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第23届过程控制会议

作者： Xingdi Yan Wen Yang Hehe Ma Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education

The ammonia synthesis section is the core during the whole ammonia synthesis production. The ammonia concentration at the ammonia converter outlet is a significant process variable, which reflects the production efficiency directly. However, it is hard to be measured reliably online in real applications. In this paper, a soft sensor based on BP neural network (BPNN) is applied to estimate the ammonia concentration. A modified group search optimization with nearest neighborhood (GSO-NH) is proposed to optimize the weights and thresholds of BPNN. GSO-NH is integrated with BPNN to build a soft sensor model. Finally, the soft sensor model based on BPNN and GSO-NH (GSO-NH-NN) is used to infer the outlet ammonia concentration in a real-world application. Three other modeling methods are applied to compare with GSO-NH-NN. The results show that the soft sensor based on GSO-NH-NN has a good prediction performance with high accuracy. Moreover, the GSO-NH-NN also provides good generalization ability to other modeling problems in ammonia synthesis production.

关键词： Ammonia synthesis Ammonia concentration Soft sensor Group search optimization.

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An Empirical Study on Personality Characteristics of College Volunteers: Based on the Collected Data from Shanghai Expo

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Procedia - Social and Behavioral Sciences 2013年 83卷 969-974页

作者： Ya-di Gu Dong-xiao Gu Qing Wei Shen Pan Wen-en Chen Yi Ge Students’ Affairs Division at University of Shanghai for Science and Technology Shanghai200093 P.R. CHINA School of Management at Hefei University of Technology Hefei Anhui230009 P.R. CHINA School of Foreign Studies at Hefei University of Technology Hefei Anhui230009 P.R. CHINA Engineering Research Center of Intelligent Decision-Making and Information System Technology of Ministry of Education of China Hefei Anhui 230009 P.R. CHINA Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education of China Hefei Anhui 230009 P.R. CHINA Department of Electronic Information Technology at Tianjin Normal University Tianjin 300387 P.R. CHINA

Objective : This study is to investigate the personality characteristics of student volunteers, which would provide a reference to select and train qualified volunteers for the future. Methods : 233 student volunteers and 236 non-volunteers are selected for our study. Based on the data of 16PF personality exported from the database, statistical software SPSS15.0 is used to conduct data analysis. Result : Volunteers and non-volunteers have significant differences of personality: the 16 basic personality factors, the gregariousness, excitement, daring and independence scores are significantly different; in the other eight binary factors, emotional and serene in the alert type, introverted and extroverted type, timid and bold type factors have significantly different scores. Male and female volunteers have significant personality difference in some respects. Conclusion : College student volunteers have obvious personality traits of extroversion, optimism, cheerfulness, enthusiasm, self-confidence etc. In addition, male and female volunteers have gender differences in personality characteristics in some aspects.

关键词： College students Volunteers Personality traits Shanghai Expo Selection

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Parameter estimation of industrial PET reactor using multi-objective kernel density estimation of distribution algorithm

Parameter estimation of industrial PET reactor using multi-o...

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作者： Luo, Na Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai 200237 China State-Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai 200237 China

With a multitude of reaction pathways, poly (ethylene-terephthalate) (PET) polymerization of industrial practice is complex, and the quality of PET is normally described in terms of several experimentally measured indices. In this paper, parameters estimation of industrial PET reactors is presented as a multi-objective problem to make the mathematic model consistent with the actual industrial process. Considering the interrelation among parameters and the failure of general optimization algorithms, a new multi-objective estimation of distribution algorithm is proposed. Kernel density estimation is used to make the new population more suitable for real-life problems instead of Gaussian model during the evolution of the algorithm. Strategies including selection of kernel width, sampling method and Pareto domination selection are used to explore and exploit the search space more efficiently. With industrial operating data identified in steady state and eliminated from gross error, kinetic parameters are estimated by minimizing carboxyl end group concentration and degree of polymerization simultaneously using the proposed algorithm. The simulation results show that the model with estimated parameters has better predictive performance compared with the experimental parameters. Copyright © 2011 Curtin University of technology and John Wiley & Sons, Ltd. Copyright © 2011 Curtin University of technology and John Wiley & Sons, Ltd.

关键词： Parameter estimation

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Short-term power load forecasting based on self-adapting PSO-BP neural network model

Short-term power load forecasting based on self-adapting PSO...

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4th International Conference on Computational and Information Sciences, ICCIS 2012

作者： He, Yaoyao Xu, Qifa School of Management Hefei University of Technology Hefei 230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei 230009 China

ISBN: (纸本)9780769547893

To resolve the problem of short-term power load forecasting, we propose a self-adapting particle swarm optimization (PSO) algorithm to optimize the error back propagation (BP) neural network model. The proposed model is called PSO-BP model which employs PSO to adjust control parameters of BP neural network. In order to verify the performance of PSO-BP, the practical datum of a city in China are selected in the experiments. Simulation results show that our approach outperforms simple BP neural network. © 2012 IEEE.

关键词： Neural network models

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Chaotic particle swarm optimization algorithm with harmony search for industrial applications

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Qinghua Daxue Xuebao/Journal of Tsinghua University 2012年第3期52卷 325-330页

作者： Du, Wenli Zhang, Hailong Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China

Particle swarm optimization methods for optimization problems tend to search premature solutions. This paper presents an improved particle swarm optimization algorithm merging chaotic and harmony searches. The chaos particle swarm optimization method is stable, robust and adaptable. The harmony search algorithm is a meta heuristic algorithm for simulating band tuning to obtain an optimal harmonized process with a global search. Results for four standard test functions show that this chaos particle swarm optimization algorithm with a harmony search (CPSO-HS) can jump out of local optimums with fast convergence and good stability. This algorithm has been successfully applied to parameter estimates for a heavy oil thermal cracking model.

关键词： Particle swarm optimization (PSO)

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Robot visual servo control based on fuzzy adaptive PID

Robot visual servo control based on fuzzy adaptive PID

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2012 International Conference on Systems and Informatics, ICSAI 2012

作者： Dong, Jie Hu, Yu Peng, Kaixiang School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China Key Laboratory of Advanced Control of Iron and Steel Process Ministry of Education Beijing 100083 China

ISBN: (纸本)9781467301992

Visual servo control is one of the central issues in the research field of intelligent robot. In order to obtain more effective information from the environment, visual sensor is used in robot control. This paper sets up the suitable model of the robot, with mathematical formulas derivation of visual servo control. Fuzzy adaptive PID is introduced to IBVS, in order to get a better performance. The simulation result shows that control strategy is effective. © 2012 IEEE.

关键词： Intelligent robots

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Regularized CSP with Fisher's criterion to improve classification of single-trial ERPs for BCI

Regularized CSP with Fisher's criterion to improve classific...

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2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012

作者： Zhang, Yu Zhao, Qibin Zhou, Guoxu Wang, Xingyu Cichocki, Andrzej Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China Laboratory for Advanced Brain Signal Processing Brain Science Institute RIKEN Wako-shi Saitama 351-0198 Japan

ISBN: (纸本)9781467300223

A brain-computer interface (BCI) based on the combination of oddball paradigm and face perception has been introduced. Such BCI mainly exploits three event-related potential (ERP) components, namely vertex positive potential (VPP), N170 and P300 instead of only P300. With different temporal and spatial distributions of the three ERP components, a regularized common spatial pattern (CSP) with Fisher's criterion (FC), named FCCSP, is proposed to extract the most discriminative features for single trial classification of ERP components. With linear discriminant analysis (LDA) classifier, the proposed FCCSP spatial filtering method yields an average classification accuracy of 95.4% on seven healthy subjects for single-trial ERP components, which outperforms no spatial filtering, the CSP and the FC. © 2012 IEEE.

关键词： Brain computer interface

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Gaussian process assisted coevolutionary estimation of distribution algorithm for computationally expensive problems

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Journal of Central South University 2012年第2期19卷 443-452页

作者： Luo, Na Qian, Feng Zhao, Liang Zhong, Wei-min Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China

In order to reduce the computation of complex problems, a new surrogate-assisted estimation of distribution algorithm with Gaussian process was proposed. Coevolution was used in dual populations which evolved in parallel. The search space was projected into multiple subspaces and searched by sub-populations. Also, the whole space was exploited by the other population which exchanges information with the sub-populations. In order to make the evolutionary course efficient, multivariate Gaussian model and Gaussian mixture model were used in both populations separately to estimate the distribution of individuals and reproduce new generations. For the surrogate model, Gaussian process was combined with the algorithm which predicted variance of the predictions. The results on six benchmark functions show that the new algorithm performs better than other surrogate-model based algorithms and the computation complexity is only 10% of the original estimation of distribution algorithm.

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Regression Analysis Based on Wavelet Kernel for optimization of Chemical process

Regression Analysis Based on Wavelet Kernel for Optimization...

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第23届过程控制会议

作者： ZHENG Rongjian ZHOU Lincheng PAN Feng Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan Univ Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan Univ

Some limitations exist in modeling of chemical process by SVM (support vector machine), such as unsatisfactory modeling accuracy, generalization ability and difficult kernel parameter selection process. To overcome these difficulties, combining wavelet SVM (W-SVM) with Morlet wavelet kernel was described in this article, reproducing kernel space and the wavelet analysis, and the proof to supporting Morlet wavelet kernel function was also given. To show the wavelet kernel function’s better generalization capability and accuracy, the proposed method was applied to establish a soft-sensor model for average molecular weight in polyacrylonitrile (PAN) production process. The results of real data simulation show that this method is effective

关键词： Chemical process Wavelet kernel Wavelet support vector machine

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An investigation about large-scale IoT situation assessment

An investigation about large-scale IoT situation assessment

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2012 International Conference on Computer Distributed control and Intelligent Environmental Monitoring, CDCIEM 2012

作者： Li, Zhi-Hua Gu, Wen-Qiang Zhang, Hai-Tao Key Laboratory of Advanced Process Control for Light Industry Ministry of Education School of IoT Engineering JiangNan University WuXi China Engineering School of IoT JiangNan University WuXi China

ISBN: (纸本)9780769546391

This paper studied the problems of parameter system construction for large-scale Internet of Thing situation assessment. It also states the research of situational awareness and assessment of IP network briefly, the situation assessment differences between Internet of Thing and IP network are dicussed, for some especial aspects and the significance about large-scale Internet of Thing situation assessment are presented, and several serious problems faced the current establishment of situation evaluation index system firstly are given .Finally, an indicator of the situation assessment model and discussion on how to generate all kinds of parameters are given out as a example, and the above research works makes a foundation about the Internet of Things' situation awareness and situation assessment. © 2012 IEEE.

关键词： Internet of things

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