Article
Mathematics
Zhiyong Xiao, Zengtai Gong
Summary: This article proposes scalar multiplication and addition operations of complex numbers and fuzzy complex numbers based on a new representation, and introduces a new method for solving FCLS. By converting FCLS into complex and real linear systems, solutions for FCLS can be obtained, and FCLS based on RFCN as a special case are investigated.
Article
Mathematics, Applied
Talha Midrar, Saifullah Khan, Saleem Abdullah, Thongchai Botmart
Summary: Due to the vagueness and uncertainty in human cognition and judgments, existing fuzzy decision-making approaches lack credibility measures for fuzzy assessment values. This research proposes new procedures for credible fuzzy numbers based on Dombi t-norm and Dombi t-conorm, and develops a series of fuzzy credibility Dombi aggregation operators.
Article
Computer Science, Theory & Methods
Zengtai Gong, Zhiyong Xiao
Summary: This paper proposes a new representation of fuzzy complex numbers, investigates arithmetic operations, establishes calculus theory of fuzzy complex valued functions, defines concepts of strong sum and strong difference, and examines the necessary and sufficient conditions of the analyticity of fuzzy complex-valued functions. Furthermore, it discusses the integral of fuzzy complex-valued functions and Cauchy integral theorem.
FUZZY SETS AND SYSTEMS
(2021)
Article
Mathematics
Niccolo Cao, Antonio Calcagni
Summary: This article presents a method for jointly analyzing ratings and response times using fuzzy numbers, and validates it through a real case study. The results indicate that using fuzzy numbers provides more reliable and parsimonious data analysis methods, addressing statistical issues that may occur with standard data analysis procedures.
Article
Computer Science, Theory & Methods
Sayedabbas Sobhi, Scott Dick
Summary: Complex fuzzy sets are an extension of type-1 fuzzy sets with complex-valued membership functions. Time-series forecasting using complex fuzzy sets has become an important application, with neuro-fuzzy systems shown to be accurate and compact. However, there has been no systematic investigation comparing sinusoidal and complex Gaussian membership functions within a common architecture.
FUZZY SETS AND SYSTEMS
(2023)
Article
Mathematics
Krzysztof Piasecki, Anna Lyczkowska-Hanckowiak
Summary: The study found formal differences between oriented fuzzy numbers and fuzzy numbers in algebraic structures, showing they are not isomorphic models. Oriented fuzzy numbers were shown to be more useful than fuzzy numbers for portfolio analysis, indicating their utility in modeling real-world problems.
Article
Computer Science, Artificial Intelligence
Heng Xia, Jian Tang, Wen Yu, Canlin Cui, Junfei Qiao
Summary: This article presents the Takagi-Sugeno (T-S) fuzzy regression tree (TSFRT) method, which applies fuzzy decision trees to regression tasks and proposes multiple strategies to optimize its performance. The experiments demonstrate that the proposed method performs exceptionally well on complex industrial modeling problems.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Nicolas Zumelzu, Benjamin Bedregal, Edmundo Mansilla, Humberto Bustince, Roberto Diaz
Summary: This article introduces the concept of admissible order for fuzzy numbers and proposes a method to construct admissible orders. With this method, the path costs in fuzzy weighted graphs can be ranked.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Mathematics, Applied
M. Khalili, R. A. Borzooei, M. Deldar
Summary: This study aims to introduce new methods to achieve optimal matching in fuzzy graphs and classify the fuzzy sizes of the edges and vertices of a matching, called matching numbers. Matching numbers are not only a direct tool in improving existing matching optimization algorithms, but can also be used to build optimization algorithms based on the vertices of a matching. Introducing the properties of matching numbers is useful in constructing and solving edge-fuzzy and vertex-fuzzy maximization problems.
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Zengtai Gong, Zhiyong Xiao
Summary: This paper proposes a method for approximating fuzzy complex numbers using special fuzzy numbers, and discusses the concept of prismoid fuzzy complex numbers and the nearest prismoid fuzzy complex number with respect to the centroid and weighted pseudometric.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Shahzad Noor Abbasi, Shahzaib Ashraf, M. Shazib Hameed, Sayed M. Eldin
Summary: The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while taking into account unpredictability and reliability in decision-making. The research introduces the concept of PFZN, a graded structure that combines Pythagorean fuzzy sets and ZN to deal with uncertainty in decision-aid problems. The proposed methodology of PFZN is more precise and effective in real-life problems compared to other existing methodologies.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Computer Science, Theory & Methods
Xiaozi Liu, Dongming Liu, Guanghao Jiang
Summary: As two special types of n-dimensional fuzzy numbers, fuzzy n-cell numbers and fuzzy n-ellipsoid numbers are important in representing imprecise multichannel digital information. This paper studies the topological structures of the sets L(Rn) and E(Rn) under the topology induced by the supremum metric Doo. The main result shows that (L(Rn), Doo) and (E(Rn), Doo) are homeomorphic to the Hilbert space 2(c) pound and do not have the fixed point property.
