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Congress on Evolutionary Computation

作者： Zhijian Wu Zhilong Tang Jun Zou Lishan Kang Mingbiao Li State Key Laboratory of Software Engineering Wuhan University of China Wuhan China Department of Mathematics Chinese University of Hong Kong New Territories Hong Kong China School of Computer Science and Engineering Wenzhou Normal College Wenzhou Zhejiang China

ISBN: (纸本)0780385152

In this paper, we construct an evolutionary algorithm. It yields good performance on a collection of elliptic parameter identification problems. The evolutionary algorithm has a good tolerability for the noise in the observed data. Even when the noise level is up to 10%, we can also get such a good result. The result of numerical experiments shows explicitly that the algorithm is very fit for solving this kind of inverse problem but not very sensitive to the noise.

关键词： Evolutionary computation Parameter estimation Inverse problems laboratories software engineering Mathematics computer science Educational institutions Noise level Data engineering

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Benchmarking algorithms for dynamic travelling salesman problems

Benchmarking algorithms for dynamic travelling salesman prob...

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Congress on Evolutionary Computation

作者： Lishan Kang Aimin Zhou B. McKay Yan Li Zhuo Kang State Key Laboratory of Software Engineering Wuhan University of China Wuhan China Department of Computer Science & Technology China University of Geoscience Wuhan China School of IT & EE University of New South Wales Canberra Australia Computer Center Wuhan University Wuhan China

Dynamic optimisation problems are becoming increasingly important; meanwhile, progress in optimisation techniques and in computational resources are permitting the development of effective systems for dynamic optimisation, resulting in a need for objective methods to evaluate and compare different techniques. The search for effective techniques may be seen as a multi-objective problem, trading off time complexity against effectiveness; hence benchmarks must be able to compare techniques across the Pareto front, not merely at a single point. We propose benchmarks for the dynamic travelling salesman problem, adapted from the CHN-144 benchmark of 144 Chinese cities for the static travelling salesman problem. We provide an example of the use of the benchmark, and illustrate the information that can be gleaned from analysis of the algorithm performance on the benchmarks.

关键词： Heuristic algorithms Distributed computing Grid computing Traveling salesman problems Cities and towns computer networks Peer to peer computing Optimization methods Mobile computing Evolutionary computation

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Optimal ramped-gate soft programming of over-erased flash EEPROM cells at given current

Optimal ramped-gate soft programming of over-erased flash EE...

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2004 7th International Conference on Solid-state and Integrated Circuits Technology Proceedings, ICSICT 2004

作者： Quan, Wu-Yun Baek, Chang-Ki Kim, Dae M. Gang, Ruan Huang, Yiping ASIC and System State-Key Research Lab. Department of Microelectronics Fudan University 220 Handan-road 200433 Shanghai China School of Electrical Engineering and Computer Science ISRC Seoul National University Kwanak P.O. Box 34 Seoul 151-744 Korea Republic of Korea Institute for Advanced Study 207-43 Cheongryangri Seoul Korea Republic of

Presented herein is an efficient simulation technique enabling systematic investigation of the soft programming over-erased flash EEPROM cells. The simulation provides a method by which to find the optimal soft programming technique for given current. The method requires only the cell performance data and allows investigation of the soft programming under various bias conditions. In principle, the methodology can also be used to investigate the programming and erase operations. © 2004 IEEE.

关键词： Flash memory

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A chromosome-based evaluation model for computer defense immune systems

A chromosome-based evaluation model for computer defense imm...

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2003 Congress on Evolutionary Computation, CEC 2003

作者： Wu, Zejun Dong, Hongbin Liang, Yiwen McKay, R.I. School of Computer State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 China School of Information Technology and Electrical Engineering University of New South Wales at ADFA Canberra Australia

ISBN: (纸本)0780378040

The computer defense immune system (GDIS) is an artificial immune system for detecting computer viruses and network intrusions. We present a simple chromosome-based evaluation model for GDIS. In this model, the genotype space is a linear number sequence, and a digital pattern sequence is produced as the phenotype space using a number of mechanisms, including pattern mining and genetic algorithms. We present a range of experiment analyses to show the higher efficiency and stronger immunity of this model, improving the rate of successful prediction in intrusion detection in GDIS. The detectors generated may have higher coverage, hence would impose lower communications and computational loads on systems in which they were incorporated. © 2003 IEEE.

关键词： Immune system

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Applying Evolutionary Algorithm to Public key Cryptosystems

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Wuhan University Journal of Natural Sciences 2003年第S1期8卷 287-293页

作者： Tu Hang, Li Li, Wu Tao-jun, Li Yuan-xiangstate key laboratory of software engineering, Wuhan University, Wuhan 430072, Hubei,China)school of computer, Wuhan University, Wuhan 430072, Hubei,China State Key Laboratory of Software Engineering Wuhan University Wuhan Hubei China School of Computer Wuhan University Wuhan Hubei China

A best algorithm generated scheme is proposed in the paper by making use of the thought of evolutionary algorithm, which can generate dynamically the best algorithm of generating primes in RSA cryptography under different conditions. Taking into account the factors of time, space and security integrated, this scheme possessed strong practicability. The paper also proposed a model of multi-degree parallel evolutionary algorithm to evaluate synthetically the efficiency and security of the public key cryptography. The model contributes to designing public key cryptography system too.

关键词： prime generation RSA public key cryptography evolutionary algorithm

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Do Search and Selection Operators Play Important Roles in Multi-Objective Evolutionary Algorithms:A Case Study

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Wuhan University Journal of Natural Sciences 2003年第S1期8卷 195-201页

作者： Yan Zhen-yu, Kang Li-shan, Lin Guang-ming ,He Meistate key laboratory of software engineering, Wuhan University, Wuhan 430072, Hubei, Chinaschool of computer Science, UC, UNSW Australian Defence Force Academy, Northcott Drive, Canberra, ACT 2600 AustraliaCapital Bridge Securities Co. ,Ltd, Floor 42, Jinmao Tower, Shanghai 200030, China Wuhan University State Key Laboratory of Software Engineering Wuhan Hubei China (GRID:grid.49470.3e) (ISNI:***) UC UNSW Australian Defence Force Academy School of Computer Science Canberra Australia (GRID:grid.97008.36) (ISNI:***) Capital Bridge Securities Co. Ltd Shanghai China (GRID:grid.97008.36)

Multi-objective Evolutionary Algorithm (MOEA) is becoming a hot research area and quite a few aspects of MOEAs have been studied and discussed. However there are still few literatures discussing the roles of search and selection operators in MOEAs. This paper studied their roles by solving a case of discrete Multi-objective Optimization Problem (MOP): Multi-objective TSP with a new MOEA. In the new MOEA, We adopt an efficient search operator, which has the properties of both crossover and mutation, to generate the new individuals and chose two selection operators: Family Competition and Population Competition with probabilities to realize selection. The simulation experiments showed that this new MOEA could get good uniform solutions representing the Pareto Front and outperformed SPEA in almost every simulation run on this problem. Furthermore, we analyzed its convergence property using finite Markov chain and proved that it could converge to Pareto Front with probability 1. We also find that the convergence property of MOEAs has much relationship with search and selection operators.

关键词： multi-objective evolutionary algorithm convergence property analysis search operator selection operator Markov chain

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A chromosome-based evaluation model for computer defense immune systems

A chromosome-based evaluation model for computer defense imm...

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Congress on Evolutionary Computation

作者： Zejun Wu Hongbin Dong Yiwen Liang R.I. McKay School of Computer / State Key Laboratory of Software Engineering Wuhan University of China Wuhan China School of Information Technology and Electrical Engineering University of New South Wales Canberra Australia

关键词： Biological cells Immune system Intrusion detection Detectors computer networks computer viruses Biology computing Artificial immune systems Predictive models Distributed computing

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Multi-objective and MGG evolutionary algorithm for constrained optimization

Multi-objective and MGG evolutionary algorithm for constrain...

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Congress on Evolutionary Computation

作者： Yuren Zhou Yuanxing Li Jun He Lishan Kang College of Computer Science and Engineering South China University of Technology Guangzhou China State key Laboratory of Software Engineering Wuhan University Wuhan China School of Computer Science University of Binningham Edgbaston UK

ISBN: (纸本)0780378040

This paper presents a new approach to handle constrained optimization using evolutionary algorithms. The new technique converts constrained optimization to a two-objective optimization: one is the original objective function, the other is the degree function violating the constraints. By using Pareto-dominance in the multi-objective optimization, individual's Pareto strength is defined. Based on Pareto strength and minimal generation gap (MGG) model, a new real-coded genetic algorithm is designed. The new approach is compared with some other evolutionary optimization techniques on several benchmark functions. The results show that the new approach outperforms those existing techniques in feasibility, effectiveness and generality. Especially for some complicated optimization problems with inequality and equality constraints, the proposed method provides better numerical accuracy.

关键词： Constraint optimization Evolutionary computation Pareto optimization Genetic programming computer science Genetic algorithms software engineering Testing Educational institutions Helium

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C-pruner: an improved instance pruning algorithm

C-pruner: an improved instance pruning algorithm

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ke-Ping Zhao Shui-Geng Zhou Ji-Hong Guan Ao-Ying Zhou Department of Computer Science & Engineering Fudan University Shanghai China State Key Laboratory of Software Engineering Wuhan University of China Wuhan China School of Computer Science Wuhan University of China Wuhan China

ISBN: (纸本)0780378652

Instance-based learning faces the problem of deciding which instances could be discarded in order to save computation and storage costs. For large instance bases classifier suffers from large memory requirements and slow response. And present noisy instances may deteriorate the classification accuracy. This paper analyzes the strength and weakness of some of the existing algorithms for instance pruning, and propose an improved method C-Pruner. Experiments over real-world datasets verify C-pruner's superior to the existing methods in classification accuracy.

关键词： Nearest neighbor searches Algorithm design and analysis computer science Computational efficiency software engineering Noise reduction Machine learning Cybernetics Machine learning algorithms Classification algorithms

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AN ALGORITHM FOR FAULT DIAGNOSIS BASED ON COMBINATORIAL DESIGN APPROACH FOR TESTING

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Journal of Electronics(China) 2003年第3期20卷 224-226页

作者： Nie Changhai Xu Baowen Shi Liang (Dept. of computer Science & Eng., Southeast Univ., Nanjing 210096) (state key laboratory of software engineering, Wuhan University, Wuhan 430072) (Jiangsu key lab. of computer Info. Proc. Tech., Soochow Univ., Suzhou 215006) Dept. of Computer Science & Eng. Southeast Univ. Nanjing State Key Laboratory of Software Engineering Wuhan University Wuhan Jiangsu Key Lab. of Computer Info. Proc. Tech. Soochow Univ. Suzhou

Much research has been done mainly in testcase generation and its effect for com-binatorial design approach for testing. This letter presents an algorithm for fault diagnosis basedon the approach. It can conclude that the factors, which cause errors, must be in a very smallrange through analyzing the test cases after testing, and retesting with some complementary testcases. The algorithm can provide a very efficient and valuable guidance for the debugging andtesting of software.

关键词： software testing Combinatorial testing Fault diagnosis

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