. Let {(U,ψb):bB} be a family of supra-TSs, and let

    ψ={HSS(U,B):H(b)ψb for all bB}.

    Then (U,ψ,B) is a supra-STS.

    Proof: Since for every bB, 0B(b)=ψb, and 1B(b)=Yψb, therefore {0B,1B}ψ. Let {H:HH}ψ. Then for all bB and HH, H(b)ψb and HHH(b)ψb. So, for each bB, (˜HHH)(b)=HHH(b)ψb. Consequently, ˜HHHψ.

    Definition 2.2. Let {(U,ψb):bB} be a family of supra-TSs.

    (a) The supra-soft topology {HSS(U,B):H(b)ψb for all bB} is indicated by bBψb.

    (b) If ψb= for all bB, then bBψb is indicated by μ().

    Theorem 2.3. Let {(U,ψb):bB} be a family of supra-TSs. Then, for each aB, {aV:Vψa}bBψb.

    Proof: Let aB and let Zψa. We then have

    (aV)(b)={Vifb=a,ifba.

    Consequently, (aV)(b)ψb for all bB. Hence, aVbBψb.

    Theorem 2.4. Let {(U,ψb):bB} be a family of supra-TSs and let HSS(U,B){0B}. Then, HbBψb if for each by˜H, we find Vψb with yV and bV˜H.

    Proof: Necessity. Let HbBψb and let by˜H. Then, yH(b)ψb. Set V= H(b). Thus, we have Vψb, yZ, and bV˜H.

    Sufficiency. Let HSS(U,B){0B} such that for each by˜H, we find Vψb with yV and bV˜H. Let bB. To show that H(b)ψb, let yH(b). Then by˜H and, by assumption, we find Vψb with by˜bV˜H. Moreover, by Theorem 2.3, bVbBψb. Hence, HbBψb.

    Theorem 2.5. Let {(U,ψb):bB} be a family of supra-TSs. Then, (bBψb)a=ψa for all aB.

    Proof: To demonstrate that (bBψb)aψb, let V(bBψb)a. We then find HbBψb with H(a)=V. By the definition of bBψb, H(a)ψb, and thus Vψb. To demonstrate that ψb(bBψb)a, let Vψb, then, by Theorem 2.3, aVbBψb, and so aV(a)=V(bBψb)a.

    Corollary 2.6. If (U,) is a supra-TS and B is any set of parameters, then (μ())b= for all bB.

    Proof: For every bB, set ψb=. Then, μ()=bBψb, and, by Theorem 2.5, we get the result.

    Theorem 2.7. If (U,ψ,B) is a supra-STS, then ψbBψb.

    Proof: Let Hψ. Then, H(b)ψb for all bB, and thus, HbBψb.

    The equality in Theorem 2.7 is not often true.

    Example 2.8. Let U={1,2,3,4}, B={s,t}, H=s{1,2}˜t{3,4}, and ψ={0B,1B,H}. Then, ψs={,U,{1,2}}, ψt={,U,{3,4}}, and bBψb={0B,1B,s{1,2},t{3,4},F}. Hence, ψbBψb.

    Theorem 2.9. For any supra-STS (U,ψ,B) and any aB, (bBψb)a=ψb.

    Proof: The proof is derived from Theorem 2.5.

    Theorem 2.10. Let (U,) be a supra-TS, B be a set of parameters, and ψ={CV:V}. Then, (U,ψ,B) is a supra-STS.

    Proof: Since , U, then 0B=Cψ and 0B=CUψ. Let { CVi:iI}ψ where {Vi:iI}ψ. We then have iIVi and so CiIViψ. Moreover, it is not difficult to demonstrate that ˜iICVi=CiIVi. Consequently, ˜iICViψ.

    Definition 2.11. For every supra-TS (U,) and every collection of parameters B, the supra-soft topology {CV:V} is indicated by C().

    Theorem 2.12. For every supra-TS (U,), and each collection of parameters B, (C())b= for all bB.

    Proof: Obvious.

    Theorem 2.13. Let (U,ψ,B) be a supra-STS with ψ{CV:ZU}, and let ={VU:CVψ}. Then (U,) is a supra-TS.

    Proof: Since 0B=Cψ, and 1B=CUψ, , U. Let {Vi:iI}. Then {CVi:iI}ψ and so ˜iICViψ. Since ˜iICVi=CiIVi, iIVi.

    Definition 2.14. Let (U,ψ,B) be a supra-STS with ψ{CV:VU}. Then the supra-topology {VU:CVψ} is indicated by D(ψ).

    The following two results follow obviously:

    Theorem 2.15. For any supra-STS (U,ψ,B) with ψ{CV:VU}, ψb=D(ψ) for all bB.

    Theorem 2.16. For every supra-TS (U,) and every collection of parameters B, D(C())=.

    Definition 3.1. Let (U,ψ,B) be a supra-STS and let H SS(U,B).

    (a) A soft point bySP(U,B) is a supra-soft condensation point of H in (U,ψ,B) if, for each Kψ with by˜K, K˜HCSS(U,B).

    (b) The soft set ˜{bySP(U,B):by is a supra-soft condensation point of H in (U,ψ,B)}, which is indicated by Cond(H).

    (c) H is supra-soft ω-closed in (U,ψ,B) if Cond(H)˜H.

    (d) H is supra-soft ω-open in (U,ψ,B) if 1BH is supra-soft ω-closed in (U,ψ,B).

    (e) The collection of all supra-soft ω-open sets in (U,ψ,B) is indicated by ψω.

    Theorem 3.2. Let (U,ψ,B) be a supra-STS and let H SS(U,B). Then, Hψω iff for each by˜H, we find Kψ with by˜K, and KHCSS(U,B).

    Proof: Necessity. Let Hψω and let by˜H. Then, 1BH is soft ω-closed in (U,ψ,B) and by˜1BH. Since Cond(1BH)˜1BH, then by˜Cond(1BH), and thus, we find Kψ with by˜K and K˜(1BH)CSS(U,B). Since K˜(1BH)=KH, we are done.

    Sufficiency. We show that H˜1BCond(1BH). Let by˜H. Then we find Kψ with by˜K and KHCSS(U,B). Thus, we have Kψ, by˜K, and K˜(1BH)=KHCSS(U,B). Hence, by˜1BCond(1BH).

    Theorem 3.3. Let (U,ψ,B) be a supra-STS and let H SS(U,B). Then, Hψω iff for each by˜H, we find Kψ and FCSS(U,B) with by˜KF˜H.

