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8th World Congress on Intelligent Control and Automation (WCICA)

作者： Wen, Xiulan Zhu, Xiaochun Wang, Dongxia Sheng, Danghong Nanjing Inst Technol Automat Dept Nanjing 211167 Peoples R China

ISBN: (纸本)9781424467129

Chaos underlies many natural phenomena and recognizing chaotic dynamics is potentially important. for understanding and managing real systems, This paper presents an immune evolutionary algorithm (IEA) based on the clonal selection, affinity maturation principles in immune system and the mutating ideas of biology evolutionary to train neural network for modeling and predicting chaotic time series, The method takes the weight and bias of neural network as antibody, the mean square. error between actual and desired output values of neural network as the objective function, and the objective function and constraints as antigen, An antibody that. most fits the antigen is the solution, Application for henon chaotic time series and complex mechanical vibration chaotic signal modeling and prediction are investigated, Compared the results with those obtained by back-propagation (BP), an improved genetic algorithm (IGA), particle swarm optimization (PSO) and hypid particle swarm optimization (HPSO), the proposed method has better precision for modelling and predicting chaotic time series,

关键词： Neural Network immune evolutionary algorithm chaotic time series modeling and prediction

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immune evolutionary algorithm to Reduce PAPR of OFDM Signals Using PTS Technique

Immune Evolutionary Algorithm to Reduce PAPR of OFDM Signals...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Hou, Jun Ge, Jianhua Huang, Songtao Xidian Univ State Key Lab Integrated Serv Networks Xian Peoples R China

ISBN: (纸本)9781424492688

Partial transmit sequences (PTS) is a distortionless phase optimization technique that significantly improves peak-to-average power ratio (PAPR) performance with a small amount of redundancy for orthogonal frequency division multiplexing (OFDM) systems. However, the computational complexity in conventional PTS increases exponentially with the number of subblocks. In this paper, a novel global parallel algorithm, combining the immune and versatile evolutionary mechanism, is proposed for PTS technique to reduce computational complexity and improve PAPR performance. The proposed scheme restrains the degenerate phenomenon effectively during the evolutionary process, thus making the fitness of population increase steadily. The simulation results show that the proposed scheme achieves significant PAPR reduction while maintaining low complexity.

关键词： Computational complexity evolutionary computation OFDM modulation OFDM signals Optimization PAPR reduction PTS technique Partial transmit sequences Peak to average power ratio artificial immune systems computational complexity computational complexity distortionless phase optimization technique evolutionary computation immune evolutionary algorithm orthogonal frequency division multiplexing system parallel algorithms partial transmit sequences peak-to-average power ratio sequences versatile evolutionary mechanism

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An immune evolutionary algorithm for sphericity error evaluation

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INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE 2004年第10期44卷 1077-1084页

作者： Wen, XL Song, AG Southeast Univ Dept Instrument Sci Nanjing 210096 Peoples R China Nanjing Inst Technol Dept Automat Nanjing 210013 Peoples R China

An immune evolutionary algorithm (IEA) is proposed by imitating the defense process of the immune system and the ideas of mutation in evolutionary biology. In the IEA, a self-adaptive mutation operator is constructed to decide the mutation step size of every antibody according to its environment, and an affinity calculation process is also embedded to maintain diversity. Application of the proposed algorithm to the evaluation of sphericity error is investigated. The method takes the sphericity error objective function and constraints as antigen. Through genetic evolution, an antibody that most fits the antigen becomes the solution. Finally, the experimental results evaluated by different methods confirm the effectiveness of the proposed IEA. Furthermore, the method has good flexibility and is also suitable for other evaluations of form errors such as circularity, flatness etc. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： sphericity error evaluation minimum zone solution immune evolutionary algorithm

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A novel immune evolutionary algorithm incorporating chaos optimization

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PATTERN RECOGNITION LETTERS 2006年第1期27卷 2-8页

作者： Guo, ZL Wang, S Zhuang, J Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Shan Xi Peoples R China

Making use of the ergodicity and internal randomness of chaos iterations, a novel immune evolutionary algorithm based on the chaos optimization algorithm and immune evolutionary algorithm is presented to improve the convergence performance of the immune evolutionary algorithm. The novel algorithm integrates advantages of the immune evolutionary algorithm and chaos optimization algorithm. Chaos variables are loaded into the variable colony of the immune algorithm in the immune evolutionary algorithm, tiny disturbance is introduced into the memory colony, and the disturbance amplitude is gradually adjusted based on the characteristic of chaos search. The experimental results indicate that the new immune evolutionary algorithm improves the convergence performance and search efficiency of the immune evolutionary algorithm. (c) 2005 Elsevier B.V. All rights reserved.

关键词： immune evolutionary algorithm chaos search chaos immune evolutionary algorithm

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Application of particle swarm optimisation based on immune evolutionary algorithm for optimal operation of cascade reservoirs

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2009年第3期8卷 233-239页

作者： Chang, Jian-xia Wan, Fang Huang, Qiang Yuan, Wen-lin Wang, Yi-min Xian Univ Technol Inst Water Resources & Hydroelect Engn Xian Shaanxi Peoples R China

In the operation of complex cascade reservoirs, it is often challenged by the curse of dimensionality and solutions can get trapped in local optimal. This paper proposes a particle swarm optimisation based on immune evolutionary algorithm to solve the problems. This new algorithm can overcome the shortcomings with regards to the dependence on initial population and local optimisation of particle swarm optimisation algorithms. The feasibility of the proposed algorithm is demonstrated through an example system and the results are compared with that of other algorithms. The results have shown that this new algorithm is feasible for the problems of complex non-linear systems with some restraint conditions.

关键词： cascade reservoirs optimal operation particle swarm optimisation PSO immune evolutionary algorithm IEA

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Integral transport scheduling in emergency relief based on an immune evolutionary algorithm

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INTERNATIONAL JOURNAL OF EMERGENCY MANAGEMENT 2014年第1期10卷 67-90页

作者： Hu, Zhi-Hua Sheng, Zhao-Han Shanghai Maritime Univ Logist Res Ctr Shanghai 200135 Peoples R China Tongji Univ Sch Econ & Management Shanghai 200092 Peoples R China

The integral transport scheduling problem in emergency relief is studied with the following features: simultaneous transport of people and resources, integral forward and reverse transport, matching between scattered vehicles and demands. The proposed solution has two stages: first, feasible paths are generated by an exact algorithm and an immune evolutionary algorithm, all based on an open path optimisation algorithm;secondly, an integer linear programming model is designed to choose a set of paths from the set of feasible paths. The approach can be extended to be a part of integral logistics systems with scattered transport services and demands.

关键词： emergency logistics immune evolutionary algorithm integral transport integer linear programming immune clonal selection algorithm

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Simulation and optimization of a production/inventory system based on immune evolutionary algorithm

Simulation and optimization of a production/inventory system...

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14th International Conference on Management Science and Engineering

作者： Wang Xu-ping Zhao Hai Shang Hong-yan Dalian Univ Technol Sch Management Dalian 116024 Peoples R China Changan Univ Sch Econ & Management Xian 710064 Shaanxi Peoples R China

ISBN: (纸本)9787560322780

This paper discusses the simulation and optimization of a production/inventory system, which is composed of one workshop and some warehouses. Accepting the material supplying from upriver suppliers, the workshop produces the products and make the supplying to their downriver manufactories. The warehouses are used to store the materials and the products. However, it is a big problem that how to allocate resources appropriately to satisfy the JIT mode of the core manufactories. Thus aiming at assistant machining and distribution, we construct a logistics simulation model for the system and design an immune evolutionary algorithm to resolve it. After simulation process of biologic immune evolutionary, we can achieve the optimal result for the key resources allocation problem, including inventory of both materials and productions, transport equipments.

关键词： immune evolutionary algorithm JIT production/inventory resources allocation simulation and optimization

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Application of a Novel Fuzzy Clustering Method Based on Chaos immune evolutionary algorithm for Edge Detection in Image Processing

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中国高等学校学术文摘·机械工程 2006年第1期1卷 85-89页

作者： WANG Sun-an GUO Zi-long Shool of Mechanical Engineering Xi'an Jiaotong UniversityXi'an710049China

A novel fuzzy clustering method based on chaos immune evolutionary algorithm(CIEFCM)is presented to solve fuzzy edge detection problems in image *** CIEFCM,a tiny disturbance is added to a filial generation group using a chaos variable and the disturbance amplitude is adjusted step by step,which greatly improves the colony diversity ofthe immune evolution algorithm(IEA).The experimental results show that the method not only can correctly detect the fuzzy edge and exiguous edge but can evidently improve the searching efficiency of fuzzy clustering algorithm based on IEA.

关键词： immune evolutionary algorithm chaos search fuzzy clustering algorithm edge detection

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MHC inspired immune evolutionary algorithm (MHCIEA) for numerical function optimization

MHC inspired immune evolutionary algorithm (MHCIEA) for nume...

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5th International Conference on Machine Learning and Cybernetics

作者： Hu, Min Wu, Geng-Feng Shanghai Univ Sydney Inst Language & Commerce Shanghai 200072 Peoples R China Shanghai Univ Sch Engn & Comp Sci Shanghai 200072 Peoples R China

ISBN: (纸本)1424400600

The protein major histocompatibility complex (MHC) plays a critical role in immune system with important biological functions. Inspired by the features of MHC, this paper presents an immune evolutionary algorithm (MHCIEA). This algorithm uses the metaphor of mapping "optimization problem solving" onto the model of immune system with MHC, which is defined as a sub-solution to accelerate optimization process. The four numerical function optimization problems are considered to verify the performance of the algorithm. In this paper we compare the performance of MHCIEA with DE, PSO and real-valued GA regarding their general applicability as numerical optimization techniques. The results from our study show that the performance of MHCIEA is better than others applied techniques.

关键词： major histocompatibility complex immune evolutionary algorithm function optimization

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Study on the Application of immune evolutionary algorithm

Study on the Application of Immune Evolutionary Algorithm

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Chen, Ming Xu, Changxin Hohai Univ Sch Business Nanjing 211100 Jiangsu Peoples R China Univ Florida Gulf Coast Res & Educ Ctr Wimauma FL 33598 USA

ISBN: (纸本)9781509056866

The immune evolutionary algorithm (IEA) is a new type of soft algorithm, it is based on the theory of biological immune system and evolved on the basis of evolutionary algorithm. This paper first introduces the theoretical basis of immune evolutionary algorithm, and obtains the general expression of immune evolutionary algorithm. On this basis, the application of immune evolutionary algorithm has been studied and applied to rural water pollution control. According to the convergence characteristics of the algorithm, the following conclusions are obtained: In the farmers participating model for water pollution control, the supervisory department needs to implement the reward and punishment system for the farmers' behavior. The behavior conducive to water environmental protection needs to be encouraged by the government, and the behavior of polluting the water environment needs to be punished. In this way, the correct behavior of the farmers can be inherited between generations effectively, and finally the problem of rural water pollution will be resolved in a limited time.

关键词： immune evolutionary algorithm Soft Computing Water pollution control

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