IEEE Transactions on Fuzzy Systems

Recently, the three-way decision models based on prospect theory have attracted much attention, because they can well consider the risk attitude of decision makers when decisions involve gains and losses. However, in terms of reference point selection for ...

By offering a robust framework, granular computing empowers the field to effectively navigate and manage such challenging information, thereby facilitating human-like reasoning and decision-making capabilities. Within this context, a multi-scale ...

Discovering valuable knowledge from massive time series data is challenging due to sophisticated temporal relationships and inherent uncertainties. This article proposes a new multigranularity fuzzy association analysis of multigranularity incorporated ...

Computational intelligence is increasingly applied to complex decision-making challenges, leveraging its data analysis prowess. Hybrid human–artificial intelligence models enhance the grasp of intricate social behaviors, offering valuable insights ...

In this article, we propose an automatic trading system for portfolio selection that incorporates an investor's trading strategy (aggressive, conservative, or neutral). The system employs technical indicators to forecast assets' future price ...

Modern industrial processes often exhibit complex and uncertain operating state fluctuations due to the diversification of production materials, the complexity of production processes, and the harsh production environment. To address the real-time control ...

Dynamic pruning is an effective model compression method to reduce the computational cost of networks. However, existing dynamic pruning methods are limited to pruning along a single dimension (channel, spatial, or depth), which cannot maximally excavate ...

Myocardial scar regions appear in cardiac magnetic resonance images of patients with myocardial infarction. Implantable cardioverter defibrillators (ICDs) can be used to effectively prevent arrhythmias and even death caused by myocardial infarction. ...

Many models and methods have been developed to determine numerical thresholds in three-way decision. However, there are challenges such as local optimum-based thresholds, initial point-related optimal solutions, and a limited model generalization. To ...

A bunch of stream clustering algorithms have been proposed recently to mine data streams generated at high speeds from hardware platforms and software applications. Density-based methods are widely used because they can handle outliers and capture ...

Heterogeneous multiagent system (MAS) has been attracting increasing attention in many application areas, but the safety and reliability of MAS are still challenging issues. Fault diagnosis is a necessary technology to ensure the safety and reliability of ...

The node importance evaluation of the Internet of drones, also called unmanned aerial vehicle swarm network, can assist network administrators in implementing security protection for important nodes, slowing down attacks on important nodes and providing ...

Most of the existing multiattribute decision-making models under multiscale decision information systems are established by selecting the optimal scale or fusing multiscale information into a single scale. These models will lose part of the decision ...

Currently, three-way decision with neighborhood rough sets (3WDNRS) is widely used in many fields. The core of 3WDNRS is to calculate threshold pairs to divide a neighborhood space into three pairwise disjoint regions. The majority of research on 3WDNRS ...

This study Present a novel group three-way decision (TWD) method that effectively addresses decision-making problems characterized by interval-valued uncertain information by integrating regret theory and the consensus reaching process (CRP) model. The ...

In this article, an imitation learning framework is innovatively developed for robot skills learning in violin bowing. The introduction of dynamic movement primitives (DMPs) to model motion addresses issues such as the uncertainty in changing string ...

Graph classification has always been a research hotspot in the field of graph neural networks and related areas. However, due to the complexity of graph data, finding a feasible algorithm that balance efficiency and accuracy remains a challenge. In this ...

Presently, intelligent games have emerged as a substantial research area. Nonetheless, the slow convergence of intelligent wargame training and the low success rates of agents against specific rules present challenges. In this article, we propose a game ...

Human-centric instructional videos provide opportunities for users to learn real-world multistep tasks, such as cooking, makeup, and using professional tools. However, these lengthy videos always lead to a tedious learning experience, making it ...

Feature selection facilitates system processing, and it relies on knowledge granulation and uncertainty measurement. Focusing on ordered decision systems, the fuzzy dominance neighborhood (FDN) granulation and corresponding condition entropy have recently ...

Fuzzy convex optimization problems with fuzzy coefficients (FCOPFCs) arise in many applications. Although many neurodynamics-based models have been proposed for solving FCOPFCs, most of them are designed for FCOPFCs with equality or inequality constraints ...

Weakly supervised anomaly detection (WSAD) has gained increasing attention due to its core idea of enhancing the performance of unsupervised anomaly detection by leveraging prior knowledge from a limited number of labeled anomalies. In this article, we ...

Pattern recognition plays an important role in the process of knowledge discovery. The construction of easily describable and interpretable classification rules is of vital importance in pattern recognition. In this study, we propose a development of ...

Feature selection in a traditional binary classification algorithm is always used in the stage of dataset preprocessing, which makes the obtained features not necessarily the best ones for the classification algorithm, thus affecting the classification ...

A multiscale information system (MSIS) is a kind of information system that divides data into different scales according to the thickness of different granularities, which solves the limitation of traditional single-scale information systems. In view of ...

With the increase of high-dimensional multilabel data, multilabel feature selection (MFS) has received more and more widespread attention. Embedded feature selection methods have been widely studied due to their high efficiency and low computational cost. ...

This article investigates the dynamic-memory event-triggered (DMET)-based double asynchronous dissipative control issue for Takagi–Sugeno fuzzy semi-Markov jump systems (T-S FSMJSs) under redundant channel strategy. To mitigate the network burden ...

Belief rule base (BRB) has attracted considerable interest due to its interpretability and exceptional modeling accuracy. Generally, BRB construction relies on prior knowledge or historical data. The limitations of knowledge constrain the knowledge-based ...

This article proposes a practical adaptive fuzzy backstepping control (FBC) scheme for the constrained locus tracking problem of a nonlinear cable-driven manipulator. Specifically, fuzzy logic systems aim to approximate unknown nonlinear terms, and the ...

For accomplishing efficiency analysis and resource planning of organizations in various sectors, data envelopment analysis (DEA) has attracted many researchers' interest. Rather than requiring accurate measurement of input and output data, ...