FUZZY SETS AND SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Zhen Ming Ma, Wei Yang, Lingqiang Li, Zeshui Xu
Summary: In this paper, a novel method for ranking fuzzy numbers based on additively consistent fuzzy preference relations (ACFPR) is proposed. The additive priority degree (APD) is introduced to capture pair-wise comparisons of fuzzy numbers, and it is separable by taking a suitable parameter in the weight function and able to induce an ACFPR. A ranking procedure is developed to compare the given fuzzy numbers with a total order by combining all the point-wise comparisons among different fuzzy numbers with a strictly increasing weight function. Numerical examples show the differences of the proposed method compared to the previous approaches.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Shing-Chung Ngan
Summary: Fuzzy number ranking is an important and fundamental subject in fuzzy set theory. This article proposes a simple framework for ranking fuzzy numbers that allows users to configure their own ranking operator. The framework is demonstrated to be concrete, user-configurable, and user-explainable in various examples. It also has potential applications beyond fuzzy ranking, making it a fundamental framework in fuzzy set theory.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Yuanyuan Liu, Yunwen Miao, Athanasios A. Pantelous, Jian Zhou, Ping Ji
Summary: This article introduces two innovative techniques for approximating the expected values of fuzzy numbers' monotone functions based on existing fuzzy simulation algorithms. Through numerical experiments, the superiority of these two novel techniques over others in terms of accuracy, stability, and efficiency is prominently displayed.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Jing Yang, Changjing Shang, Ying Li, Fangyi Li, Liang Shen, Qiang Shen
Summary: This article introduces a new ANFIS learning approach that uses an evolutionary process and interpolation to generate high-performing ANFIS models in cases of data shortage.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Ming Yang, Hongguang Ma, Xiang Li, Changjing Shang, Qiang Shen
Summary: This article studies the bus bridging problem in public transportation systems, where passenger demand is represented as parametric interval-valued fuzzy variables and their associated uncertainty distribution sets. A distributionally robust fuzzy optimization model is proposed to minimize the maximum travel time and find the optimal scheme for vehicle allocation, route selection, and frequency determination. The proposed approach is verified using real-world uncertain parameters and validated to provide a better uncertainty-immunized solution.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Li -Jiang Li, Sheng-Lin Zhou, Fei Chao, Xiang Chang, Longzhi Yang, Xiao Yu, Changjing Shang, Qiang Shen
Summary: This paper presents a network compression method using knowledge distillation technology to develop concise neural network-based controllers that strike a balance between control performance and computational costs. The method involves training a full-size teacher model, pruning it to obtain a compact network, and then further training the compact network as a student model using knowledge distillation. Experimental results demonstrate that the student models with fewer neurons achieve similar performance to the teacher models for intelligent dynamic control but with faster convergence speed.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Jing Yang, Chanyue Wu, Tengfei You, Dong Wang, Ying Li, Changjing Shang, Qiang Shen
Summary: In this study, a new dual pyramid model is proposed for hyperspectral image super resolution. It utilizes a novel hierarchical spatial and spectral fusion method to progressively estimate the high resolution image. Qualitative and quantitative evaluations demonstrate its outstanding performance over large scale factors compared to other spatio-spectral fusion based super resolution techniques.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xiaowei Gu, Miqing Li, Liang Shen, Guolin Tang, Qiang Ni, Taoxin Peng, Qiang Shen
Summary: Zero-order intelligent systems have shown strong performance in data stream classification with high model transparency. However, the lack of optimality in identified prototypes hinders the classification performance. To address this, a novel multiobjective optimization approach is proposed in this article, combining training error minimization and intracluster variance minimization. Experimental studies demonstrate the effectiveness of the approach in improving the classification performance of zero-order intelligent systems.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Mou Zhou, Changjing Shang, Guobin Li, Liang Shen, Nitin Naik, Shangzhu Jin, Jun Peng, Qiang Shen
Summary: Fuzzy rule interpolation (FRI) is enhanced by using a novel transformation-based approach that utilizes the Mahalanobis distance metric for rule selection. By transforming the rule base into a coordinate system, instances of the same category are brought closer and instances of different categories are moved further apart. This allows for more accurate selection of neighboring rules for interpolation when a new observation matches no rules.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Jiagang Liu, Ju Ren, Yongmin Zhang, Xuhong Peng, Yaoxue Zhang, Yuanyuan Yang
Summary: In this paper, a dependent task offloading framework (COFE) is proposed, which allows mobile devices to offload compute-intensive tasks with dependent constraints to the MEC-Cloud system to improve user experience. The task offloading problem is formulated as an average makespan minimization problem, and a heuristic ranking-based algorithm is proposed to assign the offloaded tasks. Theoretical analysis proves the stability of the system under the proposed algorithm, and extensive simulations validate its effectiveness in reducing average makespan and deadline violation probabilities.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Xuan Hou, Yunpeng Bai, Yefan Xie, Huibin Ge, Ying Li, Changjing Shang, Qiang Shen
Summary: Deep learning has shown great potential in SAR imagery change detection, but it requires a large amount of labeled samples, which is a tedious and time-consuming task. In addition, sample imbalance is a challenge for existing change detection techniques. To address these problems, a Deep Collaborative semi-supervised learning Framework with Class-Rebalancing (DCF-CRe) is proposed for SAR imagery change detection, by using Convolutional Neural Network (CNN) and deep clustering.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Automation & Control Systems
Jialin Liu, Fei Chao, Longzhi Yang, Chih-Min Lin, Changjing Shang, Qiang Shen
Summary: This article presents a novel metalearning method that controls the gradient descent process in a neural network by limiting the model parameters in a low-dimensional latent space. It also introduces an alternative design of the decoder with shared weights to reduce the number of parameters. Experimental results show that the proposed approach outperforms the state of the art in classification tasks.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Artificial Intelligence
Guanli Yue, Yanpeng Qu, Longzhi Yang, Changjing Shang, Ansheng Deng, Fei Chao, Qiang Shen
Summary: Fuzzy clustering is a method that uses partial memberships to decompose data into clusters, and it demonstrates comparable performance in knowledge exploitation when dealing with incomplete information. This article proposes a new fuzzy-rough intrigued harmonic discrepancy clustering (HDC) algorithm that effectively handles complex data distribution and improves clustering performance.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Dong Wang, Chanyue Wu, Yunpeng Bai, Ying Li, Changjing Shang, Qiang Shen
Summary: This paper proposes a multitask network (MTNet) to achieve joint multispectral (MS) pansharpening for images acquired by different satellites. The MTNet shares generic knowledge between datasets via a task-agnostic subnetwork (TASNet) and adapts this knowledge to specific satellites using task-specific subnetworks (TSSNets). It also introduces band-aware dynamic convolutions (BDConvs) to accommodate various ground scenes and bands. Experimental results demonstrate that the proposed approach outperforms existing state-of-the-art (SOTA) techniques across different datasets.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Mizi Han, Yanpeng Qu, Neil MacParthalain, Changjing Shang, Zihan Yao, Qiang Shen
Summary: Three-valued reasoning or three-way decision modelling theory (3WD) is a natural and intuitive approach to handling uncertainty. This paper proposes a linear reconstruction neighbourhood membership and representation-based decision-theoretic rough set (RDTRS) approach to improve 3WD classification models. The experimental results demonstrate improved classification performance for both benchmark and face image datasets.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Mou Zhou, Changjing Shang, Qiang Shen
Summary: Fuzzy rule interpolation empowers fuzzy rule-based systems to infer even with sparse rule bases. This article introduces a groundbreaking rule-ranking-based method, RT-FRI, which streamlines the rule selection procedure by using ranking scores produced through aggregation functions. Experimental results show that RT-FRI is highly efficient and accurate.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Artificial Intelligence
Qingping Zheng, Ling Zheng, Jiankang Deng, Ying Li, Changjing Shang, Qiang Shen
Summary: In this paper, a Transformer-based Hierarchical Dynamic Decoder (T-HDDNet) is proposed for salient object detection. The method utilizes a self-attention mechanism to extract features and has a powerful capability of learning global cues. With a dynamic dual upsampling mechanism and a dynamic feature fusion unit, it achieves accurate saliency maps of high resolution in a data-driven manner.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Automation & Control Systems
Ruiqi Wu, Fei Chao, Changle Zhou, Xiang Chang, Longzhi Yang, Changjing Shang, Zihao Zhang, Qiang Shen
Summary: This article proposes a robotic writing framework based on a robotic hand-eye coordination method. By constructing a vision-motor network and a motor-vision network, the proposed method successfully writes strokes of Chinese characters. The underlying research of this method can be applied to other areas, such as human-robot motion mimicking.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