    Proof: Necessity. Let Hψω and let by˜H. By Theorem 3.2, we find Kψ with by˜K and KHCSS(U,B). Set F=KH. We then have FCSS(U,B) with by˜KF=K(KH)=H˜H.

    Sufficiency. Let by˜H. Then, by assumption, we find Kψ and FCSS(U,B) with by˜KF˜H. Since KH˜F, KHCSS(U,B). Consequently, by Theorem 3.2, Hψω.

    Theorem 3.4. For any supra-STS (U,ψ,B), ψψω.

    Proof: Let Hψ and let by˜H. Set K=H and F=0B. We then have Kψ and FCSS(U,B) with by˜KF=K˜K=H. Consequently, by Theorem 3.2, Hψω.

    Theorem 3.5. For any supra-STS (U,ψ,B), (U,ψω,B) is a supra-STS.

    Proof: Since (U,ψ,B) is a supra-STS, {0B,1B}ψ. So, by Theorem 3.4, {0B,1B}ψω. Let Hψω and let by˜˜HHH. Choose HH with by˜H. Since Hψω, by Theorem 3.3, we find Kψ and FCSS(U,B) with by˜KF˜H˜˜HHH. Again, by Theorem 3.3, ˜HHHψω.

    The example that follows demonstrates that equality in general cannot take the place of inclusion in Theorem 3.4.

    Example 3.6. Let Y=R, B=N, and ψ={0B,1B,C(,0],C[0,)}. Then (U,ψ,B) is a supra-STS and C(0,)ψωψ.

    Theorem 3.7. Let (U,ψ,B) be a supra-STS. Then, ψ=ψω iff {KF:Kψ and FCSS(U,B)}ψ.

    Proof: Necessity. Let ψ=ψω. Then, by Theorem 3.3, {KF:Kψ and FCSS(U,B)}ψω=ψ.

    Sufficiency. Let {KF:Kψ and FCSS(U,B)}ψ. By Theorem 3.4, it is enough to demonstrate that ψωψ. Let Hψω{0B} and let by˜H. Then, by Theorem 3.3, we find Kψ and FCSS(U,B) with by˜KF˜H. Since {KF:Kψ and FCSS(U,B)}ψ, KFψ. Consequently, Hψ.

    Theorem 3.8. Let (U,ψ,B) be a supra-STS. Then for all bB, (ψb)ω=(ψω)b.

    Proof: Let bB. To demonstrate that (ψb)ω(ψω)b, let S(ψb)ω and let yS. We then find Mψb and a countable set NU with yMNS. Since Mψb, we find Gψ with G(b)=M. Since bNCSS(U,B), GbNψω and (GbN)(b)=G(b)N=MN(ψω)b. Consequently, S(ψω)b. To demonstrate that (ψω)b(ψb)ω, let S(ψω)b and let yS. Choose Hψω with H(b)=S. Since by˜Hψω, by Theorem 3.3, we find Kψ and FCSS(U,B) with by˜KF˜H. Consequently, we have K(b)ψb, F(b) is a countable subset of U, and yK(b)F(b)H(b)=S. Hence, S(ψb)ω.

    Corollary 3.9. Let (U,ψ,B) be a supra-STS. If Hψω, then for each bB, H(b)(ψb)ω.

    Proof:Let Hψω and let bB. Then, H(b)(ψω)b, and, by Theorem 3.8, H(b)(ψb)ω.

    Theorem 3.10. For any family of supra-TSs {(U,ψb):bB}, (bBψb)ω=bB(ψb)ω.

    Proof: Let H (bBψb)ω. To demonstrate that H bB(ψb)ω, we show that H(a)(ψa)ω for all aB. Let aB and let yH(a). We then have ay˜H(bBψb)ω and, by Theorem 3.3, we find KbBψb and FCSS(U,B) with ay˜KF˜H. Consequently, we have K(a)ψa, F(a) is a countable subset of U, and yK(a)F(a)H(a). This implies that H(a)(ψa)ω. Conversely, let H bB(ψb)ω. To demonstrate that H (bBψb)ω, let ay˜H. Then, yH(a). Since H bB(ψb)ω, H(a)(ψa)ω. Since yH(a)(ψa)ω, we find Mψa and a countable set NU with yMNH(a). Thus, we have aMbBψb, aNCSS(U,B), and ay˜aMaN˜H. Consequently, by Theorem 3.3, H (bBψb)ω.

    Corollary 3.11. For every supra-TS (U,) and every collection of parameters B, (μ())ω=μ(ω) for every bB.

    Proof: For each bB, set ψb=. Then μ()=bBψb and, by Theorem 3.10,

    (μ())ω=(bBψb)ω=bB(ψb)ω=μ(ω).

    Definition 3.12. A supra-STS (U,ψ,B) is called supra-soft locally countable (supra-soft L-C, for short) if, for each bySP(U,B), we find KψCSS(U,B) with by˜K.

    Theorem 3.13. If (U,ψ,B) is supra-soft L-C, then ψω=SS(U,B).

    Proof: It is sufficient to show that SP(U,B)ψω. Let bySP(U,B). Since (U,ψ,B) is supra-soft L-C, then we find KψCSS(U,B) with by˜K. Since KCSS(U,B), then Kby˜CSS(U,B). Thus, by Theorem 3.3, K(Kby)=byψω.

    Corollary 3.14. If (U,ψ,B) is a supra-STS with U being countable, then ψω=SS(U,B).

    Theorem 3.15. Let (U,ψ,B) be a supra-STS. Then (U,ψω,B) is supra-soft countably compact iff SP(U,B) is finite.

    Proof: Necessity. Let (U,ψω,B) be supra-soft countably compact and assume, however, that SP(U,B) is infinite. Choose a denumerable subset {an:nN}SP(U,B) with aiaj when ij. For each nN, set Hn=1B˜knak. We then have ˜nNHn=1B and {Hn:nN}ψω. Since (U,ψω,B) is supra-soft countably compact, we find {Hn1,Hn2,...,Hnk}{Hn:nN} with n1<n2<...<nk and ˜i{n1,n2,...,nk}Hi=Hnk=1B, which is a contradiction.

    Sufficiency. Suppose that SP(U,B) is finite. Then SS(U,B) is finite. Thus, (U,ψω,B) is supra-soft compact, and hence (U,ψω,B) is supra-soft countably compact.

