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2020 IEEE International Symposium on Product Compliance engineering-Asia, ISPCE-CN 2020

作者： Yang, Cuili Wu, Zhanhong Han, Honggui Bi, Xiaowen Beijing University of Technology Faculty of Information Technology Beijing China City University of Hong Kong Department of Electrical Engineering Hong Kong Faculty of Information Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligence System Eng. Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China Department of Electrical Engineering City University of Hong Kong. Hong Kong

ISBN: (纸本)9781665414616

During the recycling process of used electrical and electronic products from recycling places to sorting center, the vehicle path planning is an urgent problem to be solved which needs to minimize the number of vehicles and vehicle transportation distance simultaneously. To solve this problem, a multi-objective optimization algorithm is proposed which combines the genetic algorithm (GA) and multi-objective evolutionary algorithm based on decomposition (MOEA/D). Firstly, the vehicle path planning model of the sorting center is established according to characteristics of product transportation process. Secondly, the GA is used to produce some vehicle path planning schemes. Then, the MOEA/D is introduced to deal with the trade-off relationship between two objectives. Simulation results demonstrate that the proposed algorithm is able to generate a set of non-dominated solutions. © 2020 IEEE.

关键词： Genetic algorithms

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Joint Association, Beamforming, and Resource Allocation for Multi-IRS Enabled MU-MISO Systems With RSMA

arXiv

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arXiv 2024年

作者： Wang, Chunjie Zhang, Xuhui Xing, Huijun Xue, Liang Wang, Shuqiang Shen, Yanyan Yang, Bo Guan, Xinping Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China School of Information and Electrical Engineering Hebei University of Engineering Handan056038 China Hebei Key Laboratory of Security and Protection Information Sensing and Processing Handan056038 China Shenzhen Future Network of Intelligence Institute The School of Science and Engineering The Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Shenzhen Future Network of Intelligence Institute The Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China Department of Automation The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

Intelligent reflecting surface (IRS) and rate-splitting multiple access (RSMA) technologies are at the forefront of enhancing spectrum and energy efficiency in the next generation multi-antenna communication systems. This paper explores a RSMA system with multiple IRSs, and proposes two purpose-driven scheduling schemes, i.e., the exhaustive IRS-aided (EIA) and opportunistic IRS-aided (OIA) schemes. The aim is to optimize the system weighted energy efficiency (EE) under the above two schemes, respectively. Specifically, the Dinkelbach, branch and bound, successive convex approximation, and the semidefinite relaxation methods are exploited within the alternating optimization framework to obtain effective solutions to the considered problems. The numerical findings indicate that the EIA scheme exhibits better performance compared to the OIA scheme in diverse scenarios when considering the weighted EE, and the proposed algorithm demonstrates superior performance in comparison to the baseline algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Beamforming

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Utility coupling promotes cooperation in multiplayer snowdrift games on interdependent simplicial networks

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The European Physical Journal Special Topics 2023年第4期233卷 831-842页

作者： Wang, Juan Guo, Shiqiang Xia, Chengyi Perc, Matjaž Tianjin Key Laboratory for Control Theory and Complicated Industry Systems Tianjin University of Technology Tianjin People’s Republic of China School of Electrical Engineering and Automation Tianjin University of Technology Tianjin People’s Republic of China School of Artificial Intelligence Tiangong University Tianjin People’s Republic of China Faculty of Natural Sciences and Mathematics University of Maribor Maribor Slovenia Alma Mater Europaea Maribor Slovenia Complexity Science Hub Vienna Vienna Austria Department of Physics Kyung Hee University Seoul Republic of Korea

Real-world social networks often contain not only one-to-one pairwise interactions, but also multi-person group interactions involving more than two individuals. To reveal the important role of such group interactions (i.e., higher order topology) for the evolution of cooperation, we here use interdependent simplicial network topologies, where the evolutionary interactions, governed by the snowdrift game, are thus explored beyond pairwise links. We also consider utility coupling between two network layers in an uncorrelated interdependence. Systematic Monte Carlo simulations lead us to two main conclusions. First, we find that the level of cooperation can be elevated by increasing the utility coupling value. And second, cooperation tends to decline when we increase the number of 2-simplex interactions. However, despite the later result, the overall cooperation level on both interdependent networks is still higher than that on any isolated network. We hope that these results will inspire future research on cooperation among unrelated individuals in higher order networks.

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An IGD+ Performance Indicator Based Particle Swarm Optimizer For Multi-objective Optimization

An IGD+ Performance Indicator Based Particle Swarm Optimizer...

引用

第33届中国控制与决策会议

作者： Fei Li Shijian Dong Yuanqu Liu Zhengkun Shang School of Electrical and Information Engineering Anhui Unviersity of Technology AnHui Province Key Laboratory of Special Heavy Load Robot Anhui Unviersity of Technology Ma'anshan University School of Information and Control Engineering China University of Mining and Technology Department of Automation North China Electric Power University

Particle swarm optimizer（PSO） is suitable for solving multi-objective optimization problems（MOPs）.However,there are two main issues for any multi-objective particle swarm optimizers（MOPSOs）.The first issue is how to balance the convergence and *** second issue is how to enhance the exploitation and exploration during the evolutionary *** order to address these issues,an modified inverted generational distance（IGD） performance indicator based PSO（IGD-MOPSO） is *** external archive updating strategies based on the IGD indicator and the objective space decomposition method are proposed to select the evenly distributed non-dominated *** leader updated strategy of each particle is based on the IGD indicator value which is associated to the corresponding reference *** genetic operator is embedded into the evolutionary procedure to reset the position in order to help the particle jump out of the local *** have conducted the simulation on some related benchmark test *** experimental results have indicated that the proposed algorithm is competitive with some related algorithms.

关键词： IGD+ indicator Particle swarm optimization The external archive updated strategy Objective space decomposition Multi-objective optimization problems

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Implementation of a Robust Electric Brake Actuator Design Based on H-infinity control Theory

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Periodica Polytechnica Transportation engineering 2019年第3期47卷 178-185页

作者： Péter, Gábor Max, György Kiss, Bálint Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics P.O.B. 91 BudapestH-1521 Hungary

This paper deals with the robust control system design and implementation of a brake actuator for a smart car. To deliver robust performance, an H∞ controller had been chosen for the task. This allows excellent disturbance rejection while requiring low computational needs. In order to realize the controller a nominal model of the system has been identified, then, the parameter uncertainties were taken into account to find the stabilizing controller. The brake system consists of a low level H∞ controller sustaining robustness, a mid-level serial compensator for effective setpoint tracking and a high level supervisory control logic to deliver a reliable system. The implementation was tested and verified on a test bench using rapid prototyping tools and HIL methods. © 2019 Budapest University of technology and Economics. All rights reserved.

关键词： Robust control

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Compressed Gradient Tracking Algorithms for Distributed Nonconvex Optimization

arXiv

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arXiv 2023年

作者： Xu, Lei Yi, Xinlei Wen, Guanghui Shi, Yang Johansson, Karl H. Yang, Tao The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China The Lab for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Systems Science School of Mathematics Southeast University Nanjing210096 China The Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

In this paper, we study the distributed nonconvex optimization problem, aiming to minimize the average value of the local nonconvex cost functions using local information exchange. To reduce the communication overhead, we introduce three general classes of compressors, i.e., compressors with bounded relative compression error, compressors with globally bounded absolute compression error, and compressors with locally bounded absolute compression error. By integrating them, respectively, with the distributed gradient tracking algorithm, we then propose three corresponding compressed distributed nonconvex optimization algorithms. Motivated by the state-of-the-art BEER algorithm proposed in [1], which is an efficient compressed algorithm integrating gradient tracking with biased and contractive compressors, our first proposed algorithm extends this algorithm to accommodate both biased and non-contractive compressors. For each algorithm, we design a novel Lyapunov function to demonstrate its sublinear convergence to a stationary point if the local cost functions are smooth. Furthermore, when the global cost function satisfies the Polyak–Lojasiewicz (P–L) condition, we show that our proposed algorithms linearly converge to a global optimal point. It is worth noting that, for compressors with bounded relative compression error and globally bounded absolute compression error, our proposed algorithms’ parameters do not require prior knowledge of the P–L constant. The theoretical results are illustrated by numerical examples, demonstrating the effectiveness of the proposed algorithms in significantly reducing the communication burden while maintaining the convergence performance. Moreover, simulation results show that the proposed algorithms outperform the state-of-the-art compressed distributed nonconvex optimization algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Cost functions

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Improved Classification of Benign and Malignant Breast Lesions Based on Contrast Manipulation and Gradient Map

Improved Classification of Benign and Malignant Breast Lesio...

引用

E-Health and Bioengineering Conference (EHB)

作者： Iulia–Nela Anghelache Nastase Simona Moldovanu Luminita Moraru The Modelling & Simulation Laboratory University Dunarea de Jos of Galati UGAL Galati Romania Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics University Dunarea de Jos of Galati UGAL Galati Romania Department of Chemistry Physics and Environment Faculty of Sciences and Environment University Dunarea de Jos of Galati UGAL Galati Romania

ISBN: (数字)9781665485579

ISBN: (纸本)9781665485586

This study proposes an approach to enhance the contrast breast ultrasound (BUS) images with the preservation of the finer details. The main idea is to use the relevant and most important features in the classification of BUS images as benign or malignant. Among the contrast manipulation techniques, both linear under- and overexposure methods, contrast limiting adaptive histogram equalization (CLAHE) method and homomorphic filtering are used. The gradient maps of original images are generated for further analysis. Also, the gradient maps of original images are improved by the local mean subtraction and divisive normalization. Eight structural features are extracted from each gradient map image type. The extracted features feed a Random Forest (RF) classifier to determine their relevance for BUS images classification. An accuracy of 97.12% has been obtained for improved gradient map images and 93.03% for gradient map images.

关键词： Histograms Ultrasonic imaging Limiting Breast Feature extraction Lesions Standards

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Melanoma Detection using a Random Forest Algorithm

Melanoma Detection using a Random Forest Algorithm

引用

E-Health and Bioengineering Conference (EHB)

作者： Felicia-Anisoara Damian Simona Moldovanu Luminita Moraru The Modelling & Simulation Laboratory University Dunarea de Jos of Galati UGAL Galati Romania Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics University Dunarea de Jos of Galati UGAL Galati Romania Department of Chemistry Physics and Environment Faculty of Sciences and Environment University Dunarea de Jos of Galati UGAL Galati Romania

ISBN: (数字)9781665485579

ISBN: (纸本)9781665485586

In recent years, statistical evidence has identified melanoma as a major cause of skin cancer deaths. In this study, we propose a skin analysis lesions based on colour features (C) and Hu (H) moments to differentiate benign (nevi) and malignant (melanoma) lesions and, a classification based on Random Forest algorithm. Colour features are found as follows. Pre-processing for hair removing using the Dull-razor method; image segmentation based on the optimal colour threshold set on each RGB colour channel (red, green, blue); 23 colour features extraction using the minimum and maximum RGB intensity and Hu moments; Random Forest (RF) algorithm to accurately differentiate benign and malignant skin lesions. This study used three datasets: 7-Point, Med-Node, PH2. RF classifier performance in terms of accuracy was: 94% for the 7-point dataset with H5, H7, H6, H2, C08 selected as relevant features; 98.1% for the Med-Node dataset and H7, H5, H6, H2, H1 ACC the relevant features; and, 96.5% for the PH2 dataset and H5, H6, H7, C03, H1 selected as relevant features, respectively. Shape features based on Hu moments are found to improve the classification performance of the skin lesions compared to the colour features.

关键词： Visualization Image segmentation Image color analysis Shape Melanoma Skin Classification algorithms

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Secure State Estimation against Sparse Attacks on a Time-varying Set of Sensors

arXiv

引用

arXiv 2022年

作者： Li, Zishuo Niazi, Muhammad Umar B. Liu, Changxin Mo, Yilin Johansson, Karl H. Department of Automation Tsinghua University Beijing100084 China Division of Decision and Control Systems Digital Futures School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Laboratory for Information and Decision Systems Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States

This paper studies the problem of secure state estimation of a linear time-invariant (LTI) system with bounded noise in the presence of sparse attacks on an unknown, time-varying set of sensors. In other words, at each time, the attacker has the freedom to choose an arbitrary set of no more that p sensors and manipulate their measurements without restraint. To this end, we propose a secure state estimation scheme and guarantee a bounded estimation error subject to 2p-sparse observability and a mild, technical assumption that the system matrix has no degenerate eigenvalues. The proposed scheme comprises a design of decentralized observer for each sensor based on the local observable subspace decomposition. At each time step, the local estimates of sensors are fused by a median operator to obtain a secure estimation, which is then followed by a local detection-and-resetting process of the decentralized observers. The estimation error is shown to be upper-bounded by a constant which is determined only by the system parameters and noise magnitudes. Moreover, we design the detector threshold to ensure that the benign sensors never trigger the detector. The efficacy of the proposed algorithm is demonstrated by its application on a benchmark example of IEEE 14-bus system. © 2022, CC BY-NC-ND.

关键词： Fault detection

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Swarm intelligent algorithm for re-entrant hybrid flow shop scheduling problems

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International Journal of Simulation and Process Modelling 2019年第1期14卷 17-27页

作者： Han, Zhonghua Tian, Xutian Dong, Xiaoting Xie, Fanyi Faculty of Information and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China Department of Digital Factory Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning China Faculty of Electrical Engineering Sichuan College of Architectural Technology Deyang Sichuan China

In order to solve re-entrant hybrid flowshop (RHFS) scheduling problems and establish simulations and processing models, this paper uses wolf pack algorithm (WPA) as global optimisation. For local assignment, it takes minimum remaining time rule. Scouting behaviours of wolf are changed in former optimisation by means of Levy flight, extending searching ranges and increasing rapidity of convergence. When it comes to local extremum of WPA, dynamic regenerating individuals with high similarity adds diversity. Hamming distance is used to judge individual similarity for increased quality of individuals, enhanced search performance of the algorithm in solution space and promoted evolutionary vitality. A painting workshop in a bus manufacture enterprise owns typical features of re-entrant hybrid flowshop. Regarding it as the algorithm applied target, this paper focuses on resolving this problem with dynamic wolf pack algorithm based on levy flight (LDWPA). Results show that LDWPA can solve re-entrant hybrid flowshop scheduling problems effectively. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Hamming distance

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