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2010 IEEE World Congress on Computational Intelligence

作者： Takeda, Takahiro Taniguchi, Kazuhiko Asari, Kazunari Kuramoto, Kei Kobashi, Syoji Hata, Yutaka Univ Hyogo Grad Sch Engn Hyogo Japan Kinden Co Osaka Japan Kansai Elect Power Co Inc Tokyo Japan Osaka Univ WPI Immunol Frontier Res Ctr Osaka Japan

ISBN: (纸本)9781424469208

This paper proposes a biometric personal authentication method based on one step foot pressure distribution change. We acquire the foot pressure distribution change by mat type load distribution sensor and use it as a personal authentication. We employ twelve features based on shape of footprint, and twenty seven features based on movement of weight while walking. A classifier for each feature is developed on the basis of fuzzy inference. The classifier is trained by a clonal selection algorithm in artificial immune system. A personal authentication system for one step is made every classifier for all features. We employed 10 volunteers, and we took the step data five times. We evaluated our method by five-fold cross validation method. We obtained low false rejection and acceptance rates in identification and verification.

关键词： artificial immune systems authorisation biometric personal authentication biometrics (access control) clonal selection algorithm distributed sensors feature classifier feature extraction fuzzy artificial immune system fuzzy inference fuzzy set theory inference mechanisms load distribution sensor one step foot pressure distribution change pattern classification pressure sensors

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A Novel Immune-PSO algorithm for Job Shop Scheduling

A Novel Immune-PSO Algorithm for Job Shop Scheduling

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International Conference on Material and Manufacturing Technology

作者： Hong Lu Yang Jing Huaihai Inst Technol Dept Elect Engn Lianyungang Peoples R China Guizhou Univ Coll Elect Engn Guiyang Peoples R China

ISBN: (纸本)9780878492435

The job shop scheduling problem (JSSP) is one of the most difficult problems, as it is classified as an NP-complete one. Particle Swarm Optimization, a nature-inspired evolutionary algorithm, has been successful in solving a wide range of real-value optimization problems. However, little attempts have been made to extend it to discrete problems. In this paper, a new particle swarm optimization method based on the clonal selection algorithm is proposed to avoid premature convergence and guarantee the diversity of the population. Experimental results indicate that the proposed algorithm is highly competitive, being able to produce better solutions than GA and clonalG in several cases, and is a viable alternative for solving efficiently job shop scheduling problem.

关键词： Artificial immune system clonal selection algorithm PSO Job shop scheduling problem

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An Improved Artificial Immune Approach to Network Intrusion Detection

An Improved Artificial Immune Approach to Network Intrusion ...

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The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

作者： Xianjin Fang Longshu Li School of Computer Science and Engineering Anhui University of Science and Technology Huainan 23200 School of Computer Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9781424458455;9781424458486;9781424458479;9781424458462

The definition of vaccine, vaccine autonomous obtaining algorithm, vaccination operator and evolution of vaccine library are proposed in this paper. The generic clonal selection algorithm is improved by integrating with vaccine autonomous obtaining and vaccination operator, whose purpose is to accelerate the convergence speed of clonal selection algorithm, and improve the efficiency of the algorithm. The improved clonal selection algorithm together with negative selection mechanism in immunology is used to create the model of network intrusion detection. Simulated experimental results and theoretical computation efficiency analyses demonstrate the availability of the model and the speedup of convergence.

关键词： Artificial Immune System clonal selection algorithm Vaccination operator network Intrusion Detection

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Orthogonal Immune algorithm with Diversity-based selection for Numerical Optimization 09

Orthogonal Immune Algorithm with Diversity-based Selection f...

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World Summit on Genetic and Evolutionary Computation (GEC 09)

作者： Gong, Maoguo Jiao, Licheng Ma, Wenping Xidian Univ Inst Intelligent Informat Proc Minist Educ China Key Lab Intelligent Percept & Image Understanding Xian 710071 Peoples R China

ISBN: (纸本)9781605583266

In this study, we design an Orthogonal Immune algorithm (OIA) for numerical optimization by incorporating orthogonal initialization, a novel neighborhood orthogonal cloning operator, a static hypermutation operator, and a novel diversity-based selection operator. The OIA is unique in three respects: Firstly, a new selection method based on orthogonal arrays is provided in order to maintain diversity in the population. Secondly, the orthogonal design with quantization technique is introduced to generate initial population. Thirdly, the orthogonal design with the modified quantization technique is introduced into the cloning operator. In order to identify any improvement due to orthogonal initialization, diversity-based selection and neighborhood orthogonal cloning, we modify the OIA via replacing its orthogonal initialization by random initialization;replacing its diversity-based selection by a standard evolutionary operator (mu+lambda)-selection operator;and replacing its neighborhood orthogonal cloning by proportional cloning, and compare the four version algorithms in solving eight benchmark functions and six composition functions.

关键词： Orthogonal experimental design clonal selection algorithm evolutionary algorithm numerical optimization

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A Novel Clone selection algorithm for High-dimensional Global Optimization Problems

A Novel Clone Selection Algorithm for High-dimensional Globa...

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Asia-Pacific Conference on Information Processing (APCIP 2009)

作者： Liu, Xingbao Shi, Liangwu Chen, Rongyuan Chen, Haijun Hunan Coll Business Educ Ctr Modern Tech Changsha Hunan Peoples R China

ISBN: (纸本)9780769536996

The clone selection algorithm (CSA) is a stochastic, population-based evolutionary method that can be applied to the global optimization problems. The paper proposes a variation on the traditional CSA: clone selection algorithm with simplex crossover, or CSA_SPX. The novel algorithm employs the randomized distribution scheme for clone individuals, bit hyper-mutation and simplex crossover to significantly improve the performance of the original algorithm. Application of the CSA_SPX on 23 benchmark optimization problems shows a marked improvement in performance over the traditional CSA.

关键词： clonal selection algorithm simplex crossover global optimization differential evolution

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Improving the performance of DCT-based fragile watermarking using intelligent optimization algorithms

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OPTICS COMMUNICATIONS 2009年第14期282卷 2806-2817页

作者： Aslantas, Veysel Ozer, Saban Ozturk, Serkan Erciyes Univ Dept Comp Engn TR-38039 Kayseri Turkey Erciyes Univ Dept Elect & Elect Engn TR-38039 Kayseri Turkey

The performance of a fragile watermarking method based on discrete cosine transform (DCT) has been improved in this paper by using intelligent optimization algorithms (IOA). namely genetic algorithm, differential evolution algorithm, clonal selection algorithm and particle swarm optimization algorithm. In DCT based fragile watermarking techniques, watermark embedding can usually be achieved by modifying the least significant bits of the transformation coefficients. After the embedding process is completed, transforming the modified coefficients from the frequency domain to the spatial domain produces some rounding errors due to the conversion of real numbers to integers. The rounding errors caused by this transformation process were corrected by the use of intelligent optimization algorithms mentioned above. This paper gives experimental results which show the feasibility of using these optimization algorithms for the fragile watermarking and demonstrate the accuracy of these methods. The performance comparison of the algorithms was also realized. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Fragile watermarking DCT Genetic algorithm Differential evolution algorithm clonal selection algorithm Particle swarm optimization algorithm

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Design Earthquake Ground Motion Prediction for Perth Metropolitan Area with Microtremor Measurements for Site Characterization

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JOURNAL OF EARTHQUAKE ENGINEERING 2009年第7期13卷 997-1028页

作者： Liang, Jonathan Z. Hao, Hong Wang, Ying Bi, Kai Ming Univ Western Australia Sch Civil & Resource Engn Crawley WA 6009 Australia

Perth is the largest city in Western Australia and home to three-quarters of the state's residents. In recent decades, there have been a lot of earthquake activities just east of Perth in an area known as the South-West Seismic Zone. Previous numerical results of site response analyses based on limited available geology information for PMA indicated that Perth Basin might amplify the bedrock motion by more than 10 times at some frequencies and at some sites. Hence, more detailed studies on site characterization and amplification are necessary. The microtremor method using spatial autocorrelation (SPAC) processing is a useful tool for gaining thickness and shear wave velocity (SWV) of sediments and has been adopted in many previous studies. In this study, the response spectrum of rock site corresponding to the 475-year return period for PMA is defined according to the probabilistic seismic hazard analysis (PSHA) based on the latest ground motion attenuation model of Southwest Western Australia. Site characterization in PMA is performed using two microtremor measurements, namely SPAC technique and H/V method. The clonal selection algorithm (CSA) is introduced to perform direct inversion of SPAC curves to determine the soil profiles of representative PMA sites investigated in this study. Using the simulated bedrock motion as input, the responses of the soil sites are estimated using numerical method based on the shear-wave velocity vs. depth profiles determined from the SPAC technique. The response spectrum of the earthquake ground motion on surface of each site is derived from the numerical results of the site response analysis, and compared with the respective design spectrum defined in the Australian Earthquake Loading Code. The comparison shows that the code spectra are conservative in the short period range, but may slightly underestimate the response spectrum at some long period range.

关键词： Site Response SPAC Method clonal selection algorithm Response Spectrum Ground Motion

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clonal selection Based Memetic algorithm for Job Shop Scheduling Problems

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Journal of Bionic Engineering 2008年第2期5卷 111-119页

作者： Jin-hui Yang Liang Sun Heow Pueh Lee Yun Qian Yan-chun Liang College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012 P. R. China Institute of High Performance Computing Singapore 117528 Singapore Department of Mechanical Engineering National University of Singapore Singapore 117576 Singapore Institute of Electric and Information Engineering Beihua University Jilin 13202 l P. R. China

A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki＇s neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algorithm.

关键词： job shop scheduling problem clonal selection algorithm simulated annealing global search local search

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clonal selection algorithm in power filter optimization

Clonal selection algorithm in power filter optimization

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IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications

作者： Wang, X Aalto Univ Inst Intelligent Power Elect FIN-02150 Espoo Finland

ISBN: (纸本)0780389425

Inspired by natural immune mechanisms, Artificial Immune Optimization (AIO) methods have been successfully applied to deal with numerous challenging optimization problems with superior performances over classical optimization techniques. clonal selection algorithm (CSA) is one of the most widely employed immune-based approaches for handling those optimization tasks. In this paper, the proposed CSA is used to search for the optimal parameters (values of inductor and capacitor) of a passive filter in the diode full-bridge rectifier. Simulation results demonstrate that the CSA-based approach can acquire the optimal LC parameters with certain given criteria for power filter design.

关键词： artificial immune system optimization clonal selection algorithm passive filter harmonic distortion

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Automatic Estimation of the Object Pose for Industrial Robots

Automatic Estimation of the Object Pose for Industrial Robot...

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IEEE International Workshop on Imaging Systems and Techniques

作者： Xu Haili Wang Sun'an Zhang Xingguo Hua Guoran Xi An Jiao Tong Univ Sch Mech Engn Xian Shanxi Peoples R China Nantong Univ Sch Mech Engn Jiangsu Peoples R China

ISBN: (纸本)9781424434824

An industrial robot equipped with a camera system requires robust and accurate estimation of the pose of a target object. The pose estimation is achieved by a three-dimensional registration method. This paper presents this novel method for the registration of the rotated and translated part according to its camera images and three-dimensional model. The spatial registration parameters can be computed by finding which projection of the volume is the most similar to the given image. We propose a three-step procedure. First, we compute the Fourier transform (FT) of the volume projection by using FT projection theorem. Then, a cost function is designed according to the magnitude of projection FT and image FT. Last, an optimization algorithm called Small World clonal selection algorithm (SWCSA) is applied to obtain spatial registration parameters. SWCSA combines the good local search ability in clonal selection algorithm and the random long-range search operator in small world, so the global optimization ability is enhanced. Experimental results demonstrate that the registration is accurate and robust.

关键词： registration pose clonal selection algorithm small world

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