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2012 5th International Conference on Intelligent Computation technology and Automation, ICICTA 2012

作者： Gao, Luan Li, Feng-Gang Wang, Jian Liang, Yu Li, Yu Chinese Medicine Clinic Institute Anhui Chinese Medical College Hefei 230038 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei University of Technology Hefei 230009 China

ISBN: (纸本)9780769546377

The purpose of this paper is to probe into the rules of medicine compounding for stroke prevention treated by Xin'an physicians by data mining. The method is in two steps. First step is to build the database of the Xin'an physical stroke prevention. Second step is to use the method of association rules contained in professional data mining software and probe into the medicine rules for stroke prevention treated by Xin'an physicians. The result is that Chenpi, Fuling, Gancao, Luxiancao, Xiqiancao, Baijili, and Shinanye which are of the seven common Chinese medical compounding prescriptions can be used for Xin'an physicians' stroke prevention. The conclusion is that we should utilize the eliminating phlegm, calming wind and clearing the channels when Xin'an physicians treat stroke problem. © 2012 IEEE.

关键词： Association rules

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Modified Self-adaptive Immune Genetic Algorithm for optimization in the Combustion Side Reaction of p-Xylene Oxidation

Modified Self-adaptive Immune Genetic Algorithm for Optimiza...

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第23届过程控制会议

作者： Lili Tao Xiangdong Kong Weimin Zhong Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education E Automation Institute East China University of Science and Technology Shanghai 200237 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education E

In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution of non-linear optimization problems encountered in many engineering applications. In IGA, the mutation factor values are either fixed or change together according to a function of the individual’s current generation number during all the search process. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. A modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to strengthen the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method can quickly converge to the global optimum and overcome premature problem. Then, this algorithm is applied to optimize a feed forward neural network to measure the content of products in the combust ion side reaction of p-xylene oxidation, and satisfactory results are obtained.

关键词： Self-adaptive immune genetic algorithm Artificial neural network Measurement p-Xylene oxidation process

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Peak Traffc Forecasting Using Nonparametric Approaches

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Journal of Shanghai Jiaotong university(Science) 2012年第1期17卷 76-81页

作者：张扬王梦灵 Shanghai Municipal Transportation Information Center Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

States of traffic situations can be classified into peak and nonpeak periods. The complexity of peak traffic brings more difficulty to forecasting models. Travel time index （TTI） is a fundamental measure in transportation. How to master the characteristics and provide accurate real-time forecasts is essential to intelligent transportation systems （ITS）. Cooperating with state space approach, least squares support vector machines （LS- SVMs） are investigated to solve such a practical problem in this paper. To the best of our knowledge, it is the first time to apply the technique and analyze the forecast performance in the domain. For comparison purpose, other two nonparametric predictors are selected because of their effectiveness proved in past research. Having good generalization ability and guaranteeing global minima, LS-SVMs perform better than the others. Providing sufficient improvement in stability and robustness reveals that the approach is practically promising.

关键词： traffic forecasting peak traffic nonparametric techniques

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Modeling and simulation of VRP in wartime using NSGA II

Modeling and simulation of VRP in wartime using NSGA II

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Chinese control and Decision Conference, CCDC

作者： Jiangyun Li Xiaobo Jing Chaonan Tong Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing

Aiming at VRP in modern military logistics, this paper sets up the multi-objective VRP mathematical model of military logistics in wartime. This model is solved by NSGA II, and improves the dependence on the initial population and the deficiency in the practical application from NSGA II, and has improved the population initialization and intersection in NSGA II algorithm by the introduction of Greedy algorithm. The algorithm is realized by Matlab programming and applied by examples. After the simulation is improved, NSGA II is able to solve the multi-objective VRP of military logistics in wartime.

关键词： Vehicles Biological cells Convergence Logistics optimization Approximation algorithms Heuristic algorithms

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Novel numerical and computational strategies based on differential evolutionary strategy

Novel numerical and computational strategies based on differ...

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International Conference on Computer Science and Information processing (CSIP)

作者： Chang-bin Hu Chao-nan Tong Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing China

Evolutionary algorithm for complex process optimization based on differential evolutionary strategy (DEACOP) that has a similar framework structure of scatter search is proposed. This algorithm not only retained the original algorithm's advantages, but also made improvements in three areas: above all, in order to maintain the diversity of the population, the set RefSet2 is selected from those individuals generated by Latin hypercube uniform sampling, according to minimum Euclidean distance to set RefSet1 is the highest. Furthermore, differential mutation with scaling factor and differential crossover strategy is introduced to replace linear combination method of evolutionary algorithm for complex-process optimization (EACOP). Finally, local search method is adopted to improve the trial solution generated at “go-beyond strategy” stages. The results show that the algorithm is able to use fewer adjustable parameters to complete to search and get feasible mathematical solution.

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Weighted least square support vector machine integrated with parameter optimization and its application in chemical process

Weighted least square support vector machine integrated with...

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International Conference on Natural Computation (ICNC)

作者： Wen-Tong Cui Xue-Feng Yan Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China

Considering that outliers can disrupt the correlation structure of least square support vector machine (LS-SVM), and that the parameters of LS-SVM play an important role in the performance, a novel weighted least square support vector machine integrated with parameter optimization is proposed to obtain the optimal parameters and to eliminate the effect of outliers. Several LS-SVM variants are applied in simulation experimentation and chemical process respectively to demonstrate the satisfactory performance of the proposed method.

关键词： optimization Training Support vector machines Oxidation Adaptation models Mathematical model educational institutions

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Robust control with state decoupler for combined shape and gauge system in rolling process

Robust control with state decoupler for combined shape and g...

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International Conference on Automatic control and Artificial Intelligence, ACAI 2012

作者： Jing, Peng Tong, Chaonan Hu, Changjun School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China Key Laboratory of Advanced Control for Iron and Steel Process Ministry of Education Beijing 100083 China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing 100083 China

ISBN: (纸本)9781849195379

Considering the dynamic characteristics of the deformation zone, a new model of combined shape and thickness system in rolling process was proposed, regarding bending force and gauge as the main factors. Taking various kinds of secondary causes, perturbation and disturbance into consideration, robust control methods were brought in. A mathematic model was proposed based on field data, then static decoupler and robust controller were developed with benefit of robust control toolbox in MATLAB. Simulation results show the effectiveness of tracing and decoupling and robustness for parameter perturbation.

关键词： Robust control

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Research on a novel MPPT control method for variable-speed wind power systems

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Research Journal of Applied Sciences, Engineering and technology 2012年第16期4卷 2712-2715页

作者： Li, T. Shen, Y.X. Ji, Z.C. Jiangnan University China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Wuxi 214122 China

In this study, we build up the double-dynamic models of variable speed wind power systems and design a new type Maximum Power Point Tracking (MPPT) PI-NN controller to improve the precision of the Tip Speed Ratio (TSR) tracking based on the models. Moreover, the effect of the PI-NN controller and the PILQG controller are compared based on Matlab/simulation and the results show that precision of optimal TSR tracking using PI-NN controller is higher than that using the PI-LQG controller, output value of the TSR is optimized, thus more wind energy is captured. © Maxwell Scientific Organization, 2012.

关键词： MATLAB

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The Utility Frequent Pattern Mining Based on Slide Window in Data Stream

The Utility Frequent Pattern Mining Based on Slide Window in...

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International Conference on Intelligent Computation technology and Automation, ICICTA

作者： Feng-gang Li Ying-jia Sun Zhi-wei Ni Yu Liang Xue-ming Mao Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei University of Technology Hefei China

In traditional study of mining data stream, each item in the data stream is of equal importance. However, in practice, each item has a different significance, which is known as utility. This paper combines frequent mining item sets with utility and proposes an efficient algorithm for utility frequent pattern mining (UFPM). It combines bitmap with tree structure that can store and update the pattern of data stream quickly and completely by scanning only once. The algorithm generated by lexicographic order, proposes a novel tree U-tree and makes convenience for pattern updating and user reading. With a pattern growth approach in mining, the algorithm can effectively avoid the problem of a mass candidacy generation by level-wise searching. The experiments results show that our algorithm which is in high efficiency and good scalability outperforms the existing analogous algorithm.

关键词： Data mining Itemsets Algorithm design and analysis Scalability Focusing Automation

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Data-driven Pattern Moving and Generalized Predictive control

Data-driven Pattern Moving and Generalized Predictive Contro...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Zhengguang Xu Jinxia Wu Department of Control Science and Engineering University of Science and Technology Beijing Key Laboratory of Advanced Control for Iron and Steel Process (Ministry of Education)

ISBN: (纸本)9781467317139

In this paper, a generalized predictive control method based on pattern recognition technique is proposed for a class of uncertain complex systems with statistical characteristics. The system dynamics is described by working condition pattern moving rather than output equation or state space model. First, working condition data are collected around the nominal operating condition to construct "pattern moving space". The space can be updated on-line. Then "pattern class variable" is defined in this space and the prediction model based on this new variable is also constructed. At last, the generalized predictive control method is also given. This method can identify the optimal controller's parameters directly by the prediction equations and input/output data. And it can avoid many intermediate operations for online solving Diophantine equations. Some simulations based on the actual run status data collected from sintering process of Anyang iron and steel plant are given to verify the effectiveness.

关键词： Pattern moving Pattern moving space Pattern class variable Generalized predictive control generalized predictive control Moving Iron and steel plants PREDICTION EQUATIONS System dynamics Prediction models control Methods data driven

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