    Corollary 3.16. Let (U,ψ,B) be a supra-STS. Then (U,ψω,B) is supra-soft compact iff SP(U,B) is finite.

    Lemma 3.17. Let (U,ψ,B) be a supra-STS, and let K be a supra-soft base of (U,ψ,B). Then, (U,ψ,B) is supra-soft Lindelof iff for every K1K with ˜KK1K=1B, we find a countable subcollection K2K1 with ˜KK2K=1B.

    Proof: Necessity. Let (U,ψ,B) be supra-soft Lindelof. Let K1K with ˜KK1K=1B. Then, K1ψ with ˜KK1K=1B, and so, we find a countable subcollection K2K1 with ˜KK2K=1B.

    Sufficiency. Let Hψ with ˜HHH=1B. For each bySP(U,B), choose HbyH with by˜Hby. Since K is a supra-soft base of (U,ψ,B), for each bySP(U,B), we find KbyK with by˜Kby˜Hby. Let K1={Kby:bySP(U,B)}. We then have K1K with ˜KK1K=1B, and, by assumption, we find a countable subcollection K2K1 with ˜KK2K=1B. Choose a countable subset γSP(U,B) with K2={Kby:byγ}. Let H1={Hby:byγ}. Then, H1 is a countable subcollection of H with ˜KH1H=1B. Consequently, (U,ψ,B) is supra-soft Lindelof.

    Theorem 3.18. Let (U,ψ,B) be a supra-STS with B being countable. Then (U,ψ,B) is supra-soft Lindelof iff (U,ψω,B) is supra-soft Lindelof.

    Proof: Necessity. Let (U,ψ,B) be supra-soft Lindelof. Set R={KF:Kψ and FCSS(U,B)}. Then, by Theorem 3.3, R is a supra-soft base of (U,ψω,B). We apply Lemma 3.17. Let R1R with ˜RR1R=1B, say R1={KjFj:where Kjψ and FjCSS(U,B):jJ}. Since ˜jJKj=1B and (U,ψ,B) is supra-soft Lindelof, then there is a countable subset J1J with ˜jJ1Kj=1B. Set F=˜jJ1Fj. Then FCSS(U,B). For each by˜F, choose jbyJ with by˜KjbyFjby. Let

    R2={KjFj:jJ1}{KjbyFjby:by˜F}.

    Then, R2R1, R2 is countable, and ˜RR2R=1B.

    Sufficiency. Let (U,ψω,B) be supra-soft Lindelof. By Theorem 3.4, ψψω. Thus, (U,ψ,B) is supra-soft Lindelof.

    Theorem 3.19. Let (U,ψ,B) be a supra-STS and let V U. Then,  (ψV)ω=(ψω)V.

    Proof: To show that (ψV)ω(ψω)V, let S(ψV)ω and let by˜S. By Theorem 3.3, we find M ψV and LCSS(V,B) with by˜ML˜S. Choose Kψ with M=K˜CV. Then, KL ψω, by˜KL, and (KL)˜CV=ML˜S. Consequently, S(ψω)V. Conversely, to show that (ψω)V(ψV)ω, let S(ψω)V and let by˜S. Choose Hψω with S=HCV. Since by˜Hψω, by Theorem 3.3, we find Kψ and FCSS(U,B) with by˜KF ˜H. Set T=K˜CV. We then have T ψV, F˜CVCSS(V,B), and by˜T(F˜CV)˜S. Again, by Theorem 3.3, S(ψV)ω.

    Theorem 3.20. Let {(U,ψb):bB} be a family of supra-TSs. Then (U,bBψb,B) is supra-soft Lindelof iff B is countable and (U,ψb) is supra-Lindelof for all bB.

    Proof: Necessity. Let (U,bBψb,B) be supra-soft Lindelof. Since {bU:bB}bBψb with ˜bBbU=1B, we find a countable subset B1B with ˜bB1bU=1B. We must have B1=B, and hence B is countable. Let aB. To show that (U,ψb) is supra-Lindelof, let Yψa with YYY=U. Let K={aY:YY}{bU:bB{a}}. Then, KbBψb and ˜KKK=1B. Since (U,bBψb,B) is supra-soft Lindelof, we find a countable subcollection K1K with ˜KK1K=1B. Consequently, we find a countable subcollection Y1Y with K1={aY:YY1}{bU:bB{a}}. Moreover, we must have YY1Y=U. This shows that (U,ψb) is supra-Lindelof.

    Sufficiency. Let B be countable, and (U,ψb) be supra-Lindelof for all bB. Let H={bV:bB and Vψb}. By Theorem 2.4, H is a supra-soft base of (U,bBψb,B). We apply Lemma 3.17. Let TH with ˜TTT=1B. For each bB, let Tb={VU:bVT}. For each bB, we have Tb ψb with YTbY=U, and, we find a countable subcollection LbTb with YLbY=U. Let T1={bV:bB and VLb}. Since B is countable, T1 is countable. Consequently, we have a T1 that is a countable subcollection of T with ˜TT1T=1B. It follows that (U,bBψb,B) is supra-soft Lindelof.

    Definition 3.21. A supra-STS (U,ψ,B) is called supra-soft anti locally countable (supra-soft A-L-C, for short) if for any G,Hψ, either G˜H=0B or G˜HCSS(U,B).

    Theorem 3.22. A supra-STS (U,ψ,B) is supra-soft A-L-C iff (U,ψω,B) is supra-soft A-L-C.

    Proof: Necessity. Let (U,ψ,B) be supra-soft A-L-C. Assume, however, we have G,Hψω with G˜HCSS(U,B){0B}. Choose by˜G˜H. By Theorem 3.3, we find M,Nψ and F,LCSS(U,B) with by˜MF˜G and by˜NL˜H. Consequently, M˜N˜(G˜H)˜(F˜L). This implies that M˜NCSS(U,B){0B}. Consequently, (U,ψ,B) is not supra-soft A-L-C, which is a contradiction.

    Sufficiency. Obvious.

    Theorem 3.23. Let (U,ψ,B) be supra-soft A-L-C. Then for all Hψω, Clψ(H)=Clψω(H).

    Proof: Let (U,ψ,B) be supra-soft A-L-C and let Hψω. Since, by Theorem 3.4, ψψω, Clψω(H)˜Clψ(H). To demonstrate that Clψ(H)˜Clψω(H), let by˜Clψ(H), and let Kψω with by˜K. By Theorem 3.3, we find Mψ and FCSS(U,B) with by˜MF˜K. Since by˜Mψ and by˜Clψ(H), M˜H0B. Choose ax˜M˜H. Since Hψω, by Theorem 3.3, we find Nψ and LCSS(U,B) with ax˜NL˜H. Since ax˜M˜N and (U,ψ,B) is supra-soft A-L-C, M˜NCSS(U,B). Thus, (MF)˜(NL)0B, and hence, K˜H0B. Consequently, by˜Clψω(H).

    The following example demonstrates that Theorem 3.23 is no longer true when the assumption of being "supra-soft A-L-C" is removed.

    Example 3.24. Let U=Z, B={a,b}, and ψ={0B,1B,CN}. Then, CN ψ ψω. We have Clψ(CN)=1B, but Clψω(CN)=CN1B.

    In Theorem 3.23, the assumption "Hψω" cannot be eliminated.

    Example 3.25. Let be the usual topology on R. Consider (R,μ(),N). Let HSS(R,N) be defined by H(b)=Q{b} for all bN. Since HCSS(R,N), Cl(μ())ω(H)=H. Moreover, Clμ()(H)=1B.

    Theorem 3.26. Let (U,ψ,B) be supra-soft A-L-C. Then for all H(ψω)c, Intψ(H)=Intψω(H).

    Proof: Let (U,ψ,B) be supra-soft A-L-C and let H(ψω)c. Then, 1BHψω and, by Theorem 3.23, Clψ(1BH)=Clψω(1BH). Thus,

    Intψ(H)=1BClψ(1BH)=1BClψω(1BH)=Intψω(H).

    Theorem 3.27. Let (U,ψ,B) be a supra-soft Lindelof space. If VU with CV(ψω)c{0B}, then (V,ψV,B) is supra-soft Lindelof.

    Proof: Let (U,ψ,B) be a supra-soft Lindelof space and let VU with CV(ψω)c{0B}. By Theorem 3.18, (U,ψω,B) is supra-soft Lindelof. Since CV(ψω)c, by Theorem 3.6 of [45], (V,(ψω)V,B) is supra-soft Lindelof. By Theorem 3.19, (V,(ψV)ω,B) is supra-soft Lindelof. Again, by Theorem 3.18, we must have (V,ψV,B) is supra-soft Lindelof.

    Theorem 4.1. If (U,ψ,B) is a supra-STS with ψψc, then, (U,ψ,B) is a soft topological space.

    Proof: Let G,Hψ. Then, G,Hψc and 1BG,1BHψ. Therefore, 1B(G˜H)=(1BG)˜(1BH)ψ. Thus, 1B(G˜H)ψc. Hence, G˜Hψ.

    Definition 4.2. A supra-STS (U,ψ,B) is said to be

    (a) Supra-soft locally indiscrete (supra-soft L-I, for short) if ψψc;

    (b) Supra-soft ω-locally indiscrete (supra-soft ω-L-I, for short) if ψ(ψω)c.

    Theorem 4.3. A supra-STS (U,ψ,B) is supra-soft L-I iff (U,ψ,B) is supra-soft L-I as a soft topological space.

    Proof: This follows from Theorem 4.1.

    Theorem 4.4. Supra-soft L-C supra-STSs are supra-soft ω-L-I.

    Proof: Let (U,ψ,B) be a supra-soft L-C. Then, by Theorem 3.13, ψω=SS(U,B). Thus, ψψω=(ψω)c=SS(U,B), and hence (U,ψ,B) is supra-soft ω-L-I.

    Theorem 4.4's implication is not reversible in general.

    Example 4.5. Let U=R, B={a,b}, and ψ={0B,1B,CN{1},CZN,CZ}. Consider the supra-STS (U,ψ,B). Since {CN{1},CZN,CZ}CSS(U,B), then {CN{1},CZN,CZ}(ψω)c. Consequently, we have ψ(ψω)c, and hence, (U,ψ,B) is supra-soft ω-L-I. Moreover, it is clear that (U,ψ,B) is not supra-soft L-C.

    Theorem 4.6. Every supra-soft L-I supra-STS is supra-soft ω-L-I.

    Proof: Let (U,ψ,B) be supra-soft L-I, and thus ψψc. Since ψψω, ψc(ψω)c. Consequently, ψ(ψω)c. Hence, (U,ψ,B) is supra-soft ω -L-I.

    Theorem 4.6's implication is not reversible in general.

    Example 4.7. Let U=Q, B=N, and ψ={0B,1B,CN{1},CZN,CZ}. Consider the supra-STS (U,ψ,B). Then, (U,ψ,B) is supra-soft L-C, and, by Theorem 3.13, ψω=SS(U,B). Thus, (ψω)c=ψω=SS(U,B), and hence (U,ψ,B) is supra-soft ω-L-I. Moreover, since CZNψψc, (U,ψ,B) is not supra-soft L-I.

    Theorem 4.8. If (U,ψ,B) is supra-soft A-L-C, and supra-soft ω-L-I, then (U,ψ,B) is supra-soft L-I.

    Proof: Let Hψ. Since (U,ψ,B) is supra-soft ω -L-I, then H(ψω)c, and hence, Clψω(H)=H. Since (U,ψ,B) is supra-soft A-L-C, then, by Theorem 3.23, Clψ(H)=Clψω(H). Thus, Clψ(H)=H, and hence, Hψc. Consequently, (U,ψ,B) is supra-soft L-I.

    Example 4.7 is an example of a supra-soft L-C supra-STS that is not supra-soft L-I. An example of a supra-soft L-I supra-STS that is not supra-soft L-C is as follows:

    Example 4.9. Let U=[0,1][2,3], B={a,b}, and ψ={0B,1B,C[0,1],C[2,3]}. Consider the supra-STS (U,ψ,B). Then, (U,ψ,B) is not supra-soft L-C. Since ψ=ψc, (U,ψ,B) is supra-soft L-I.

    Theorem 4.10. If (U,ψ,B) is supra-soft ω-L-I, then (U,ψb) is supra ω-L-I for all bB.

    Proof: Since (U,ψ,B) is supra-soft ω-L-I, then ψ(ψω)c. Let Vψb. Choose Kψ with K(b)=V. Therefore, we have K(ψω)c, and hence, V=K(b)((ψω)b)c. But, by Theorem 3.8, (ψω)b=(ψb)ω. Then, V((ψb)ω)c. This proves that ψb((ψb)ω)c, and hence, (U,ψb) is supra ω-L-I.

