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5th International Symposium on Advanced Optical Manufacturing and Testing Technologies - Design, Manufacturing, and Testing of Micro- and Nano-Optical Devices and Systems

作者： Xiong Yu Hong Xu Shao Ping Lv Xiao Lan Jiang Shun Liang Ye Fa Mao Zhou Shi Lin Nanchang Univ Dept Comp Sci & Technol Nanchang 330031 Peoples R China Nanchang Univ Dept Chem Nanchang 330031 Jiangxi Peoples R China

ISBN: (纸本)9780819480873

In the analysis of optical spectrum, it is an effective means to construct the model of analysis and calibration by selecting proper wavelength data points, which can overcome the influences negatively produced by such factors as instruments, personnel and impurity in the measure of substances, as well as to improve the analytical precision of micro spectrometer system. This is particularly the case with multiple components. The reciprocal effect between multiple components appears to be more necessary than ever in involving in the selecting the wavelength data points in the construction of the model. The paper discusses the application of chaos optimization algorithm in the spectral wavelength selection on the basis of an overview of the basic theory of chaos optimization algorithm and brings forward a method of wavelength selection based on parallel binary chaos optimization. In the end, this method is illustrated with examples by adopting the computer simulation.

关键词： spectral analysis chaos optimization algorithm wavelength selection

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OPTIMAL DESIGN OF SOLAR PHOTOVOLTAIC POWER GENERATION SYSTEM

LIGHT & ENGINEERING

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LIGHT & ENGINEERING 2016年第3期24卷 100-104页

作者： Xu, Zhiming Jiang, Tieliu Li, Yong Northeast Dianli Univ Coll Energy & Power Engn Chuanying Jilin Peoples R China North China Elect Power Univ Coll Energy & Mech Engn Beijing Peoples R China

In this paper, solar concentrator mass and wind factor are used as objective functions. The coupling effect of function factors is combined with the adaptive chaos optimization algorithm for multi-objective optimization. The multi-objective function of a dish solar concentrator is obtained using weighting factors. Flow field and quality are then compared before and after the optimization of the dish solar concentrator. The optimized dish solar concentrator exhibits reduced quality but improved flow, stress, and pressure fields at varying degrees.

关键词： dish solar concentrator multidisciplinary design chaos optimization algorithm

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Prediction of film-cooling effectiveness based on support vector machine

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APPLIED THERMAL ENGINEERING 2015年 84卷 82-93页

作者： Wang, Chunhua Zhang, Jingzhou Zhou, Junhui Alting, Siti Aisyah Nanjing Univ Aeronaut & Astronaut Jiangsu Prov Key Lab Aerosp Power Syst Nanjing 210016 Peoples R China Collaborat Innovat Ctr Adv Aeroengine Beijing 100191 Peoples R China

Least square support vector machine (LS-SVM) model is applied to predict the lateral averaged adiabatic film-cooling effectiveness on a flat plate surface downstream of a row of cylindrical holes. The dataset used to develop and validate the presented model is obtained from the public literature. The input parameters of LS-SVM include dimensionless downstream distance, pitch-to-diameter ratio, hole incline angle, hole compound angle, length-to-diameter ratio, blowing ratio, density ratio, and mainstream turbulence intensity. The predicted results are found to be in good agreement with the experimental results (the mean relative error is about 17.5%). The comparison between LS-SVM model and existing semi-empirical correlations is carried out, and the prediction performance of LS-SVM model is much better. Moreover, the effects of LS-SVM input parameters on film-cooling effectiveness are discussed in detail. LS-SVM is a promising model to predict the film-cooling effectiveness. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Turbine Film-cooling effectiveness Support vector machine chaos optimization algorithm

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Chaotic Newton-Raphson optimization Based Predictive Control for Permanent Magnet Synchronous Motor Systems with Long-Delay

Chaotic Newton-Raphson Optimization Based Predictive Control...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Wu, Bing-Fei Lin, Chun-Hsien Natl Chiao Tung Univ Dept Elect & Comp Engn Hsinchu Taiwan

ISBN: (纸本)9781479986965

A Tent-map chaotic Newton-Raphson optimization based neural network predictive control (TCNR-NPC) is developed to apply to the long-delay permanent magnet synchronous motor (PMSM) system in this paper. Due to a nonlinear model utilized in the predictive controller, nonlinear optimization methods turn into an important issue. To overcome the shortcoming of the conventional nonlinear programming on the initial condition sensitivity and maintain the accuracy of optimal solution, chaos optimization algorithm (COA) and Newton-Raphson (NR) are combined. With the comparison of COA and NR based optimization methods, our approach, the Tent-map chaotic Newton-Raphson (TCNR) optimization, is easier to reach the global optimum;thus, it would be employed in neural network predictive control. It is found that TCNR-NPC has a better performance than those of GPC, modified GPC, adaptive extended PSO based NPC, and PSO based PI controllers in real experiments.

关键词： predictive control neural network Newton-Raphson chaos optimization algorithm long-delay plant

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Hybrid chaos optimization and affine scaling search algorithm for solving linear programming problems

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APPLIED SOFT COMPUTING 2013年第5期13卷 2703-2710页

作者： Bouras, Abdelghani Syam, Wahyudin P. King Saud Univ Dept Ind Engn Coll Engn Riyadh 11421 Saudi Arabia

In this study, we addressed Single Objective Linear Programming (SOLP). This article proposed a new combination of chaos optimization algorithm (COA) with Affine Scaling Search (AFS) to be used as a Hybrid COA and AFS algorithm (chaos AFS) for solving SOLP. The potential of COA as an emerging optimization algorithm to improve efficiency and effectiveness of AFS is investigated. chaos AFS method is so-called numerical search algorithm that searches through the domain of decision variables of SOLP to obtain final feasible solution. An initial solution point, obtained from COA, will be used as starting solution point in AFS algorithm to improve the performance of AFS algorithm. The result shows that Hybrid COA and AFS for solving SOLP problems significantly improves the results of objective value compared to pure AFS and reduces the number of iteration steps compared to simplex and pure AFS. (C) 2012 Elsevier B. V. All rights reserved.

关键词： chaos optimization algorithm Interior point method Affine scaling Single objective linear programming Linear programming

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Study on Minimum Zone Evaluation of Flatness Errors Based on a Hybrid chaos optimization algorithm

Study on Minimum Zone Evaluation of Flatness Errors Based on...

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5th International Conference on Intelligent Computing

作者： Zhang, Ke Shanghai Inst Technol Sch Mech & Automat Engn Shanghai 200235 Peoples R China

ISBN: (纸本)9783642040696

In this paper, according to characteristics of flatness error evaluation, a hybrid evaluation method to evaluate the minimum zone error is provided. The evolutional optimum model and the calculation process are introduced in detail. The hybrid optimization algorithm is based upon chaos optimization algorithm (COA) and Powell search. Compared with conventional optimum methods such as simplex search and Powell method, it can find the global optimal solution, and the precision of calculating result is very good. Moreover, the efficiency of COA is much higher than some stochastic algorithms such as simulated anneal algorithm and genetic algorithm (GA) when COA is used to a kind of continuous problems. The hybrid optimization algorithm can improve the efficiency of searching in the whole field by gradually shrinking the area of optimization variable. Finally, the control experiment results evaluated by different method such as the least square, simplex search, Powell optimum methods and GA, indicate that the proposed method does provide better accuracy on flatness error evaluation, and it has fast convergent speed as well as using computer expediently and popularizing application easily.

关键词： Flatness Evaluation chaos optimization algorithm Minimum Zone

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Image Segmentation Based on Two-Dimensional Inter-Class Cross Entropy and chaos optimization algorithm

Image Segmentation Based on Two-Dimensional Inter-Class Cros...

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International Forum on Information Technology and Applications (IFITA 2009)

作者： Zhang Xinming Zhang Huiyun Henan Normal Univ Coll Comp & Informat Technol Xinxiang 453007 Peoples R China

ISBN: (纸本)9780769536002

In this paper, a thresholding technique based on two-dimensional inter-class cross entropy and chaos optimization algorithm (COA) is presented. Firstly, adopt the cross entropy approach to describe the difference in pixel information between the object and the background in a two-dimensional histogram and to use maximum inter-class separation degree. Then apply improved COA to get the threshold value, which can get global solution with low computational load. Experimental results show the proposed approach is effective and gets competitive visual effects.

关键词： image segmentation two-dimensional cross entropy chaos optimization algorithm thresholding

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Calculation of Jiles-Atherton hysteresis model's parameters using mix of chaos optimization algorithm and simulated annealing algorithm

Calculation of Jiles-Atherton hysteresis model's parameters ...

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2009 International Conference on Microwave Technology and Computational Electromagnetics (ICMTCE 2009)

作者： Huiqi Li Qingfeng Li Junjie Zhang Electrical Engineering Department North China Electric Power University Baoding China Baoding Tianwei Group Company Limited Baoding China

ISBN: (纸本)9781617382567

A mix of chaos optimization method and simulated annealing method to calculate the Jiles-Atherton (JA) model's parameters is proposed in this paper. The new method costs less time in calculating the JA model's parameters. During the search performance, the local extreme value can be avoided effectively. A modified JA model is applied in this paper, choose the magnetic flux as the confident variable. The model can be directly used in time-domain finite-element calculations applied to the magnetic vector potential formulation. The curve which calculated using the obtained parameters is well agreed to the measured curve by experiment.

关键词： chaos optimization algorithm Jiles-Atherton model Simulated annealing algorithm

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Parallel chaos Search Based Incremental Extreme Learning Machine

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NEURAL PROCESSING LETTERS 2013年第3期37卷 277-301页

作者： Yang, Yimin Wang, Yaonan Yuan, Xiaofang Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China

Recently, a simple and efficient learning steps referred to as extreme learning machine (ELM), was proposed by Huang et al. , which has shown that compared to some conventional methods, the training time of neural networks can be reduced even by thousands of times. However, recent study showed that some of random hidden nodes may paly a very minion role in the network output and thus eventually increase the network complexity. This paper proposes a parallel chaos search based incremental extreme learning machine (PC-ELM) with additional steps to obtain a more compact network architecture. At each learning step, optimal parameters of hidden node that are selected by parallel chaos optimization algorithm will be added to exist network in order to minimize the residual error between target function and network output. The optimization method is proposed parallel chaos optimization method. We prove the convergence of PC-ELM both in increased network architecture and fixed network architecture. Then we apply this approach to several regression and classification problems. Experiment of 19 benchmark testing data sets are used to test the performance of PC-ELM. Simulation results demonstrate that the proposed method provides better generalization performance and more compact network architecture.

关键词： Extreme learning machine Convergence rate chaos optimization algorithm Random hidden nodes

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A new adaptive mutative scale chaos optimization algorithm and its application

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控制理论与应用（英文版） 2008年第2期6卷 141-145页

作者： Jiaqiang E Chunhua WANG Yaonan WANG Jinke GONG College of Mechanical and Automotive Engineering Hunan University Changsha Hunan 410082 China College of Electrical and Informational Engineering Hunan University Changsha Hunan 410082 China

Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin（2/x） with infinite collapses within the finite region[-1, 1] to some representative iterative chaotic maps with finite collapses （e.g., Logistic map, Tent map, and Chebyshev map）, a new adaptive mutative scale chaos optimization algorithm （AMSCOA） is proposed by using the chaos model x = sin（2/x）. In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken： 1） the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2） the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.

关键词： Adaptive Mutative scale chaos optimization algorithm One-dimensional iterative chaotic self-map

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