Research article

Sub-base local reduct in a family of sub-bases

  • Received: 15 January 2022 Revised: 26 April 2022 Accepted: 05 May 2022 Published: 13 May 2022
  • MSC : 54A05, 54B15, 54C05, 54C10

  • This paper discusses sub-base local reducts in a family of sub-bases. Firstly, definitions of sub-base local consistent sets and sub-base local reducts are provided. Using the sub-base local discernibility matrix, a necessary and sufficient condition for sub-base local consistent sets is presented. Secondly, properties of the sub-base local core are studied. Finally, sub-base local discernibility Boolean matrices are defined, and the calculation method is given. Utilizing sub-base local discernibility Boolean matrices, an algorithm is devised to obtain sub-base local reducts.

    Citation: Liying Yang, Jinjin Li, Yiliang Li, Qifang Li. Sub-base local reduct in a family of sub-bases[J]. AIMS Mathematics, 2022, 7(7): 13271-13277. doi: 10.3934/math.2022732

    Related Papers:

    [1] Mamta Barik, Chetan Swarup, Teekam Singh, Sonali Habbi, Sudipa Chauhan . Dynamical analysis, optimal control and spatial pattern in an influenza model with adaptive immunity in two stratified population. AIMS Mathematics, 2022, 7(4): 4898-4935. doi: 10.3934/math.2022273
    [2] Nenghui Kuang, Huantian Xie . Derivative of self-intersection local time for the sub-bifractional Brownian motion. AIMS Mathematics, 2022, 7(6): 10286-10302. doi: 10.3934/math.2022573
    [3] Yanlan Zhang, Changqing Li . The discernibility approach for multi-granulation reduction of generalized neighborhood decision information systems. AIMS Mathematics, 2024, 9(12): 35471-35502. doi: 10.3934/math.20241684
    [4] Man Jiang . Properties of R0-algebra based on hesitant fuzzy MP filters and congruence relations. AIMS Mathematics, 2022, 7(7): 13410-13422. doi: 10.3934/math.2022741
    [5] Adnan, Khalid Abdulkhaliq M. Alharbi, Waqas Ashraf, Sayed M. Eldin, Mansour F. Yassen, Wasim Jamshed . Applied heat transfer modeling in conventional hybrid (Al2O3-CuO)/C2H6O2 and modified-hybrid nanofluids (Al2O3-CuO-Fe3O4)/C2H6O2 between slippery channel by using least square method (LSM). AIMS Mathematics, 2023, 8(2): 4321-4341. doi: 10.3934/math.2023215
    [6] Saleh Mousa Alzahrani . Enhancing thermal performance: A numerical study of MHD double diffusive natural convection in a hybrid nanofluid-filled quadrantal enclosure. AIMS Mathematics, 2024, 9(4): 9267-9286. doi: 10.3934/math.2024451
    [7] Yimeng Xi, Zhihong Liu, Ying Li, Ruyu Tao, Tao Wang . On the mixed solution of reduced biquaternion matrix equation $ \sum\limits_{i = 1}^nA_iX_iB_i = E $ with sub-matrix constraints and its application. AIMS Mathematics, 2023, 8(11): 27901-27923. doi: 10.3934/math.20231427
    [8] Saiwan Fatah, Arkan Mustafa, Shilan Amin . Predator and n-classes-of-prey model incorporating extended Holling type Ⅱ functional response for n different prey species. AIMS Mathematics, 2023, 8(3): 5779-5788. doi: 10.3934/math.2023291
    [9] Scala Riccardo, Schimperna Giulio . On the viscous Cahn-Hilliard equation with singular potential and inertial term. AIMS Mathematics, 2016, 1(1): 64-76. doi: 10.3934/Math.2016.1.64
    [10] Xiaorui He, Jingyong Tang . A smooth Levenberg-Marquardt method without nonsingularity condition for wLCP. AIMS Mathematics, 2022, 7(5): 8914-8932. doi: 10.3934/math.2022497
  • This paper discusses sub-base local reducts in a family of sub-bases. Firstly, definitions of sub-base local consistent sets and sub-base local reducts are provided. Using the sub-base local discernibility matrix, a necessary and sufficient condition for sub-base local consistent sets is presented. Secondly, properties of the sub-base local core are studied. Finally, sub-base local discernibility Boolean matrices are defined, and the calculation method is given. Utilizing sub-base local discernibility Boolean matrices, an algorithm is devised to obtain sub-base local reducts.