    Theorem 4.11. Let {(U,ψb):bB} be a family of supra-TSs. Then (U,bBψb,B) is supra-soft ω-L-I iff (U,ψb) is supra ω-L-I for all bB.

    Proof: Necessity. Let (U,bBψb,B) be supra-soft ω-L-I. Then, by Theorem 4.10, (U,(bBψb)b) is supra ω-L-I for all bB. But, by Theorem 2.5, (bBψb)b=ψb for all bB. This ends the proof.

    Sufficiency. Let (U,ψb) be supra ω-L-I for all bB. Let KbBψb. Then, K(b)ψb for all bB. Since (U,ψb) is supra ω-L-I for all bB, K(b)((ψb)ω)c for all bB. Therefore, K(bB(ψb)ω)c. Now, by Theorem 3.10, K((bBψb)ω)c. It follows that (U,bBψb,B) is supra-soft ω-L-I.

    Corollary 4.12. Let (U,) be a supra-TS and B be a set of parameters. Then, (U,μ(),B) is supra-soft ω-L-I iff (U,) is supra ω-L-I.

    Proof: For every bB, set b=. Then, μ()=bBψb. Theorem 4.11 ends the proof.

    The example that follows demonstrates that, generally, the conclusion in Theorem 4.10 is not true in reverse.

    Example 4.13. Let U=R and B={s,t}. Let

    T={(s,(,0)),(t,(,1))},

    S={(s,[0,1)),(t,(,1))},

    W={(s,[1,2)),(t,[1,))},

    L={(s,[2,)),(t,[1,))},

    N={(s,),(t,(,1))},

    M={(s,),(t,[1,))}.

    Consider the supra-STS (U,ψ,B), where ψ is the supra-soft topology having {T,S,W,L,N,M} as a supra-soft base. Then, ψa is the supra-topology on U having {(,0),[0,1),[1,2),[2,)} as a supra base, and ψb is the supra-topology on U having {(,1),[1,)} as a supra base. Hence, (U,ψa) and (U,ψb) are both supra L-I. Since (U,ψ,B) is supra-soft A-L-C and 1BTψ, by Theorem 4.8, 1BTψω. This implies that (U,ψ,B) is not supra-soft ω-L-I.

    Definition 5.1. A supra-STS (U,ψ,B) is called supra-soft ω-regular (supra-soft ω-r, for short) if whenever Lψc and by˜1BL, we find Gψ and Hψω with by˜G, L˜H, and G˜H=0B.

    Theorem 5.2. A supra-STS (U,ψ,B) is supra-soft ω-r iff whenever Tψ and by˜T, we find Gψ with by˜G˜Clψω(G)˜T.

    Proof: Necessity. Let (U,ψ,B) be supra-soft ω-r. Let Tψ and by˜T. Then, we have 1BTψc and by˜1B(1BT). We then find Gψ and Hψω with by˜G, 1BT˜H, and G˜H=0B. Since 1BT˜H, 1BH˜T. Since G˜H=0B, G˜1BH, and so, by˜G˜Clψω(G)˜Clψω(1BH)=1BH˜T.

    Sufficiency. Let Lψc and by˜1BL. By assumption, we find Gψ with by˜G˜Clψω(G)˜1BL. Set H=1BClψω(G). Then, Hψω, L˜H, and G˜H=0B. Consequently, (U,ψ,B) is supra-soft ω-r.

    Theorem 5.3. If (U,ψ,B) is supra-soft ω -L-I, then (U,ψ,B) is supra-soft ω-r.

    Proof: Let Tψ and by˜T. Since (U,ψ,B) is supra-soft ω-L-I, T(ψω)c, and so, T= Clψω(T). Hence, we have Tψ and by˜T˜Clψω(T)˜T. Thus, by Theorem 5.2, (U,ψ,B) is supra-soft ω-r.

    Corollary 5.4. If (U,ψ,B) is supra-soft L-C, then (U,ψ,B) is supra-soft ω-r.

    Proof: This follows from Theorems 4.4 and 5.3.

    Theorem 5.5. Supra-soft regularity implies supra-soft ω -regularity.

    Proof: Let (U,ψ,B) be supra-soft regular. Let Tψ and by˜T. By the supra-soft regularity of (U,ψ,B), we find Gψ with by˜G˜Clψ(G)˜T. Since Clψω(G)˜Clψ(G), we have by˜G˜Clψω(G)˜Clψ(G)˜T. Consequently, (U,ψ,B) is supra-soft ω-r.

    Lemma 5.6. Let (U,ψ,B) be a supra-STS and let KSS(U,B). Then, for every bB, Clψb(K(b))(Clψ(K))(b).

    Proof: Let yClψb(K(b)). We show that by˜Clψ(K). Let Gψ with by˜G. We then have yG(b)ψb. Since yClψb(K(b)), K(b)G(b). Thus, (K˜G)(b)=K(b)G(b), and hence, K˜G0B. It follows that by˜Clψ(K).

    Theorem 5.7. If (U,ψ,B) is supra-soft regular, then (U,ψb) is supra-regular for all bB.

    Proof: Let (U,ψ,B) be supra-soft regular and let bB. Let Vψb and yV. Choose Tψ with T(b)=V. Then, by˜Tψ, and, by the supra-soft regularity of (U,ψ,B), we find Gψ with by˜G˜Clψ(G)˜T. Thus, we have G(b)ψb, and, by Lemma 5.6, yG(b)Clψb(G(b))(Clψ(G))(b)T(b)=V. Consequently, (U,ψb) is supra-regular.

    Lemma 5.8. Let {(U,ψb):bB} be a family of supra-TSs and let KSS(U,B). Then, Clψa(K(a))=(ClbBψbK)(a) for every aB.

    Proof: Let aB. Then, by Lemma 5.6, Cl(bBψb)a(K(a))(ClbBψb(K))(a). Moreover, by Theorem 2.5, (bBψb)a=ψa. Hence, Clψa(K(a))(ClbBψbK)(a). To demonstrate that (ClbBψbK)(a)Clψa(K(a)), let y(ClbBψbK)(a), and let Vψa with yV. We then have ay˜aVbBψb. Since y(ClbBψbK)(a), ay˜ClbBψbK, and so, aV˜K0B. Consequently, VK(a). This shows that yClψa(K(a)).

    Lemma 5.9. Let {(U,ψb):bB} be a family of supra-TSs. Then, for any aB and VU, ClbBψb(aV)=aClψa(V).

    Proof: Let aB and VU. Let bB. Then, by Lemma 5.8, (ClbBψbaV)(b)=Clψa(aV(b))={Clψa(V)ifb=a,ifba.

    Consequently, ClbBψb(aV)=aClψa(V).

    Theorem 5.10.Let {(U,ψb):bB} be a family of supra-TSs. Then, (U,bBψb,B) is supra-soft regular if (U,ψb) is supra-regular for all bB.

    Proof: Necessity. Let (U,bBψb,B) be supra-soft regular. Then, by Theorem 5.7, (U,(bBψb)b,B) is supra-regular for all bB. But, by Theorem 2.5, (bBψb)b=ψb for all bB. This completes the proof.

    Sufficiency. Let (U,ψb) be supra-regular for all bB. Let TbBψb and let ay˜T. Then, yT(a)ψa and, by the supra-regularity of (U,ψa), we find Vψa with yVClψa(V)T(a). Consequently, we have ay˜aVbBψb , and, by Lemma 5.9, ClbBψb(aV)=aClψa(V)˜T. Therefore, (U,bBψb,B) is supra-soft regular.

    Corollary 5.11.Let (U,) be a supra-TS and B be a set of parameters. Then (U,μ(),B) is supra-soft regular iff (U,) is supra-regular.

    Proof: For every bB, set b=. Then, μ()=bBψb. Theorem 5.10 completes the proof.

    Theorem 5.12. If (U,ψ,B) is supra-soft ω-r, then (U,ψa) is supra-ω-regular for all aB.

    Proof: Let (U,ψ,B) be supra-soft ω-r and let aB. Let Vψa and yV. Pick Tψ with T(a)=T. We then have ay˜Tψ, and, by the supra-soft ω-regularity of (U,ψ,B) and Theorem 5.2, we find Gψ with ay˜G˜Clψω(G)˜T. Thus, we have G(a)ψa, and, by Lemma 5.6, yG(a)Clψω(G(a))(Clψω(G))(a)T(a)=V. Consequently, (U,ψa) is supra-ω-regular.

    Theorem 5.13. Let {(U,ψb):bB} be a family of supra-TSs. Then, (U,bBψb,B) is supra-soft ω-r iff (U,ψb) is supra-ω-regular for all aB.

    Proof: Necessity. Let (U,bBψb,B) be supra-soft ω-r. Then, by Theorem 5.12, (U,(bBψb)b,B) is supra-ω-regular for all bB. But, by Theorem 2.5, (bBψb)b=ψb for all bB. This completes the proof.

    Sufficiency. Let (U,ψb) be supra-ω-regular for all bB. Let TbBψb, and let ay˜T. Then, yT(a)ψa. Since (U,ψa) is supra-ω-regular, we find Vψa with yVCl(ψa)ω(V)T(a). Consequently, we have ay˜aVbBψb and, by Lemma 5.9, ClbB(ψb)ω(aV)=aCl(ψa)ω(V)˜T. Moreover, by Theorem 3.10, (bBψb)ω=bB(ψb)ω. Consequently, ClbB(ψb)ω(aV)=Cl(bBψb)ω(aV). This shows that (U,bBψb,B) is supra-soft ω-r.

    Corollary 5.14. Let (U,) be a supra-TS and B be a set of parameters. Then (U,μ(),B) is supra-soft ω-r iff (U,) is supra-ω-regular.

    Proof: For every bB, set b=. Then, μ()=bBψb. Theorem 5.13 completes the proof.

    The opposites of Theorem 5.3 and Corollary 5.4 are false.

    Example 5.15. Let B={s,t}. Let ψs and ψt be the usual and the discrete topologies on R. Consider the supra-STS (R,bBψb,B). Then, the supra-TSs (R,ψs) and (R,ψt) are supra-regular. Thus, by Theorem 5.10, (R,bBψb,B) is supra-soft regular. Hence, by Theorem 5.5, (R,bBψb,B) is supra-soft ω-r. Conversely, since (,0)ψs((ψs)ω)c, (R,ψs) is not supra-ω-L-I. So, by Theorem 4.11, (R,bBψb,B) is not supra-soft ω-L-I. Moreover, clearly, (R,bBψb,B) is not supra-soft L-C.

    The contrary of Theorem 5.5 is generally untrue.

    Example 5.16. Let U=Z, B=R, and be the cofinite topology on U. Then, (U,) is not supra-regular. So, by Corollary 5.11, (U,μ(),B) is not supra-soft regular. Since (U,μ(),B) is supra-soft L-C, by Corollary 5.4, (U,μ(),B) is supra-soft ω-r.

    Example 5.17. Consider (U,ψ,B) as shown in Example 4.13. In Example 4.13, we showed that both (U,ψs) and (U,ψt) are supra-L-I, which means they are supra-regular and thus are supra-ω -regular. Assume that (U,ψ,B) is supra-soft ω-r. If we let y=1, then ty˜1B(1BT) with 1BTψc. Therefore, we find Gψ and Hψω with ty˜G, 1BT˜H, and G˜H=0B. One can easily check that we must have ty˜T˜G, and so T˜H=0B. Thus, H˜1BT, which implies that H=1BT. But we have shown in Example 4.13 that 1BT(ψω)c. Consequently, (U,ψ,B) is not supra-soft ω-r, and, by Theorem 5.5, (U,ψ,B) is not supra-soft regular.

    Theorem 5.18. If (U,ψ,B) is supra-soft A-L-C and supra-soft ω-r, then (U,ψ,B) is supra-soft regular.

    Proof: This follows from the definitions and Theorem 3.23.

    Theorem 5.19. Let (U,ψ,B) and (V,ϕ,D) be two supra-STSs. In this case:

    (a) (pr(ψ×ϕ))ωpr(ψω×ϕω);

    (b) For any SSS(U,B) and KSS(V,D), Clψω(S)×Clϕω(K)˜Cl(pr(ψ×ϕ))ω(S×K).

    Proof: (a) Let T(pr(ψ×ϕ))ω and let (s,t)(x,y)˜T. We then find Lpr(ψ×ϕ) and HCSS(U×V,B×D) with (s,t)(x,y)˜LH˜T. Choose Fψ and Gϕ with (s,t)(x,y)˜F×G˜L. Set M=(˜{cz:(c,d)(z,w)˜H for some dw˜SP(V,D)})sx and N=(˜{dw:(c,d)(z,w)˜H for some cz˜SP(U,B)})ty. Then, MCSS(U,B) and NCSS(V,D). Therefore, we have FM ψω, GNϕω, and (s,t)(x,y)˜(FM)×(GN)˜(F×G)(M×N)˜LH˜T. Consequently, Tpr(ψω×ϕω).

