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Congress on Evolutionary Computation

作者： Changwu Huang Yuanxiang Li Xin Yao Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation University Key Laboratory of Evolving Intelligent Systems of Guangdong Province Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9781728169293

ISBN: (纸本)9781728169309

The Capacitated Arc Routing Problem (CARP) is a general and challenging arc routing problem. As the problem size increasing, exact methods are not applicable, and heuristic and meta-heuristic algorithms are promising approaches to solve it. To obtain good performance, parameter values of heuristics or meta-heuristics should be properly set. In recent years, automatic parameter tuning, which includes off-line and online parameter tuning, has attracted considerable attention in the evolutionary computation community. At present, parameters are usually determined through simple off-line parameter tuning, such as empirical analysis or grid search, when designing algorithms for CARP. However, using off-line parameter tuning on CARP has some disadvantages, among which the computational cost is the serious one. This work proposed an online parameter tuning approach using exponential recency-weighted kernel density estimation (ERW-KDE), and combines it with the SAHiD algorithm, which is an hierarchical decomposition based algorithm for CARP, to constitute the online parameter tuned SAHiD (OPT-SAHiD) algorithm. The experimental results show that OPT-SAHiD significantly outperforms the compared algorithms on two CARP benchmark sets owing to the proposed online automatic parameter tuning approach. The proposed online automatic parameter tuning approach based on ERW-KDE not only improves the performance of SAHiD algorithm, but also removes the additional computational overhead required for offline parameter tuning.

关键词： Tuning Task analysis Heuristic algorithms Kernel Routing Estimation Probability density function

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Towards explainable multi-party learning: A contrastive knowledge sharing framework

arXiv

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arXiv 2021年

作者： Gao, Yuan Li, Jiawei Gong, Maoguo Xie, Yu Qin, A.K. The School of Electronic Engineering Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education Xidian University Shaanxi Province Xi'an710071 China The Key Laboratory of Computational Intelligence Chinese Information Processing Ministry of Education Shanxi University Taiyuan030006 China The department of Computer Science and Software Engineering Swinburne University of Technology Melbourne Australia

Multi-party learning provides solutions for training joint models with decentralized data under legal and practical constraints. However, traditional multi-party learning approaches are confronted with obstacles such as system heterogeneity, statistical heterogeneity, and incentive design. How to deal with these challenges and further improve the efficiency and performance of multi-party learning has become an urgent problem to be solved. In this paper, we propose a novel contrastive multi-party learning framework for knowledge refinement and sharing with an accountable incentive mechanism. Since the existing parameter averaging method is contradictory to the learning paradigm of neural networks, we simulate the process of human cognition and communication, and analogize multiparty learning as a many-to-one knowledge sharing problem. The approach is capable of integrating the acquired explicit knowledge of each client in a transparent manner without privacy disclosure, and it reduces the dependence on data distribution and communication environments. The proposed scheme achieves significant improvement in model performance in a variety of scenarios, as we demonstrated through experiments on several real-world datasets. Copyright © 2021, The Authors. All rights reserved.

关键词： Knowledge management

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A DC-Ka-Band 7-Bit Passive Attenuator with Capacitive-Compensation-Based Bandwidth Extension Technique in 55-nm CMOS

A DC-Ka-Band 7-Bit Passive Attenuator with Capacitive-Compen...

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作者： Zhang, Zijiang Li, Nayu Gao, Huiyan Li, Min Wang, Shaogang Kuan, Yen-Cheng Song, Chunyi Yu, Xiaopeng Gu, Qun Jane Xu, Zhiwei Ocean College Institute of Marine Electronics and Intelligent Systems Zhejiang University Zhoushan China College of Information Science and Electronic Engineering Institute of VLSI Design Zhejiang University Hangzhou China Department of Electrical and Computer Engineering University of California at Davis DavisCA United States Engineering Research Center of Oceanic Sensing Technology and Equipment Ministry of Education Zhoushan316021 China Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Zhoushan316021 China International College of Semiconductor Technology National Chiao Tung University Hsinchu30010 Taiwan

This article presents a 7-bit wideband passive attenuator with low insertion loss (IL) and high attenuation accuracy in 55-nm CMOS technology. The $\pi $ -type and bridge-T-type attenuation units utilize an effective capacitive compensation technique, whose bandwidth extension mechanism is detailed in a single-unit pole-zero analysis. The matching-induced performance deterioration is investigated to minimize amplitude and phase errors at the chip level. The fabricated attenuator demonstrates a 32.4-dB attenuation range with a 0.255-dB resolution and a 3.5-8.4-dB IL from dc to 32 GHz. The measured root-mean-square (rms) amplitude and phase errors are below 0.32 dB and 5.33°, respectively. The attenuator occupies a 0.054-mm2 core area and consumes negligible power. © 1963-2012 IEEE.

关键词： Insertion losses

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Towards the hierarchical state machine oriented proteus systems programming language

Towards the hierarchical state machine oriented proteus syst...

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Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020

作者： Tellier, Daniel Millman, Meyer McClelland, Brian Go, Kate Beatrix Balayan, Alice Munje, Michael J. Dewey, Kyle Ho, Nhut Havelund, Klaus Ingham, Michel Department of Computer Science California State University Northridge NorthridgeCA91330 United States Department of Electrical and Computer Engineering California State University Northridge NorthridgeCA91330 United States Department of Mechanical Engineering California State University Northridge NorthridgeCA91330 United States Laboratory for Reliable Software Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Systems Engineering Division Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States

ISBN: (纸本)9781624106088

In space applications, hierarchical state machines (HSMs) are often used for writing simulation and control software, including that of the Curiosity rover. At the Jet Propulsion Lab (JPL), multiple programming languages have been developed specifically for writing HSM-based software, and these have been used in practice. However, we observe that the existing languages developed have significant issues with one or more of usability, performance, and safety, making them problematic for HSM-based development. To address these concerns, we are taking lessons learned from these languages and developing a new programming language named Proteus. Proteus builds HSM support directly into the language, and permits complex HSMs to be defined which communicate with each other. Proteus is designed with a look and feel similar to C/C++, making it usable and overall approachable for use by JPL systems engineers. Proteus itself compiles to C++, allowing it to fit easily into existing development toolchains, and making it amenable to embedded real-time systems. To ensure that Proteus will be of use to its target audience, it is being developed iteratively through a series of prototypes which are regularly evaluated by key stakeholders at JPL, allowing us to refine its design if we go off course. While Proteus is still very young in its development, we demonstrate its basic viability on an example utilizing multiple independent HSMs communicating with each other, and relevant execution traces. In the future, we plan to apply Proteus to larger HSMs taken from real space applications, and many additional relevant features are planned. © 2020 The MITRE Corporation. All Rights Reserved.

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A review:Photonics devices,architectures,and algorithms for optical neural computing

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Journal of Semiconductors 2021年第2期42卷 64-79页

作者： Shuiying Xiang Yanan Han Ziwei Song Xingxing Guo Yahui Zhang Zhenxing Ren Suhong Wang Yuanting Ma Weiwen Zou Bowen Ma Shaofu Xu Jianji Dong Hailong Zhou Quansheng Ren Tao Deng Yan Liu Genquan Han Yue Hao State Key Laboratory of Integrated Service Networks Xidian UniversityXi'an 710071China State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology School of MicroelectronicsXidian UniversityXi’an 710071China State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(iMLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China Wuhan National Laboratory for Optoelectronics School of Optical and Electronic InformationHuazhong University of Science and TechnologyWuhan 430074China School of Electronics Engineering and Computer Science Peking UniversityBeijing 100871China School of Physical Science and Technology Southwest UniversityChongqing 400715China

The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore *** neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed,wide bandwidth,and massive ***,we offer a review on the optical neural computing in our research groups at the device and system *** photonics neuron and photonics synapse plasticity are *** addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement ***,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives.

关键词： photonics neuron photonic STDP photonic spiking neural network optical reservoir computing optical convolutional neural network neuromorphic photonics

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A new framework of evolutionary multi-objective algorithms with an unbounded external archive

TechRxiv

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TechRxiv 2020年

作者： Ishibuchi, Hisao Pang, Lie Meng Shang, Ke Shenzhen Key Laboratory of Computational Intelligence University Key Laboratory of Evolving Intelligent Systems of Guangdong Province Department of Computer Science and Engineering Southern University of Science and Technology China

This paper proposes a new framework for the design of evolutionary multi-objective optimization (EMO) algorithms. The main characteristic feature of the proposed framework is that the optimization result of an EMO algorithm is not the final population but a subset of the examined solutions during its execution. As a post-processing procedure, a pre-specified number of solutions are selected from an unbounded external archive where all the examined solutions are stored. In the proposed framework, the final population does not have to be a good solution set. The point of the algorithm design is to examine a wide variety of solutions over the entire Pareto front and to select well-distributed solutions from the archive. In this paper, first we explain difficulties in the design of EMO algorithms in the existing two frameworks: non-elitist and elitist. Next, we propose the new framework of EMO algorithms. Then we demonstrate advantages of the proposed framework over the existing ones through computational experiments. Finally we suggest some interesting and promising future research topics. © 2020, CC BY.

关键词： Multiobjective optimization

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Non-elitist Evolutionary Multi-objective Optimizers Revisited

arXiv

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arXiv 2020年

作者： Tanabe, Ryoji Ishibuchi, Hisao Shenzhen Key Laboratory of Computational Intelligence University Key Laboratory of Evolving Intelligent Systems of Guangdong Province Department of Computer Science and Engineering Southern University of Science and Technology China

Since around 2000, it has been considered that elitist evolutionary multi-objective optimization algorithms (EMOAs) always outperform non-elitist EMOAs. This paper revisits the performance of non-elitist EMOAs for bi-objective continuous optimization when using an unbounded external archive. This paper examines the performance of EMOAs with two elitist and one non-elitist environmental selections. The performance of EMOAs is evaluated on the bi-objective BBOB problem suite provided by the COCO platform. In contrast to conventional wisdom, results show that non-elitist EMOAs with particular crossover methods perform significantly well on the bi-objective BBOB problems with many decision variables when using the unbounded external archive. This paper also analyzes the properties of the non-elitist selection. Copyright © 2020, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Sum-Rate Maximization of RIS-Aided Multi-User MIMO systems with Statistical CSI

arXiv

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arXiv 2021年

作者： Zhang, Huan Ma, Shaodan Shi, Zheng Zhao, Xin Yang, Guanghua The State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau 999078 China The Institute of Physical Internet The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Department of Electrical and Computer Engineering University of Macau Taipa 999078 China

This paper investigates a reconfigurable intelligent surface (RIS)-aided multi-user multiple-input multiple-output (MIMO) system by considering only the statistical channel state information (CSI) at the base station (BS). We aim to maximize its sum-rate via the joint optimization of beamforming at the BS and phase shifts at the RIS. However, the multi-user MIMO transmissions and the spatial correlations make the optimization cumbersome. For tractability, a deterministic approximation is derived for the sum-rate under a large number of the reflecting elements. By adopting the approximate sum-rate for maximization, the optimal designs of the transmit beamforming and the phase shifts can be decoupled and solved in closed-forms individually. More specifically, the global optimality of the transmit beamforming can be guaranteed by using water-filling algorithm and a sub-optimal solution of phase shifts can be obtained by using projected gradient ascent (PGA) algorithm. By comparing to the case of the instantaneous CSI assumed at the BS, the proposed algorithm based on statistical CSI can achieve comparable performance but with much lower complexity and signaling overhead, which is more affordable and appealing for practical applications. Moreover, the impact of spatial correlation is thoroughly examined by using majorization theory. © 2021, CC BY.

关键词： MIMO systems

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An integrated GIS-based multivariate adaptive regression splines-cat swarm optimization for improving the accuracy of wildfire susceptibility mapping

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Geocarto International 2023年第1期38卷

作者： Hai, Tao Theruvil Sayed, Biju Majdi, Ali Zhou, Jincheng Sagban, Rafid Band, Shahab S. Mosavi, Amir School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Guizhou Duyun China Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) Universiti Teknologi MARA Selangor Shah Alam Malaysia Department of Computer Science Dhofar University Salalah Oman Department of Building and Construction Technologies Engineering Al-Mustaqbal University College Hilla Iraq Department of Computer Technology Engineering Technical Engineering College Al-Ayen University Thi-Qar Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou Taiwan John von Neumann Faculty of Informatics Obuda University Budapest Hungary German Research Center for Artificial Intelligence Oldenburg Germany Institute of the Information Society University of Public Service Budapest Hungary

A hybrid machine learning method is proposed for wildfire susceptibility mapping. For modeling a geographical information system (GIS) database including 11 influencing factors and 262 fire locations from 2013 to 2018 is used for developing an integrated multivariate adaptive regression splines (MARS). The cat swarm optimization (CSO) algorithm tunes the parameters of the MARS in order to generate accurate susceptibility maps. From the Pearson correlation results, it is observed that land use, temperature, and slope angle have strong correlation with the fire severity. The results demonstrate that the prediction capability of the MARS-CSO model outperforms model tree, reduced error pruning tree and MARS. The resulting wildfire risk map using MARS-CSO reveals that 20% of the study areas is categorized in the very low wildfire risk class, whereas 40% is under the very high class of fire hazard. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： artificial intelligence cat swarm optimization geospatial machine learning natural hazard Wildfire susceptibility

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A Fuzzy Rule-Based Control System for Fast Line-Following Robots

A Fuzzy Rule-Based Control System for Fast Line-Following Ro...

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International Conference on Distributed Computing in Sensor systems (DCOSS)

作者： G. Eleftheriou L. Doitsidis Z. Zinonos S. A. Chatzichristofis Department of Computer Science Intelligent Systems Laboratory Neapolis University Pafos Cyprus School of Production Engineering and Management Technical University of Crete Greece

ISBN: (数字)9781728143514

ISBN: (纸本)9781728198040

This paper focuses on the optimization of the line-tracking and following control technique used in high speed autonomous movable IoT devices such as line-following robotic vehicles. A fusion of a new pro-active / feed-forward control system, based on the simultaneous use of computer vision and the use of an array of analog infrared reflective phototransistors with an optimised PID based feed-back implementation is proposed. Experimental evaluations demonstrate that the proposed approach aids and improves the performance of line-following robots compared to the traditional PID technique.

关键词： Robot sensing systems Fuzzy logic Cameras Navigation Robustness Mobile robots

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