    Rough set theory, proposed by Pawlak [1], provides an approach to uncertainty management. In [2], the theoretical relationships connecting rough set theory and belief function theory were investigated, and their applications in knowledge representation and machine learning were researched. Covering rough sets [3], generalizations of the classical rough sets, have been proved to be suitable for discussing covering information systems. As a significant problem, the reduct problem has captured considerable attention of numerous scholars. Many methods were provided to find reducts of covering rough sets [4,5,6,7,8]. In addition, the invariant of separation in covering approximation spaces was concerned in [9].

    Topology is a useful tool for investigating rough set theory and its applications. The inter-dependencies of topology and rough set theory were emphasized in [10]. The object of general topology is to study topological properties, namely, invariants of homeomorphism [11]. In the light of the properties of the topological rough membership function, sub-base reducts in a family of sub-bases were defined in [12]. To further research sub-base reducts in a family of sub-bases from the point of view of general topology, the concept of a minimal family of sub-bases was presented in [13]. By showing the relationship between reducts in covering information systems and minimal families of sub-bases, [13] provided an approach to deriving a minimal family of sub-bases. Moreover, minimal bases and minimal sub-bases were considered in [14,15].

    It is not hard to see that the above-cited works are focused on sub-base reducts on a given universal set. But some elements in the given universal set may be not important for specific problems. Motivated by that, this paper intents to discuss sub-base local reducts in a family of sub-bases, which has not been considered in the existing references. The main contributions are twofold. (i) The properties of sub-base local reducts in a family of sub-bases are investigated. (ii) The approach to finding sub-base local reducts in a family of sub-bases is provided, along with an algorithm for achieving it.

    The remainder of this paper is organized as follows. Section 2 gives some basic information about sub-base local reducts. Section 3 illustrates how to obtain sub-base local reducts according to Boolean matrices. Section 4 has some concluding remarks.

    Suppose Si is a sub-base for finite topological space (X,τi) for i=1,2,,n, Δ={S1,S2,,Sn}, and SΔ=ni=1Si={ni=1Si|SiSi,i=1,2,n}. Then SΔ is a sub-base for a topology τΔ of finite set X. Suppose P is a family of subsets of X. A minimal set containing x with respect to P is denoted by NP(x)={U|xUP}.

    Under the premise of keeping topology unchanged, the sub-base reduct of a family of sub-bases is defined according to the unique open neighborhood in [12,13]. However, one may concern sub-base reducts related to several open sets. Hence, the concept of the sub-base local reduct is provided.

    Definition 2.1. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n and Δ={S1,S2,,Sn}. Suppose F={F|FSΔ}. Δ1Δ is called a sub-base local consistent set with respect to F of Δ if FSΔ. If Δ is a sub-base local consistent set with respect to F of Δ, and for any proper subset Δ2 of Δ1, FSΔ, then Δ1 is called a sub-base local reduct with respect to F of Δ.

    Remark 2.1. Compared with the local reduct discussed in rough set theory, the sub-base local reduct in a family of sub-bases also focuses on a subset A of the given universal set X. Thus, the sub-base local reduct in a family of sub-bases is consistent with the local reduct discussed in rough set theory. When discussing the sub-base local reduct in a family of sub-bases, subset A is obtained via the union of those concerned open sets. But considering the local reduct in rough set theory, subset A is determined according to elements that are indispensable for certain decision classes.

    The sub-base local discernibility matrix is defined in the following.

    Definition 2.2. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n and Δ={S1,S2,,Sn}. Suppose F={F|FSΔ}. The sub-base local discernibility matrix with respect to F of Δ is denoted by DF(Δ)={D(x,y)|x,yX}, where

    (1) if there exists FF such that xF, but yF, then D(x,y)={SΔ|yNS(x)}.

    (2) Otherwise, D(x,y)=.

    Using the sub-base local discernibility matrix, a result of the sub-base local consistent set is presented.

    Theorem 2.1. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n, and Δ={S1,S,,Sn}.Suppose S={F|FSΔ}.Δ1Δ is a sub-base local consistent set with respect to F of Δ if and only if Δ1D(x,y) for D(x,y).

    Proof. Necessity. Assume there exist two points x,yX such that D(x,y), but Δ1D(x,y)=. Then SD(x,y) for each SΔ1, which means yNS(x) for each SΔ1. That is, yNSΔ1(x). Since D(x,y), for each FF satisfying xF,yF, there exists SΔ such that yNS(x). Because Δ1Δ is a sub-base local consistent set with respect to F of Δ, we have FSΔ1. Thus, NSΔ1(x)=(xA,ASΔ1,AFA)F, which contradicts with yNSΔ1. Hence, Δ1D(x,y) for D(x,y).

    Sufficiency. Assume Δ1 is not a sub-base local consistent set with respect to F of Δ. Then there exists FF such that FSΔ1. Thus, there exists a point xX such that NSΔ1{F}(x)NSΔ1(x). Since NSΔ1{F}(x)NSΔ1(x), there exists a point yX such that yNSΔ1(x), but yNSΔ1{F}(x). That is, yNSΔ(x) and yNS(x) for each SΔ1, which implies D(x,y)=, but Δ1D(x,y)=, which is a contradiction. Hence, Δ1 is a sub-base local consistent set with respect to F of Δ.

    The definition of the sub-base local core is proposed.

    Definition 2.3. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n, and Δ={S2,S2,,Sn}. Suppose F={F|FΔ}. If CF(Δ)={Δ1|FSΔ1}, then CF(Δ) is called a sub-base local core with respect to F of Δ.

    Some equivalent conditions about the sub-base local core are provided.

    Theorem 2.2. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n, and Δ={S1,S2,,Sn}, Suppose F={F|FSΔ}.Then the following conclusions are equivalent.

    (1) SCF(Δ).

    (2) There exist x,yX such that D(x,y)={S}.

    (3) There exists FF such that FSΔ{S}.

    Proof. (1)(2). Assume |D(x,y)|2 for any points x,yX. Denote Δ={D(x,y){S}|x,yX}. It is easy to see that ΔD(x,y) for D(x,y). According to Theorem 2.1, Δ is a sub-base local consistent set with respect to F of Δ. Thus, there exists Δ1Δ such that Δ1 is a sub-base local reduct with respect to F of Δ, which contradicts with SCF(Δ). Hence, there exist x,yX such that D(x,y)={S}.

    (2)(3). Assume FSΔ{S}. Then, Δ{S} is a sub-base local consistent set with respect to F of Δ. Based on Theorem 2.1, (Δ{S})D(x,y) for D(x,y), which contradicts with (2). Hence, there exists FF such that FSΔ{S}.

    (3)(1). Since there exists FF such that FSΔ{S}, one concludes that Δ{S} is not a sub-base local consistent set with respect to F of Δ. Thus, for any ΔΔ{S}, Δ is not a sub-base local reduct with respect to F of Δ, which contradicts with (1). Hence, SCF(Δ) is proved.

    To provided a simple method to find a sub-base local reduct of a given Δ, the following definitions are used to construct a Boolean matrix.

    Definition 3.1. [5] Let X={x1,x2,,xm} and AX. The characteristic function is defined as f(A)=(f1,f2,,fm) ( denotes the transpose throughout this paper), where

    fi={1,xiA,0,xiA.

    Definition 3.2. [13] Let P be a family of subsets of X with X={x1,x2,,xm} and P={P1,P2,, Pk}. The characteristic matrix of P is defined as MP=(f(P1),f(P2),, f(Pk)).

    Definition 3.3. [4] Let M=(mij)n×m be a matrix. Define two matrix operators and as follows:

    (1) M=(mij)n×m, where

    mij={1,mij=0,0,mij0.

    (2) M=(mij)n×m, where

    mij={0,mij=0,1,mij0.

    Definition 3.4. [16] Let A=(aij)n×m and B=(bij)n×m be two matrices. The Hadamard product of A and B is defined as AB=(aijbij)n×m.

    The sub-base local discernibility Boolean matrix is defined.

    Definition 3.5. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n with X={x1,x2,,xm}, and Δ={S1,S2,,Sn}. Suppose F={F|FSΔ}. For any Δ1Δ, define a sub-base local discernibility Boolean matrix DF(Δ1)=(dij)m×m satisfying:

    (1) If there exists FF such that xiF,xjF and xjNSΔ1(xi), then dij=1.

    (2) Otherwise, dij=0.

    From the following theorem, the sub-base local discernibility Boolean matrix is computed.

    Theorem 3.1. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n with X={x1,x2,,xm}.Suppose F={F|FSΔ}.Then the following results hold.

    (1) DF(S)=≈(MS(MS)(MF(MF))) for each SΔ.

    (2) DF(SΔ1)=≈(SΔ1DF(S)) for any Δ1Δ.

    Proof. Given a matrix M, denote its i-th row by Rowi(M) and its element in the i-th row and j-th column by Mij.

    (1) Denote S={S1,S2,,Sk} and F={F1,F2,,Fq}. It is easy to find that Rowi(MS(MS))=1jk(MS)ijRowj(MS). According to Definitions 3.1 and 3.2, (MS)ij=1 means xiSj, and (MS)ij=0 means xiSj. Thus, we get Rowi(MS(MS))=1jk(MS)ijRowj(MS)=xiSjRowj(MS). That is, (MS(MS))il=xiSj(MS)il. Similarly, (MF(MF))il=xiSj(MF)il. If (DF(S))il=1, then there exists FpF such that xiFp,xlFp and xlNSΔ(xi). Hence, we obtain (MF)ip=1 and (MF)pl=1. That is, (MF(MF))il1. Since xlNSΔ(xi), there exists Sj0S such that xiSj0 but xlSj0. So we have (MS(MS))il1. Therefore, we prove ((MS(MS)(MF(MF))))il=1. Similarly, if (DF(S))il=0, then ((MS(MS)(MF(MF))))il=0. Consequently, DF(S)=≈(MS(MS)(MF(MF))) for each SΔ.

    (2) If (DF(SΔ1))ij=1, then there exists FF such that xiF,xjF and xjNSΔ1(xi). Thus, there exists SΔ1 such that xjNS(xi). From (1), we conclude that (DF(S))ij=1, i.e., ((SΔ1DF(S)))ij=1. If (DF(SΔ1))ij=0, then it is similar to proving ((SΔ1DF(S)))ij=0. Consequently, DF(SΔ1)=≈(SΔ1DF(S)) for any Δ1Δ.

    Based on the results above, Theorem 3.2 is proved.

    Theorem 3.2. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n with X={x1,x2,,xm}.Suppose F={F|FSΔ}.Then the following results hold.

    (1) For each Δ1Δ, Δ1 is a sub-base local consistent set with respect to F of S if and only if DF(Δ1)=DF(Δ).

    (2) For each SΔ, SCF(Δ) if and only if DF(Δ{S})DF(Δ).

    Proof. (1) According to Theorem 2.1, S is a sub-base local core with respect to F if and only if Δ1D(xi,j) for D(xi,xj). From Definitions 2.2 and 3.5, D(xi,xj) is equivalent to (DF(Δ))ij=1. Δ1D(xi,xj) is equivalent to xjNSΔ1(xi), i.e., (DF(Δ1))ij=1. Hence, we conclude that DF(Δ1)=DF(Δ).

    (2) From Theorem 2.2, S is a sub-base local core with respect to F if and only if there exists xi,xjX such that D(xi,xj)={S}. It is equivalent to (DF(Δ))ij=1, but (DF(Δ{S}))ij=0. Hence, DF(Δ{S})DF(Δ).

    Moreover, a necessary and sufficient condition for the sub-base local reduct is presented.

    Corollary 3.1. Let Si be a sub-base for finite topological space (X,τi) for i=1,2,,n with X={x1,x2,,xm}.Suppose F={F|FSΔ}.Then Δ1Δ is a sub-base local reduct with respect to F of Δ if and only if Δ1 is a minimal subfamily of Δ satisfying DF(Δ1)=DF(Δ).

    On the basis of the analysis above, an algorithm is devised to find sub-base local reducts.

    Algorithm 1 Sub-base local reducts based on Boolean matrices
    Input: A family Δ of sub-bases and F={F|FSΔ}.
    Output: A minimal family Δ of sub-bases.
    1: Let Δ=;
    2: for each SΔ do
    3:  Compute DF(Δ{S}) according to Theorem 3.1;
    4:  if DF(Δ{S})DF(Δ); then
    5:    Let Δ=Δ{S}.//find all sub-base local cores;
    6:  end if
    7: end for
    8: while DF(Δ)DF(Δ) do
    9:  Let Δ=Δ{S0},
    10: where S0 satisfies |DF(Δ{S0})|=max{|DF(Δ{S0})|SΔΔ}, and || is the total number of 1 in a matrix;
    11: end while
    12: Return Δ.

     | Show Table
    DownLoad: CSV

    Remark 3.1. The time complexities of Steps 3-6 and Steps 8-10 are O(SΔα2|S|) and O(|Δ|1i=1α2(|Δ|i)), respectively, where α=|FFF|. Thus, the time complexity of Algorithm 1 is O(SΔα2|S|+|Δ|1i=1α2(|Δ|i)).

    Sub-base local reducts in a family of sub-bases have been investigated in this paper. Firstly, using the defined sub-base local discernibility matrix, a necessary and sufficient condition for the sub-base local consistent set has been provided. Then the sub-base local discernibility matrix has been employed to study properties of the sub-base local core. Finally, an algorithm has been devised to obtain sub-base local reducts via the sub-base local discernibility matrix.

    This work was supported by the National Natural Science Foundation of China (No. 11871259), the Natural Science Foundation of Fujian Province (No. 2019J01748), and the Key Program of the Natural Science Foundation of Fujian Province (No. 2020J02043).

    The authors declare that they have no conflict of interest.



    [1] Z. Pawlak, Rough sets, Int. J. Comput. Inf. Sci., 11 (1982), 341–356. https://doi.org/10.1007/BF01001956
    [2] A. Campagner, D. Ciucci, T. Denœux, Belief functions and rough sets: Survey and new insights, Int. J. Approx. Reason., 143 (2022), 192–215. https://doi.org/10.1016/j.ijar.2022.01.011 doi: 10.1016/j.ijar.2022.01.011
    [3] W. Żakowski, Approximations in the space (U,), Demonstr. Math. 16 (1983), 761–769.
    [4] A. H. Tan, J. J. Li, Y. J. Lin, G. P. Lin, Matrix-based set approximations and reductions in covering decision information systems, Int. J. Approx. Reason., 59 (2015), 68–80. https://doi.org/10.1016/j.ijar.2015.01.006 doi: 10.1016/j.ijar.2015.01.006
    [5] A. H. Tan, J. J. Li, G. P. Lin, Y. J. Lin, Fast approach to knowledge acquisition in covering information systems using matrix operations, Knowl. Based Syst., 79 (2015), 90–98. https://doi.org/10.1016/j.knosys.2015.02.003 doi: 10.1016/j.knosys.2015.02.003
    [6] D. G. Chen, C. Z. Wang, Q. H. Hu, A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets, Inf. Sci., 177 (2007), 3500–3518. https://doi.org/10.1016/j.ins.2007.02.041 doi: 10.1016/j.ins.2007.02.041
    [7] C. Z. Zhong, Q. He, D. G. Cheng, Q. H. Hu, A novel method for attribute reduction of covering decision systems, Inf. Sci., 254 (2014), 181–196. https://doi.org/10.1016/j.ins.2013.08.057 doi: 10.1016/j.ins.2013.08.057
    [8] T. Yang, Q. G. Li, B. L. Zhou, Related family: A new method for attribute reduction of covering information systems, Inf. Sci., 228 (2013), 175–191. https://doi.org/10.1016/j.ins.2012.11.005 doi: 10.1016/j.ins.2012.11.005
    [9] Q. F. Li, J. J. Li, X. Ge, Y. L. Li, Invariance of separation in covering approximation spaces, AIMS Math., 6 (2021), 5772–5785. https://doi.org/10.3934/math.2021341 doi: 10.3934/math.2021341
    [10] P. K. Singh, S. Tiwari, Topological structures in rough set theory: A survey, Hacett. J. Math. Stat., 49 (2020), 1270–1294.
    [11] R. Engelking, General Topology, Heldermann Verlag, Berlin, 1989.
    [12] J. J. Li, Y. L. Zhang, Reduction of subbases and its applications, Utilitas Math., 82 (2010), 179–192.
    [13] Y. L. Li, J. J. Li, Y. D. Lin, J. E. Feng, H. K. Wang, A minimal family of sub-bases, Hacett. J. Math. Stat., 49 (2019), 793–807.
    [14] Y. D. Lin, J. J. Li, L. X. Peng, Z. Q. Feng, Minimal base for finite topological space by matrix method, Fund. Inform., 174 (2020), 167–173. https://doi.org/10.3233/FI-2020-1937 doi: 10.3233/FI-2020-1937
    [15] Y. L. Li, J. J. Li, H. K. Wang, Minimal bases and minimal sub-bases for topological spaces, Filomat., 33 (2019), 1957–1965. https://doi.org/10.2298/FIL1907957L doi: 10.2298/FIL1907957L
    [16] X. D. Zhang, Matrix analysis and applications, Tsinghua University Press, Beijing, 2004 (in Chinese).
  • 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(2164) PDF downloads(82) Cited by(0)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog