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Table of contents IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-02-17
Presents the table of contents for this issue of the publication.
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-02-17
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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TechRxiv: Share Your Preprint Research with the World! IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-02-17
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-02-17
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-02-17
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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Table of contents IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-01-15
Presents the table of contents for this issue of the publication.
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-01-15
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Member Get-A-Member (MGM) Program IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-01-15
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Introducing IEEE Collabratec IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-01-15
Presents the table of contents for this issue of the publication.
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TechRxiv: Share Your Preprint Research with the World! IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-01-15
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-01-15
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2021-01-15
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Table of contents IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-12-22
Presents the table of contents for this issue of the publication.
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-12-22
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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TechRxiv: Share Your Preprint Research with the World! IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-12-22
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-12-22
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-12-22
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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Table of contents IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23
Presents the table of contents for this issue of the publication.
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23
"Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication."
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TechRxiv: Share Your Preprint Research with the World! IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23
"Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers."
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23
"Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication."
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IEEE Transactions on Cybernetics IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23
"Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication."
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Model-Based Event-Triggered Sliding-Mode Control for Multi-Input Systems: Performance Analysis and Optimization. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23 Jun Song,Daniel W C Ho,Yugang Niu
This article is concerned with the model-based event-triggered sliding-mode control (SMC) issue for multi-input systems, which is motivated by some existing results in a single-input case. A model-based event-triggered SMC scheme is first designed. In particular, a triggered condition is co-designed with SMC to achieve the reachability condition of a specified sliding surface. Thus, it can effectively
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Communication and Interaction With Semiautonomous Ground Vehicles by Force Control Steering. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23 Miguel Martinez-Garcia,Roy S Kalawsky,Timothy Gordon,Tim Smith,Qinggang Meng,Frank Flemisch
While full automation of road vehicles remains a future goal, shared-control and semiautonomous driving--involving transitions of control between the human and the machine--are more feasible objectives in the near term. These alternative driving modes will benefit from new research toward novel steering control devices, more suitably where machine intelligence only partially controls the vehicle. In
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Fixed-Time Fuzzy Control for a Class of Nonlinear Systems. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23 Yumei Sun,Fang Wang,Zhi Liu,Yun Zhang,C L Philip Chen
Fixed-time tracking control is considered for a class of nonlinear systems in this article. Different from the conventional literature on fixed-time control studies, in this article, the nonlinearities of systems are all completely unknown. Fuzzy-logic systems are utilized to model these unknown nonlinearities. To deal with the fixed-time control under the approximation errors, three steps are taken
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Early Screening of Autism in Toddlers via Response-To-Instructions Protocol. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23 Jingjing Liu,Zhiyong Wang,Kai Xu,Bin Ji,Gongyue Zhang,Yi Wang,Jingxin Deng,Qiong Xu,Xiu Xu,Honghai Liu
Early screening of autism spectrum disorder (ASD) is crucial since early intervention evidently confirms significant improvement of functional social behavior in toddlers. This article attempts to bootstrap the response-to-instructions (RTIs) protocol with vision-based solutions in order to assist professional clinicians with an automatic autism diagnosis. The correlation between detected objects and
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Two-Level LSTM for Sentiment Analysis With Lexicon Embedding and Polar Flipping. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23 Ou Wu,Tao Yang,Mengyang Li,Ming Li
Sentiment analysis is a key component in various text mining applications. Numerous sentiment classification techniques, including conventional and deep-learning-based methods, have been proposed in the literature. In most existing methods, a high-quality training set is assumed to be given. Nevertheless, constructing a high-quality training set that consists of highly accurate labels is challenging
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A Multiobjective Evolutionary Algorithm Based on Objective-Space Localization Selection. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-23 Yuren Zhou,Zefeng Chen,Zhengxin Huang,Yi Xiang
This article proposes a simple yet effective multiobjective evolutionary algorithm (EA) for dealing with problems with irregular Pareto front. The proposed algorithm does not need to deal with the issues of predefining weight vectors and calculating indicators in the search process. It is mainly based on the thought of adaptively selecting multiple promising search directions according to crowdedness
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Individual-Based Transfer Learning for Dynamic Multiobjective Optimization. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-18 Min Jiang,Zhenzhong Wang,Shihui Guo,Xing Gao,Kay Chen Tan
Dynamic multiobjective optimization problems (DMOPs) are characterized by optimization functions that change over time in varying environments. The DMOP is challenging because it requires the varying Pareto-optimal sets (POSs) to be tracked quickly and accurately during the optimization process. In recent years, transfer learning has been proven to be one of the effective means to solve dynamic multiobjective
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A Deep-Ensemble-Level-Based Interpretable Takagi-Sugeno-Kang Fuzzy Classifier for Imbalanced Data. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-18 Guanjin Wang,Ta Zhou,Kup-Sze Choi,Jie Lu
Existing research reveals that the misclassification rate for imbalanced data depends heavily on the problematic areas due to the existence of small disjoints, class overlap, borderline, and rare data samples. In this study, by stacking zero-order Takagi-Sugeno-Kang (TSK) fuzzy subclassifiers on the minority class and its problematic areas in the deep ensemble, a novel deep-ensemble-level-based TSK
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Advanced Energy Kernel-Based Feature Extraction Scheme for Improved EMG-PR-Based Prosthesis Control Against Force Variation. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-18 Sidharth Pancholi,Amit M Joshi
The EMG signal is a widely focused, clinically viable, and reliable source for controlling bionics and prosthesis devices with the aid of machine-learning algorithms. The decisive step in the EMG pattern recognition (EMG-PR)-based control scheme is to extract the features with minimum neural information loss. This article proposes a novel feature extraction method based on advanced energy kernel-based
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Line Integral Approach to Extended Dissipative Filtering for Interval Type-2 Fuzzy Systems. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-18 Yingying Han,Shaosheng Zhou
This article is concerned with the problems of extended dissipativity analysis and filter design for interval type-2 (IT2) fuzzy systems. Based on the line integral Lyapunov function, a sufficient condition of asymptotic stability and extended dissipativity of the systems under consideration is established. A LMI-based equivalent condition to the obtained one in a nonlinear form is provided by combining
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Data-Driven Discovery of Block-Oriented Nonlinear Models Using Sparse Null-Subspace Methods. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-18 Junlin Li,Xiuting Li,Hai-Tao Zhang,Guanrong Chen,Ye Yuan
This article develops an identification algorithm for nonlinear systems. Specifically, the nonlinear system identification problem is formulated as a sparse recovery problem of a homogeneous variant searching for the sparsest vector in the null subspace. An augmented Lagrangian function is utilized to relax the nonconvex optimization. Thereafter, an algorithm based on the alternating direction method
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Event-Triggered Finite-Time Consensus of Second-Order Leader-Follower Multiagent Systems With Uncertain Disturbances. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-18 Huijin Fan,Kanghua Zheng,Lei Liu,Bo Wang,Wei Wang
In this article, for second-order multiagent systems with uncertain disturbances, the finite-time leader-follower consensus problem has been investigated. First, by considering that the leader's states are only available to part of the followers, a distributed estimator is constructed to estimate the state tracking errors between the leader and each follower. Then, an estimator-based control scheme
