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Neutrosophic Soft Rough Topology and its Applications to Multi-Criteria Decision-Making

Muhammad Riaz, Florentin Smarandache, Faruk Karaaslan, Masooma Raza Hashmi, Iqra Nawaz
2020 Zenodo  
Furthermore, we aim to develop some multi-criteria decision-making (MCDM) methods based on NSR-set and NSR-topology to deal with ambiguities in the real-world problems.  ...  For this purpose, we establish algorithm 1 for suitable brand selection and algorithm 2 to determine core issues to control crime rate based on NSR-lower approximations, NSR-upper approximations, matrices  ...  NSR-set in multi-criteria decision-making In this section, we present an idea for multi-criteria decision-making method based on the neutrosophic soft rough sets − .  ... 
doi:10.5281/zenodo.3951663 fatcat:giklgt3oxjem5chath54ibiete

Two Different Views for Generalized Rough Sets with Applications

Radwan Abu-Gdairi, Mostafa A. El-Gayar, Mostafa K. El-Bably, Kamel K. Fleifel
2021 Mathematics  
The proposed methods depend basically on a new neighborhood (called basic-neighborhood).  ...  In the present paper, we suggest new sorts of rough set approximations using a multi-knowledge base; that is, a family of the finite number of general binary relations via different methods.  ...  The second method is very important for multiinformation systems and hence, it can be useful in multi attributes decision making.  ... 
doi:10.3390/math9182275 fatcat:gsor6h6wgvgp5nshr7dlv4cmjm

Multi-Span and Multiple Relevant Time Series Prediction Based on Neighborhood Rough Set

Xiaoli Li, Shuailing Zhou, Zixu An, Zhenlong Du
2021 Computers Materials & Continua  
Fuzzy neighborhood rough set de ne the fuzzy decision of a sample by using the concept of fuzzy neighborhood.  ...  In this paper, a rainfall runoff forecast model based on the variable-precision fuzzy neighborhood rough set (VPFNRS) is constructed to predict Watershed runoff value.  ...  The rainfall runoff prediction method can be extended to similar climactic zones. For different hydrological conditions, it needs to be recti ed for predicting the runoff in the new zone.  ... 
doi:10.32604/cmc.2021.012422 fatcat:vscnrpduc5dzrcuctlrl22c4se

Cognitive Properties of MADM and Hybrid Rough Sets for Efficient Healthcare Test Diagnosis

2021 International Journal of Advanced Trends in Computer Science and Engineering  
To solve this problem, we use multi attribute decision making methods to identify alternative attributes through a hybrid methodology of rough and fuzzy relations in apessimistic and optimistic parameter  ...  Healthcare test diagnostic comprises the methods of finding test results in accordance with the prescribed symptoms of disease.  ...  using features of covering and fuzzy approximation space in an attempt with multi attribute decision making method.  ... 
doi:10.30534/ijatcse/2021/921022021 fatcat:aqz634b5dbhffduvnsjo2bck7y

Novel models of fuzzy rough coverings based on fuzzy α-neighborhood and its application to decision-making

Jue Ma, Mohammed Atef, Ahmed Mostafa Khalil, Nasruddin Hassan, Gui-Xiu Chen
2020 IEEE Access  
[38] set up the Fuzzy-covering based (I , T )fuzzy rough set models and multi-attribute decision-making applications while Jiang et al.  ...  [39] proposed covering based variable precision (I, T )-fuzzy rough sets with applications to multi-attribute decision-making. Ziarko [40] established variable precision rough sets (VPRSs).  ... 
doi:10.1109/access.2020.3044213 fatcat:kjpeqdhfube6foapyxggwgeqkm

Using Neighborhood Rough Set Theory to Address the Smart Elderly Care in Multi-Level Attributes

Jining Zhou, Bo Zhang, Runhua Tan, Ming-Lang Tseng, Remen Chun-Wei Lin, Ming K. Lim
2020 Symmetry  
The neighborhood rough set theory was adopted for attributes reduction and the weight distribution of condition attributes based on the concept of importance level.  ...  The result indicates traditional concepts have a certain impact on the adoption of smart elderly care and a condition attribute of residence also has a slight influence on the symmetric decision attribute  ...  In addition, Thuy and Wongthanavasu proposed a method for a fast, deterministic reduction based on conditional information entropy and defined the original concept of attribute reduction based on the stripped  ... 
doi:10.3390/sym12020297 fatcat:65gd7gg2ovhk3gr7kvsiacs5yy

Multi-label Attribute Reduction Based on Variable Precision Fuzzy Neighborhood Rough Set

Panpan Chen, Menglei Lin, Jinghua Liu
2020 IEEE Access  
Inspired by this, we generalize variable precision fuzzy neighborhood rough set in single-label learning to fit multilabel learning, and introduce a novel multi-label attribute reduction model based on  ...  and its improvement [49] , and the attribute reduction algorithm based on heuristic information entropy [22] , [35] .  ... 
doi:10.1109/access.2020.3010314 fatcat:yh3tpxiqlnfonmufu3574okmva

Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature

Abbas Mardani, Mehrbakhsh Nilashi, Jurgita Antucheviciene, Madjid Tavana, Romualdas Bausys, Othman Ibrahim
2017 Complexity  
system, inductive reasoning, intelligent systems, data mining, pattern recognition, decision-making, and machine learning.  ...  Accordingly, the systematic and meta-analysis approach, which is called "PRISMA," has been proposed and the selected articles were classified based on the author and year of publication, author nationalities  ...  While there are a variety of existing methods for various application areas from imprecise data, the fuzzy-rough set method has an advantage for decision-making for large volumes of data since it focuses  ... 
doi:10.1155/2017/1608147 fatcat:o6khgyofg5g55hwgdj2y6angii

Spectral Clustering with Neighborhood Attribute Reduction Based on Information Entropy

Hongjie Jia, Shifei Ding, Heng Ma, Wanqiu Xing
2014 Journal of Computers  
This paper modifies the attribute reduction method based on neighborhood rough sets, in which the attribute importance is combined with information entropy to select the appropriate attributes.  ...  Then we introduce this attribute reduction method to improve spectral clustering and propose NRSR-SC algorithm.  ...  Algorithm 1: Neighborhood attribute reduction algorithm based on information entropy Input: Neighborhood decision system = NDT D A U , , . Output: The reduced attribute set red.  ... 
doi:10.4304/jcp.9.6.1316-1324 fatcat:e6bm3mpsqbhqvcpck2ygniupme

Overlap Functions Based (Multi-Granulation) Fuzzy Rough Sets and Their Applications in MCDM

Xiaofeng Wen, Xiaohong Zhang
2021 Symmetry  
new fuzzy β-neighborhood lower and upper approximate operators are analyzed and studied.  ...  By theoretical analysis for the fuzzy covering (multi-granulation) fuzzy rough sets, the solutions to problems in multi-criteria decision-making (MCDM) and multi-criteria group decision-making (MCGDM)  ...  Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sym13101779 fatcat:47r22ojsnvg6xbpq5cyovzmgqi

Multi-label classification by exploiting label correlations

Ying Yu, Witold Pedrycz, Duoqian Miao
2014 Expert systems with applications  
This paper presents two novel multi-label classification algorithms based on the variable precision neighborhood rough sets, called multi-label classification using rough sets (MLRS) and MLRS using local  ...  Given a new instance, MLRS determines its location and then computes the probabilities of labels according to its location.  ...  Acknowledgments The authors would like to thank the Editors for their kindly help and the anonymous referees for their valuable comments and helpful suggestions.  ... 
doi:10.1016/j.eswa.2013.10.030 fatcat:agzqrwo3ijcolh6sabardmf7cm

Special issue on recent advances in metaheuristics

Teodor Gabriel Crainic, Michel Gendreau, Louis-Martin Rousseau
2010 Journal of Heuristics  
Twenty-seven manuscripts were received and went through a strict review process, at the end of which twelve papers covering a broad spectrum of methodological and application topics in metaheuristics were  ...  The first four papers of the special issue focus on new approaches that combine metaheuristics with other problem-solving paradigms to yield highly effective solution methods for difficult problems.  ...  A key feature of their method is its first phase, in which they obtain an initial population of solutions which makes up a good approximation of the set of extreme supported efficient solutions.  ... 
doi:10.1007/s10732-010-9132-4 fatcat:akkt2gkchzf2lot7bylsrokxrq

A novel ensemble method for k -nearest neighbor

Youqiang Zhang, Guo Cao, Bisheng Wang, Xuesong Li
2019 Pattern Recognition  
Based on a progressive kNN, the random subspace method, attribute reduction, and Bagging, a novel algorithm termed RRSB (reduced random subspace-based Bagging) is proposed for construct ensemble classifier  ...  kNN through a multimodal perturbation-based method.  ...  possible class labels according to the belief function in Eq. 6; and 5) Make a decision based on Eq. 6.  ... 
doi:10.1016/j.patcog.2018.08.003 fatcat:w4gwnknv4za5zcbyk6nswpli5u

Application of an Optimized SVR Model of Machine Learning

Zhikun Xu, Yabin Gao, Yingying Jin
2014 International Journal of Multimedia and Ubiquitous Engineering  
It is a fundamental way to the computer intelligence. Support vector machine is one of the important methods in the field of machine learning.  ...  In this paper, a novel SVR model is proposed to forecast GDP.  ...  Neighborhood rough set model form a neighborhoodbased on each point in real number space.  ... 
doi:10.14257/ijmue.2014.9.6.08 fatcat:eskvcme65nepno7u32jzhceqqu

A Parallel Rough Set Theory for Nonlinear Dimension-Reduction in Big Data Analysis

Amsaveni Muthusamy, AVP College of Arts and Science, Duraisamy Subramani, Chikkanna Government Arts College
2019 International Journal of Intelligent Engineering and Systems  
Based on two descriptions of lower approximation and upper approximation, a rough set is constructed. Then a reduct is detected using inner importance measure and outer importance measure.  ...  It addressed the non-linear relationships within the attributes. The data dimension was reduced through a parametric mapping.  ...  An attribute reduction method [10] was proposed based on Max-Decision Neighborhood Rough Set model (MDNRS) for attribute reduction.  ... 
doi:10.22266/ijies2019.1031.17 fatcat:zv5unj6e55azle6x7we5znwdqi
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