Fuzzy Rough Set Models Based on Fuzzy Similarity Relation and Information Granularity in Multi-Source Mixed Information Systems DOI Creative Commons
Pengfei Zhang, Yuxin Zhao, Dexian Wang

и другие.

Mathematics, Год журнала: 2024, Номер 12(24), С. 4039 - 4039

Опубликована: Дек. 23, 2024

As a pivotal research method in the field of granular computing (GrC), fuzzy rough sets (FRSs) have garnered significant attention due to their successful overcoming limitations traditional handling continuous data. This paper is dedicated exploring application potential FRS models within framework multi-source complex information systems, which undoubtedly holds profound significance. Firstly, novel mixed system (MsMIS), encompassing five distinct data types, introduced, thereby enriching dimensions processing. Subsequently, similarity function, designed based on unique attributes data, utilized accurately quantify relations among objects. Building this foundation, T-norm operators are employed integrate matrices derived from different types into cohesive whole. integration not only lays solid foundation for subsequent model construction but also highlights value fusion analysis MsMIS. The integrated results subsequently develop models. Through rigorous examination perspective granularity, rationality proven, and its mathematical properties explored. contributes theoretical advancement GrC offers promising prospects practical implementation.

Язык: Английский

A Comparative Analysis of Three Data Fusion Methods and Construction of the Fusion Method Selection Paradigm DOI Creative Commons
Ziqi Liu, Ziqiao Yin, Zhilong Mi

и другие.

Mathematics, Год журнала: 2025, Номер 13(8), С. 1218 - 1218

Опубликована: Апрель 8, 2025

Multisource and multimodal data fusion plays a pivotal role in large-scale artificial intelligence applications involving big data. However, the choice of strategies for different scenarios is often based on experimental comparisons, which leads to increased computational costs during model training suboptimal performance testing. In this paper, we present theoretical analysis early fusion, late gradual methods. We derive equivalence conditions between fusions within framework generalized linear models. Moreover, analyze failure presence nonlinear feature-label relationships. Furthermore, propose an approximate equation evaluating accuracy methods as function sample size, feature quantity, modality number. also critical size threshold at dominance models undergoes reversal. Finally, introduce method selection paradigm selecting most appropriate prior task execution demonstrate its effectiveness through extensive numerical experiments. Our expected solve problems resource construction, improving scalability efficiency

Язык: Английский

Процитировано

0

I2QD: Unsupervised feature selection via information quality, quantity, and difference degree DOI
Pengfei Zhang, Yuxin Zhao, Lvhui Hu

и другие.

Information Processing & Management, Год журнала: 2025, Номер 62(5), С. 104173 - 104173

Опубликована: Апрель 9, 2025

Язык: Английский

Процитировано

0

Multiperiod distributionally robust portfolio selection with regime-switching under CVaR risk measures DOI Creative Commons
Fei Yu

AIMS Mathematics, Год журнала: 2025, Номер 10(4), С. 9974 - 10001

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

A Dynamic Unsupervised Feature Selection Method Based on Information Sets and Fuzzy Rough Sets DOI
Yuxin Zhao, Pengfei Zhang, Dexian Wang

и другие.

Lecture notes in computer science, Год журнала: 2025, Номер unknown, С. 175 - 188

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Leveraging Local Density Decision Labeling and Fuzzy Dependency for Semi-supervised Feature Selection DOI
Gangqiang Zhang, Jingjing Hu, Pengfei Zhang

и другие.

International Journal of Fuzzy Systems, Год журнала: 2024, Номер 26(8), С. 2805 - 2820

Опубликована: Май 26, 2024

Язык: Английский

Процитировано

2

A Bhattacharyya Triangular intuitionistic fuzzy sets with a Owa operator-based decision making for optimal portfolio selection in Saudi exchange DOI Creative Commons
Sunil Kumar Sharma

AIMS Mathematics, Год журнала: 2024, Номер 9(10), С. 27247 - 27271

Опубликована: Янв. 1, 2024

<p>The capital market in Saudi Arabia is fast growing. Assurance of an informed decision while investing the Stock Exchange critical. There has also been increased quest for advanced decision-making tools due to complexities selecting a given portfolio, which remains critical issue concern among investors face modern investment environment challenges. The research paper offered shall deliver innovative MCDM technique through model be developed Exchange. This uses BTIFS with OWA operator. A novelty proposed study identifying optimal weight that will obtained newly optimization known as TFOA. TFOA hybrid methodology brings on board strengths DMOA, MPA, and EO more precise efficient calculation ideal weights portfolio selection process. would improve adaptability effectiveness suggested structure. approach established by comparative analysis already existing methods MCDM, proves it superior portfolios. Sensitivity conducted evaluate strength dependability method. ranking weighted portfolios ELECTRE method also, establishes applicability BTIFS-OWA real life. results indicate along determining provides significant improvements accuracy compared traditional methods.</p>

Язык: Английский

Процитировано

2

Multi-sensor information fusion in Internet of Vehicles based on deep learning: A review DOI
Di Tian, Jiabo Li, Jingyuan Lei

и другие.

Neurocomputing, Год журнала: 2024, Номер 614, С. 128886 - 128886

Опубликована: Ноя. 12, 2024

Язык: Английский

Процитировано

2

Optimal scale combination selection based on genetic algorithm in generalized multi-scale decision systems for classification DOI
Ying Yang, Qinghua Zhang, Fan Zhao

и другие.

Information Sciences, Год журнала: 2024, Номер unknown, С. 121685 - 121685

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

2

A contemporary survey on multisource information fusion for smart sustainable cities: Emerging trends and persistent challenges DOI Creative Commons
Houda Orchi, Abdoulaye Baniré Diallo, Halima Elbiaze

и другие.

Information Fusion, Год журнала: 2024, Номер 114, С. 102667 - 102667

Опубликована: Сен. 4, 2024

Язык: Английский

Процитировано

1

Decision methods based on Bonferroni mean operators and EDAS for the classifications of circular pythagorean fuzzy Meta-analysis DOI Creative Commons

Weiwei Jiang,

Zeeshan Ali, Muhammad Waqas

и другие.

AIMS Mathematics, Год журнала: 2024, Номер 9(10), С. 28273 - 28294

Опубликована: Янв. 1, 2024

<p>Meta-analysis is a statistical technique used to process an overall summary estimation, and the of meta-analysis mostly in medicine, social science, psychology. In this manuscript, we aimed combine techniques Bonferroni mean (BM) operator based on circular Pythagorean fuzzy (CPF) sets, called CPF (CPFBM) operator, weighted (CPFWBM) described their special cases with help two parameters, "s" "t", some describable properties them are also proposed. Further, present evaluation distance from average solution (EDAS) proposed operators. Moreover, use examples show flexibility dominance operators by comparing methods existing techniques.</p>

Язык: Английский

Процитировано

0