    (b) Let (s,t)(x,y)˜Clψω(S)×Clϕω(K), and let T(pr(ψ×ϕ))ω with (s,t)(x,y)˜T. By (a), Tpr(ψω×ϕω), and thus, we find Wψω and Eϕω with (s,t)(x,y)˜W×E˜T. Since sx˜W˜Clψω(S) and ty˜E˜Clϕω(K), W˜S0B and E˜K0D. Consequently, (W×E)˜(S×K)0B×D, and hence, T˜(S×K)0B×D. This implies that (s,t)(x,y)˜Cl(pr(ψ×ϕ))ω(S×K).

    Theorem 5.20. Let (U,ψ,B) and (V,ϕ,D) be two supra-STSs. If (U×V,pr(ψ×ϕ),B×D) is supra-soft ω-r, then (U,ψ,B) and (V,ϕ,D) are supra-soft ω-r.

    Proof: Let Fψ, Gϕ, sx˜F, and ty˜G. Then, (s,t)(x,y)˜F×G pr(ψ×ϕ), and, by the supra-soft ω-regularity of (U×V,pr(ψ×ϕ),B×D), we find Kpr(ψ×ϕ) with (s,t)(x,y)˜K˜Cl(pr(ψ×ϕ))ω(K)˜F×G. Choose Sψ and Tϕ with (s,t)(x,y)˜S×T˜K. Then, by Theorem 5.19 (b), (s,t)(x,y)˜S×T˜Clψω(S)×Clϕω(T)˜Cl(pr(ψ×ϕ))ω(T×S)˜Cl(pr(ψ×ϕ))ω(K)˜F×G. Consequently, we have sx˜S˜Clψω(S)˜F and ty˜T˜Clψω(T)˜G. It follows that (U,ψ,B) and (V,ϕ,D) are supra-soft ω-r.

    Question 5.21. Let (U,ψ,B) and (V,ϕ,D) be two supra-soft ω-r supra-STSs. Is (U×V,pr(ψ×ϕ),B×D) supra-soft ω-r?

    Theorem 5.22. If (U,ψ,B) is a supra-soft ω-r supra-STS, then for any VU, (V,ψV,B) is supra-soft ω-r.

    Proof: Let M(ψV)c and by˜CVM. Choose N ψc with M=N˜CV. Since (U,ψ,B) is a supra-soft ω-r, and we have N ψc and by˜1BN, we find Fψ and Gψω with ay˜F, N˜G, and F˜G=0B. Then, by˜F˜CVψV, M=N˜CV˜G˜CV with G˜CV(ψω)V, and (F˜CV)˜(G˜CV)=(F˜G)˜CV=0B˜CV=0B. Moreover, by Theorem 3.19, G˜CV(ψV)ω. This completes the proof.

    Soft set theory demonstrates its effectiveness as a mathematical strategy for addressing uncertainty, which is crucial for cognitive analysis and artificial intelligence. Based on soft set theory, many mathematical structures have emerged, including soft topologies and some of their extensions, such as supra-soft topologies.

    In this paper, we first defined and investigated a new supra-soft topology using a collection of classical supra-topologies. We then defined supra-soft ω-open sets, a new generalization of supra-soft open sets, using the supra-soft open sets and the countable soft sets. We also showed that supra-soft ω-open sets form a new supra-soft set that is finer than the given supra-soft topology. Finally, we defined and investigated two new classes of supra-topological spaces: supra-soft ω-local indiscrete and supra-soft ω-regular spaces. Specifically, we obtained subspace and product results of supra-soft ω-regular spaces. Finally, we explored the connections between our new concepts and their counterparts in supra-topology.

    We intend to do the following in the future papers:

    (ⅰ) Define new continuity concepts between supra-soft topological spaces via supra-soft ω-open sets.

    (ⅱ) Define supra-soft semi ω-open sets in supra-soft topological spaces.

    (ⅲ) Define soft ω-Hausdorff spaces in supra-soft topological spaces.

    (ⅳ) Explore how our new notions and results can be applied in digital and approximation spaces, as well as decision-making problems.

    (ⅴ) Define supra-fuzzy ω-open sets in supra-fuzzy topological spaces.

    Dina Abuzaid and Samer Al-Ghour: Conceptualization, methodology, formal analysis, writing–original draft, writing–review and editing, and funding acquisition. All authors have read and approved the final version of the manuscript for publication.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    The authors declare that they have no conflicts of interest.



    [1] Apicella G, Dacorogna M, Di Lorenzo E, et al. (2019) Improving the forecast of longevity by combining models. N Am Actuar J 23: 298–319. https://doi.org/10.1080/10920277.2018.1556701 doi: 10.1080/10920277.2018.1556701
    [2] Booth H, Hyndman RJ, Tickle L, et al. (2006) Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions. Demogr Res 15: 298–319. https://doi.org/10.4054/DemRes.2006.15.9 doi: 10.4054/DemRes.2006.15.9
    [3] Bozzo G, Levantesi S, Menzietti M (2021) Longevity risk and economic growth in sub-populations: evidence from Italy. Decis Econ Financ 44: 101–115. https://doi.org/10.1007/s10203-020-00275-x doi: 10.1007/s10203-020-00275-x
    [4] Brouhns N, Denuit M, Vermunt JK (2002) A Poisson log-bilinear regression approach to the construction of projected lifetables. Insur Math Econ 31: 373–393. https://doi.org/10.1016/S0167-6687(02)00185-3 doi: 10.1016/S0167-6687(02)00185-3
    [5] Cairns A, Blake D, Dowd K (2006) A two-factor model for stochastic mortality with parameter uncertainty: theory and calibration. J Risk Insur 73: 687–718. https://doi.org/10.1016/S0167-6687(02)00185-3 doi: 10.1016/S0167-6687(02)00185-3
    [6] Cairns A, Blake D, Dowd K, et al. (2009) A quantitative comparison of stochastic mortality models using data from England and Wales and the United States. N Am Actuar J 13: 1–35. https://doi.org/10.1080/10920277.2009.10597538 doi: 10.1080/10920277.2009.10597538
    [7] Chen H, MacMinn R, Sun T (2015) Multi-population mortality models: A factor copula approach. Insur Math Econ 63: 135–146. https://doi.org/10.1016/j.insmatheco.2015.03.022 doi: 10.1016/j.insmatheco.2015.03.022
    [8] Chen RY, Millossovich P (2018) Sex-specific mortality forecasting for UK countries: a coherent approach. Eur Actuar J 8: 69–95. https://doi.org/10.1007/s13385-017-0164-0 doi: 10.1007/s13385-017-0164-0
    [9] Currie ID (2013) Smoothing constrained generalized linear models with an application to the Lee-Carter model. Stat Model 13: 69–93. https://doi.org/10.1177/1471082X12471373 doi: 10.1177/1471082X12471373
    [10] Currie ID, Durban M, Eilers PHC (2018) Smoothing and forecasting mortality rates. Stat Model 4: 279–298. https://doi.org/10.1191/1471082X04st080oa doi: 10.1191/1471082X04st080oa
    [11] Danesi IL, Haberman S, Millossovich P (2018) Forecasting mortality in subpopulations using Lee–Carter type models: A comparison. Insur Math Econ 62: 151–161. https://doi.org/10.1016/j.insmatheco.2015.03.010 doi: 10.1016/j.insmatheco.2015.03.010
    [12] Delwarde A, Denuit M, Eilers P (2007) Smoothing the Lee–Carter and Poisson log-bilinear models for mortality forecasting: a penalized log-likelihood approach. J Popul Res 7: 29–48. https://doi.org/10.1177/1471082X0600700103 doi: 10.1177/1471082X0600700103
    [13] De Waegenaere A, Melenberg B, Stevens R (2010) Longevity risk. De Econ 158: 151–192. https://doi.org/10.1007/s10645-010-9143-4 doi: 10.1007/s10645-010-9143-4
    [14] Enchev V, Kleinow T, Cairns A (2017) Multi-population mortality models: fitting, forecasting and comparisons. Scand Actuar J 4: 319–342. https://doi.org/10.1080/03461238.2015.1133450 doi: 10.1080/03461238.2015.1133450
    [15] Franzini L, Giannoni M (2010) Determinants of health disparities between Italian regions. BMC Public Health 10: 1–10. https://doi.org/10.1186/1471-2458-10-296 doi: 10.1186/1471-2458-10-296
    [16] Gao G, Shi Y (2021). Age-coherent extensions of the Lee–Carter model. Scand Actuar J 10: 998–1016. https://doi.org/10.1080/03461238.2021.1918578 doi: 10.1080/03461238.2021.1918578
    [17] Hainaut D, Denuit M (2020) Wavelet-based feature extraction for mortality projection. ASTIN B J IAA 50: 675–707. https://doi.org/10.1017/asb.2020.18 doi: 10.1017/asb.2020.18
    [18] Hyndman RJ, Ullah MS (2007) Robust forecasting of mortality and fertility rates: A functional data approach. Comput Stat & Data Anal 51: 4942–4956. https://doi.org/10.1016/j.csda.2006.07.028 doi: 10.1016/j.csda.2006.07.028
    [19] Hyndman R, Booth H, Yasmeen F (2017) Coherent mortality forecasting: the product-ratio method with functional time series models. Demography 50: 261–283. https://doi.org/10.1007/s13524-012-0145-5 doi: 10.1007/s13524-012-0145-5
    [20] Kleinow T (2015) A common age effect model for the mortality of multiple populations. Insur Math Econ 63: 147–152. https://doi.org/10.1007/s13524-012-0145-5 doi: 10.1007/s13524-012-0145-5
    [21] Lee RD, Carter LR (1992) Modeling and forecasting US mortality. J Am Stat Assoc 87: 659–671. https://doi.org/10.1080/01621459.1992.10475265 doi: 10.1080/01621459.1992.10475265
    [22] Li N, Lee R (2005) Coherent mortality forecasts for a group of populations: An extension of the Lee-Carter method. Demography 42: 575–594. https://doi.org/10.1353/dem.2005.0021 doi: 10.1353/dem.2005.0021
    [23] Li J (2013) A Poisson common factor model for projecting mortality and life expectancy jointly for females and males. Popul Stud 67: 111–126. https://doi.org/10.1080/00324728.2012.689316 doi: 10.1080/00324728.2012.689316
    [24] Nigri A, Levantesi S, Marino M, et al. (2019) A deep learning integrated Lee–Carter model. Risks 7: 33. https://doi.org/10.3390/risks7010033 doi: 10.3390/risks7010033
    [25] Perla F, Richman R, Scognamiglio S, et al. (2021) Time-series forecasting of mortality rates using deep learning. Scand Actuar J 2021: 1–27. https://doi.org/10.1080/03461238.2020.1867232 doi: 10.1080/03461238.2020.1867232
    [26] Renshaw A, Haberman S (2003) Lee–Carter mortality forecasting with age-specific enhancement. Insur Math Econ 33: 255–272. https://doi.org/10.1016/S0167-6687(03)00138-0 doi: 10.1016/S0167-6687(03)00138-0
    [27] Renshaw A, Haberman S (2006) A cohort-based extension to the Lee–Carter model for mortality reduction factors. Insur Math Econ 38: 556–570. https://doi.org/10.1016/j.insmatheco.2005.12.001 doi: 10.1016/j.insmatheco.2005.12.001
    [28] Richman R, Wüthrich MV (2021) A neural network extension of the Lee–Carter model to multiple populations. Ann Actuar Sci 15: 346–366. https://doi.org/10.1017/S1748499519000071 doi: 10.1017/S1748499519000071
    [29] Schnürch S, Kleinow T, Korn R (2021) Clustering-Based Extensions of the Common Age Effect Multi-Population Mortality Model. Risks 9: 45. https://doi.org/10.3390/risks9030045 doi: 10.3390/risks9030045
    [30] Shang HL, Yang Y (2021) Forecasting Australian subnational age-specific mortality rates. J Popul Res 38: 1–24. https://doi.org/10.1007/s12546-020-09250-0 doi: 10.1007/s12546-020-09250-0
    [31] Wilmoth JR and Shkolnikov V (2021) University of California, Berkeley (US), and Max Planck Institute for Demographic Research (Germany).
  • This article has been cited by:

    1. Dina Abuzaid, Samer Al-Ghour, Correction: Supra soft Omega-open sets and supra soft Omega-regularity, 2025, 10, 2473-6988, 10624, 10.3934/math.2025483
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(2203) PDF downloads(154) Cited by(2)

Figures and Tables

Figures(10)  /  Tables(2)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog