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An Improved MPCA Algorithm with Weight Matrix Based on Many-Objective Optimization 1

17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Huang, Jianrou Zhang, Jingbo Wang, Qian Cai, Xingjuan Complex System and Computational Intelligent Laboratory Taiyuan University of Science and Technology Taiyuan030024 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Data compression and dimensionality reduction play an essential role in machine learning. In recent years, due to the relatively high dimensionality of data, dimensionality reduction based on vectors cannot be well processed and will destroy the structure of high-dimensional data. Therefore, research on dimensionality reduction based on tensors is increasing daily. This paper mainly studies the extended multi-linear principal component analysis (MPCA) of principal component analysis (PCA) in the tensor space. This paper proposes a MPCA dimension reduction algorithm based on the weight matrix, followed by the construction of a multi-objective model. An IP-NSGA-III is proposed to solve the weight matrix. Experimental results of hyperspectral image classification show that, compared with different algorithms, the MPCA algorithm based on the weight matrix proposed in this paper has a better dimension-reduction effect. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Principal component analysis

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A Multi-objective Bat Algorithm for Software Defect Prediction 14th

A Multi-objective Bat Algorithm for Software Defect Predicti...

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14th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2019

作者： Wu, Di Zhang, Jiangjiang Geng, Shaojin Cai, Xingjuan Zhang, Guoyou Complex System and Computational Intelligent Laboratory Taiyuan University of Science and Technology Taiyuan030024 China

ISBN: (纸本)9789811534249

Both the class imbalance of datasets and parameter selection of support vector machine (SVM) play an important role in the process of software defect prediction. To solve these two problems synchronously, the false positive rate (pf) and the probability of detection (pd) are considered as two objective functions to construct the multi-objective software defect prediction model in this paper. Meanwhile, a multi-objective bat algorithm (MOBA) is designed to solve this model. The individual update strategy in the population is performed using the individual update method in the fast triangle flip bat algorithm, and the non-dominated solution set is used to save the better individuals of the non-defective module and the support vector machine parameters. The simulation results show that MOBA can effectively save resource consumption and improve the quality of software compared with other commonly used algorithms. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

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Spectral gap, isoperimetry and concentration on trees

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Science China Mathematics 2016年第3期59卷 539-556页

作者： LIU Wei MA Yu Tao WU Li Ming School of Mathematics and Statistics Wuhan University Computational Science Hubei Key Laboratory Wuhan University School of Mathematical Sciences & Laboratory of Complex System and Intelligent Control Beijing Normal University Laboratoire de Mathematics Université Blaise Pascal

We consider the nearest-neighbor model on the finite tree T with generator L. We obtain a twosided estimate of the spectral gap by factor 2. We also identify explicitly the Lipschitzian norm of the operator(-L)^(-1) in propriate functional space. This leads to the identification of the best constant in the generalized Cheeger isoperimetric inequality on the tree, and to transportation-information inequalities.

关键词： tree nearest-neighbor model Poisson equation transportation-information inequality concentration inequality Cheeger-type isoperimetric inequality

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Demand estimation of water resources based on algorithm comparison

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International Journal of Wireless and Mobile Computing 2019年第2期16卷 110-116页

作者： Wang, Junyan Zhang, Jiangjiang Cai, Xingjuan Ma, Yanyan Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang330099 China Complex System and Computational Intelligence Laboratory TaiYuan University of Science and Technology Taiyuan003024 China Shanxi Cloud Era TISCO Information Automation Technology Co. Ltd. Taiyuan030003 China

Water is the source of life and the correct assessment of water resources is an important prerequisite for the rational utilisation of water resources. In this paper, water resources are evaluated and predicted by three different algorithms, including Bat Algorithm (BA), Particle Swarm Optimisation (PSO) and Pigeon-Inspired Optimisation (PIO). Comparing the errors of water resources assessed for the three algorithms, we select an algorithm of the minimum error to predict the future water demand. In the experiments, firstly, the water data from 2003 to 2012 are used to find the optimal weights of the models. Then, the weight factor is combined with the given model to gain the error between predicted value and the remaining data (2013–2015). Finally, the simulation results show that PIO algorithm has a better performance compared with the BA and PSO algorithms. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Water resources

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Improving Auction Mechanisms for Online Real-Time Bidding Advertising with a Two-stage Resale Model

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IFAC-PapersOnLine 2017年第1期50卷 13575-13580页

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Real Time Bidding (RTB), widely publicized as one of the most promising big-data-driven business models for online computational advertising, has the potential of effectively monetizing user clicks and impressions via two-stage auctions with resale. Demand side platforms (DSPs) play a key role as intermediators in this auction process. Typically, the first-stage auctions will be conducted separately in each DSP to determine one winning advertiser registered on it, and in the second-stage auction, each DSP submits a bid based on its winning advertiser's bid to the ad exchange platform (AdX). The highest-bid DSP wins the ad impression from AdX and resells it to its winning advertiser in pursuit of the intermediate fee. This two-stage resale auction is a critical component in maintaining the effectiveness and efficiency of RTB ecosystems. In this paper, we strive to identify and design potential improvements for this auction mechanism with the aim of enhancing the total revenue of both advertisers and DSPs. We also validated our proposed auction mechanisms using the computational experiment approach. The experimental results indicate that our proposed mechanisms can make both advertisers and DSPs better off. Our work represents the first step towards a new research area of optimal mechanism design for RTB auctions, and is expected to provide useful managerial insights in RTB market practice. © 2017

关键词： Sales Commerce Machine design Auction mechanisms computational advertisings computational experiment Critical component Demand side Effectiveness and efficiencies Optimal mechanism designs Real time

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A Blockchain-based Framework for Central Bank Digital Currency

A Blockchain-based Framework for Central Bank Digital Curren...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Han, Xuan Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781728128535

Cryptocurrency and blockchain technologies have developed in parallel in recent years, with technological breakthroughs in currency issuance, payment methods, and currency storage. However, the existing cryptocurrencies cannot replace fiat money. There is a huge gap between decentralized cryptocurrency and central bank digital currency, namely CBDC, in terms of monetary governance and circulation. In this paper, we propose the function and security requirements of CBDC, through a comprehensive analysis of the existing typical cryptocurrency and the prototype of the CBDC scheme. On this basis, we present a blockchain-based framework for CBDC with three layers, including supervisory layer, network layer and user layer, and describe the key business processes of the CBDC's entire lifecycle of issuance-circulation-withdrawal in detail. Finally, we take cross-border payment as an example to explain the transaction process of CBDC. We aim to provide theoretical guidance for CBDC design. © 2019 IEEE.

关键词： Blockchain

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A pigeon-inspired optimization algorithm for many-objective optimization problems

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Science China(Information Sciences) 2019年第7期62卷 131-138页

作者： Zhihua CUI Jiangjiang ZHANG Yechuang WANG Yang CAO Xingjuan CAI Wensheng ZHANG Jinjun CHEN Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Beijing Institute of Petrochemical Technology Faculty of Information Technology Beijing University of Technology State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences School of Software University of Technology Sydney

Dear editor,Swarm intelligence optimization algorithms are inspired by the behaviour of biological groups in nature. Such algorithms have the advantages of a clear structure, simple operation, comprehensible principles, strong parallelism, effective search abilities, and strong robustness. They can effectively solve difficult problems that traditional methods cannot. Pigeon-inspired optimization (PIO), a novel biomimetic swarm intelligence optimization algorithm, was proposed by Duan and Qiao in

关键词： A pigeon-inspired optimization algorithm for many-objective optimization problems Pareto

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A decentralized social networking architecture enhanced by blockchain

A decentralized social networking architecture enhanced by b...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Zeng, Shuai Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728128535

The privacy issues become a major problem that should be resolved for the existing centralized online social networks, which have prompted researchers to consider the decentralization framework for online social networks. In this paper, we propose a novel decentralized social networking architecture enhanced by blockchain technology. We use a sharding framework to increase the system scalability, a blockchain system to ensure the data integrity and consistency, a reputation-based authority control method to improve the system security. © 2019 IEEE.

关键词： Blockchain

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Interval Kalman Filter Based RFID Indoor Positioning

Interval Kalman Filter Based RFID Indoor Positioning

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第28届中国控制与决策会议

作者： Ning Li Hongbin Ma Chenguang Yang School of Automation Beijing Institute of Technology State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Zienkiewicz Centre for Computational Engineering Swansea University

ISBN: (纸本)9781467397155

Radio Frequency Identification(RFID) technology has shown its potential in the field of indoor positioning in recent years,and has been widely used in large establishments such as the airport lobby,supermarkets,libraries,underground parking and so ***,the complexity of the indoor environments make positioning a challenging problem in terms of accuracy,stability,reliability,and interference *** this paper,we develop an algorithm of passive RFID indoor positioning based on interval Kalman filter,according to the geometric constraints of responding tags,combined with the target motion *** interval Kalman filter is adopted to integrate target position of one preceding time point and reference tags position to estimate the current *** of this algorithm is to use passive tags to reduce hardware costs,and on the other hand the introduction of filtering algorithm improves the positioning accuracy.

关键词： RFID Indoor positioning Interval Kalman Filter Interval arithmetic

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Improved low energy adaptive clustering hierarchy protocol based on local centroid bat algorithm

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Sensor Letters 2014年第9期12卷 1372-1377页

作者： Cao, Yang Cui, Zhihua Li, Feixiang Dai, Chaohua Chen, Weirong Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Shanxi China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Electric Engineering Southwest Jiaotong University Sichuan China

Bat algorithm (BA) is a novel intelligent optimization algorithm. In order to improve the poor local search capability of the algorithm, we present a new variant of bat optimization algorithm based on local centroid strategy (LCBA). Meanwhile, LEACH is a low energy adaptive clustering hierarchy algorithm for wireless sensor networks (WSN). And it has many disadvantages such as random selection of cluster head, taking no account of the remaining energy and position of nodes. To solve these problems, this paper proposes an improved LEACH protocol based on local centroid bat algorithm. The improved protocol divides the cluster head selection process into optimization of temporary cluster head and formal cluster head selection. First, we generate temporary cluster heads by traditional LEACH protocol, then optimize these cluster heads based on LCBA and select formal cluster heads according to the remaining energy of nodes. The result of experiment shows that, comparing with LEACH, LEACH-LCBA can balance the network load efficiently, improve the energy utilization, prolong the network lifetime.

关键词： Energy utilization

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