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V-Fuzz: Vulnerability Prediction-Assisted Evolutionary Fuzzing for Binary Programs. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-18 Yuwei Li,Shouling Ji,Chenyang Lyu,Yuan Chen,Jianhai Chen,Qinchen Gu,Chunming Wu,Raheem Beyah
Fuzzing is a technique of finding bugs by executing a target program recurrently with a large number of abnormal inputs. Most of the coverage-based fuzzers consider all parts of a program equally and pay too much attention to how to improve the code coverage. It is inefficient as the vulnerable code only takes a tiny fraction of the entire code. In this article, we design and implement an evolutionary
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Learning Latent Representation for IoT Anomaly Detection. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-18 Ly Vu,Van Loi Cao,Quang Uy Nguyen,Diep N Nguyen,Dinh Thai Hoang,Eryk Dutkiewicz
Internet of Things (IoT) has emerged as a cutting-edge technology that is changing human life. The rapid and widespread applications of IoT, however, make cyberspace more vulnerable, especially to IoT-based attacks in which IoT devices are used to launch attack on cyber-physical systems. Given a massive number of IoT devices (in order of billions), detecting and preventing these IoT-based attacks are
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A Reference Vector-Based Simplified Covariance Matrix Adaptation Evolution Strategy for Constrained Global Optimization. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-16 Abhishek Kumar,Swagatam Das,Rammohan Mallipeddi
During the last two decades, the notion of multiobjective optimization (MOO) has been successfully adopted to solve the nonconvex constrained optimization problems (COPs) in their most general forms. However, such works mainly utilized the Pareto dominance-based MOO framework while the other successful MOO frameworks, such as the reference vector (RV) and the decomposition-based ones, have not drawn
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Regularized Matrix Factorization for Multilabel Learning With Missing Labels. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-16 Lei Feng,Jun Huang,Senlin Shu,Bo An
This article tackles the problem of multilabel learning with missing labels. For this problem, it is widely accepted that label correlations can be used to recover the ground-truth label matrix. Most of the existing approaches impose the low-rank assumption on the observed label matrix to exploit label correlations by decomposing it into two matrices, which describe the latent factors of instances
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Distributed Maximum Correntropy Filtering for Stochastic Nonlinear Systems Under Deception Attacks. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-16 Haifang Song,Derui Ding,Hongli Dong,Qing-Long Han
This article focuses on the distributed maximum correntropy filtering issue for general stochastic nonlinear systems subject to deception attacks. The considered nonlinear functions consist of a determined one and a stochastic one, and the stochastic signals sent by deception attacks with identified statistic characteristics could be non-Gaussian. The corresponding calculation formulas of both the
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Asymptotic Tracking Control of State-Constrained Nonlinear Systems With Time-Varying Powers. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-16 Ruiming Xie,Chao Guo,Xue-Jun Xie
This article investigates the asymptotic tracking control problem for full-state-constrained nonlinear systems with unknown time-varying powers. By introducing a nonlinear state-dependent transformation, a continuous bounded scalar function, and lower and higher powers into adding a power integrator control design, full-state constraints are skillfully handled without imposing frequently used feasibility
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Spectral-Temporal Receptive Field-Based Descriptors and Hierarchical Cascade Deep Belief Network for Guitar Playing Technique Classification. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-16 Chien-Yao Wang,Pao-Chi Chang,Jian-Jiun Ding,Tzu-Chiang Tai,Andri Santoso,Yu-Ting Liu,Jia-Ching Wang
Music information retrieval is of great interest in audio signal processing. However, relatively little attention has been paid to the playing techniques of musical instruments. This work proposes an automatic system for classifying guitar playing techniques (GPTs). Automatic classification for GPTs is challenging because some playing techniques differ only slightly from others. This work presents
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Fixed-Time Prescribed Tracking Control for Stochastic Nonlinear Systems With Unknown Measurement Sensitivity. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-16 Changchun Hua,Pengju Ning,Kuo Li,Xinping Guan
This article is concerned with the fixed-time prescribed tracking control problem for the uncertain stochastic nonlinear systems subject to input quantization and unknown measurement sensitivity. Different from existing results, the sensitivity on the sensor for measuring the system state is considered as an unknown parameter instead of the known one. Due to unknown measurement sensitivity on the sensor
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Unsupervised Visual-Textual Correlation Learning With Fine-Grained Semantic Alignment. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-15 Yuxin Peng,Zhaoda Ye,Jinwei Qi,Yunkan Zhuo
With the rapid growth of multimedia data on the Internet, there has been a rapid rise in the demand for visual-textual cross-media retrieval between images and sentences. However, the heterogeneous property of visual and textual data brings huge challenges to measure the cross-media similarity for retrieval. Although existing methods have achieved great progress with the strong learning ability of
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Multiobjective Particle Swarm Optimization for Feature Selection With Fuzzy Cost. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-14 Ying Hu,Yong Zhang,Dunwei Gong
Feature selection (FS) is an important data processing technique in the field of machine learning. There have been various FS methods, but all assume that the cost associated with a feature is precise, which restricts their real applications. Focusing on the FS problem with fuzzy cost, a fuzzy multiobjective FS method with particle swarm optimization, called PSOMOFS, is studied in this article. The
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Semisupervised Multiple Choice Learning for Ensemble Classification. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-14 Jian Zhong,Xiangping Zeng,Wenming Cao,Si Wu,Cheng Liu,Zhiwen Yu,Hau-San Wong
Ensemble learning has many successful applications because of its effectiveness in boosting the predictive performance of classification models. In this article, we propose a semisupervised multiple choice learning (SemiMCL) approach to jointly train a network ensemble on partially labeled data. Our model mainly focuses on improving a labeled data assignment among the constituent networks and exploiting
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Second-Order Consensus for Multiagent Systems With Switched Dynamics. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-14 Yifan Liu,Housheng Su,Zhigang Zeng
This article investigates the consensus control problem for second-order multiagent systems with switched dynamics, consisting of a continuous-time subsystem and a discrete-time subsystem. Under a fixed directed topology, two linear control protocols are proposed for achieving consensus. One is that two subsystems use different control inputs, where the continuous-time system uses continuous-time control
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Optimal Adaptive Robust Control Based on Cooperative Game Theory for a Class of Fuzzy Underactuated Mechanical Systems. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-10 Xiaolong Chen,Han Zhao,Hao Sun,Shengchao Zhen,Abdullah Al Mamun
While designing control for a class of underactuated mechanical systems (UMSs), the uncertainty and the prescribed nonholonomic tracking trajectories should be taken into consideration. Uncertainty considered in this article is time varying and bounded, and the bound of uncertainty is described using the fuzzy set theory, namely, fuzzy UMSs. An analytical dynamics-based view is taken in which the prescribed
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A Controlled Strengthened Dominance Relation for Evolutionary Many-Objective Optimization. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-10 Jiangtao Shen,Peng Wang,Xinjing Wang
Maintaining a balance between convergence and diversity is particularly crucial in evolutionary multiobjective optimization. Recently, a novel dominance relation called ``strengthened dominance relation'' (SDR) is proposed, which outperforms the existing dominance relations in balancing convergence and diversity. In this article, two points that influence the performance of SDR are studied and a new
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Navigation of Three Cooperative Object-Transportation Robots Using a Multistage Evolutionary Fuzzy Control Approach. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-10 Chia-Feng Juang,Chia-Hao Lu,Chen-An Huang
This article proposes a new multistage evolutionary fuzzy control configuration and navigation of three-wheeled robots cooperatively carrying an overhead object in unknown environments. Based on the divide-and-conquer technique, this article proposes a stage-by-stage evolutionary obstacle boundary following (OBF) fuzzy control of each of the three robots through multiobjective continuous ant colony
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Continuous Support Vector Regression for Nonstationary Streaming Data. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-10 Hang Yu,Jie Lu,Guangquan Zhang
Quadratic programming is the process of solving a special type of mathematical optimization problem. Recent advances in online solutions for quadratic programming problems (QPPs) have created opportunities to widen the scope of applications for support vector regression (SVR). In this vein, efforts to make SVR compatible with streaming data have been met with substantial success. However, streaming
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Ant Colony Evacuation Planner: An Ant Colony System With Incremental Flow Assignment for Multipath Crowd Evacuation. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-10 Zhi-Min Huang,Wei-Neng Chen,Qing Li,Xiao-Nan Luo,Hua-Qiang Yuan,Jun Zhang
Evacuation path optimization (EPO) is a crucial problem in crowd and disaster management. With the consideration of dynamic evacuee velocity, the EPO problem becomes nondeterministic polynomial-time hard (NP-Hard). Furthermore, since not only one single evacuation path but multiple mutually restricted paths should be found, the crowd evacuation problem becomes even challenging in both solution spatial
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Event-Triggered Distributed State Estimation for Cyber-Physical Systems Under DoS Attacks. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-10 Yan Liu,Guang-Hong Yang
This article investigates the event-triggered distributed state estimation problem for a class of cyber-physical systems (CPSs) with multiple transmission channels under denial-of-service (DoS) attacks. First, an observer-based event-triggered transmission scheme is proposed to improve the transmission efficiency, and the corresponding distributed Kalman filter is designed to estimate the system states
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Hybrid Model-Based Emotion Contextual Recognition for Cognitive Assistance Services. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-10 N Ayari,H Abdelkawy,A Chibani,Y Amirat
Endowing ubiquitous robots with cognitive capabilities for recognizing emotions, sentiments, affects, and moods of humans in their context is an important challenge, which requires sophisticated and novel approaches of emotion recognition. Most studies explore data-driven pattern recognition techniques that are generally highly dependent on learning data and insufficiently effective for emotion contextual
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Inter-Algorithm Multiobjective Cooperation for Phylogenetic Reconstruction on Amino Acid Data. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-10 Sergio Santander-Jimenez,Miguel A Vega-Rodriguez,Leonel Sousa
Inter-algorithm cooperative approaches are increasingly gaining interest as a way to boost the search capabilities of evolutionary algorithms (EAs). However, the growing complexity of real-world optimization problems demands new cooperative designs that implement performance-driven strategies to improve the solution quality. This article explores multiobjective cooperation to address an important problem
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Predicting Network Controllability Robustness: A Convolutional Neural Network Approach. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-09 Yang Lou,Yaodong He,Lin Wang,Guanrong Chen
Network controllability measures how well a networked system can be controlled to a target state, and its robustness reflects how well the system can maintain the controllability against malicious attacks by means of node removals or edge removals. The measure of network controllability is quantified by the number of external control inputs needed to recover or to retain the controllability after the
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Stabilization of Perturbed Continuous-Time Systems Using Event-Triggered Model Predictive Control. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-07 Mengzhi Wang,Jian Sun,Jie Chen
In this article, event-triggered model predictive control (EMPC) of continuous-time nonlinear systems with bounded disturbances is studied. Two novel event-triggered control schemes are proposed. In the first strategy, an event-triggering condition, designed based on the state error between the actual system state and the optimal one, with an absolute threshold is considered. In the second strategy
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Large-Scale Traffic Signal Control Using a Novel Multiagent Reinforcement Learning. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-03 Xiaoqiang Wang,Liangjun Ke,Zhimin Qiao,Xinghua Chai
Finding the optimal signal timing strategy is a difficult task for the problem of large-scale traffic signal control (TSC). Multiagent reinforcement learning (MARL) is a promising method to solve this problem. However, there is still room for improvement in extending to large-scale problems and modeling the behaviors of other agents for each individual agent. In this article, a new MARL, called cooperative
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A New Evidential Reasoning Rule-Based Safety Assessment Method With Sensor Reliability for Complex Systems. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-03 Shuai-Wen Tang,Zhi-Jie Zhou,Chang-Hua Hu,Fu-Jun Zhao,You Cao
In current studies of safety assessment for complex systems with the evidential reasoning (ER) rule, the evidence reliability is generally given by experts, which makes the observation data by sensors ignored. However, sensors are inevitably affected by such various uncertainties as perturbations in engineering practice, which can reduce their quality and tracking ability. As such, the observation
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Guarding a Subspace in High-Dimensional Space With Two Defenders and One Attacker. IEEE Trans. Cybern. (IF 11.079) Pub Date : 2020-09-03 Rui Yan,Zongying Shi,Yisheng Zhong
This article considers a subspace guarding game in high-dimensional space which consists of a play subspace and a target subspace. Two faster defenders as a team cooperate to protect the target subspace by capturing an attacker which strives to enter the target subspace from the play subspace without being captured. A closed-form solution is provided from the perspectives of kind and degree. Contributions
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