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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yun, Zuo Zhihao, Ling Luming, Liu School of Information Science and Engineering East China University of Science and Technology Shanghai China Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education Shanghai China

ISBN: (纸本)9781424437092

The WirelessHART network is an emerging technology which aims at application in industry. The control network in industry always consists of many end devices and the environment is hash, so the network management of WirelessHART is very critical. This paper first introduced the wireless sensor network management mode and the critical techniques in WirelessHART network. Following that, network management in WirelessHART was analyzed and the solutions of some challenges were proposed. Finally it gave the expectation of WirelessHART technology. © 2010 IEEE.

关键词： Network management

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A new particle swarm optimization and the application in the soft sensor modeling

A new particle swarm optimization and the application in the...

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2010 8th IEEE International Conference on control and Automation, ICCA 2010

作者： Dang, Mingmei Wang, Zhenlei Qian, Feng East China University of Science and Technology China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (纸本)9781424451951

Aiming at the disadvantages of the standard Particle Swarm optimization (PSO), a new particle swarm optimization algorithm based on dual mutation(DDPSO) is proposed. By comparing and analyzing the results of several Benchmark functions, the excellent performance of PSO is proved. The improved PSO is applied to optimize the structure and parameters in artificial neural network(ANN). The availability of algorithm optimizing neural network is proved by applying ANN in soft sensor modeling of propylene concentration measurement. © 2010 IEEE.

关键词： Neural networks

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An immune inspired approach to 802.11 Wireless LANs coverage optimization

An immune inspired approach to 802.11 Wireless LANs coverage...

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2010 International Conference on Information, Networking and Automation, ICINA 2010

作者： Zhou, Xuan Qi, Rongbin Li, Qian Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China School of Electronics and Information Tongji University Shanghai China

ISBN: (纸本)9781424481057

Coverage optimization is a critical issue in 802.11 Wireless LANs planning problems. In this paper an immune network algorithm named opt-aiNet is studied in order to automatize the planning process by optimizing the BS's (Base Station) sites. Compared the results of opt-aiNet and genetic algorithms(GA) which have been used in radio coverage optimization before, we found that opt-aiNet could find the optimal solution all times while GA falling into local optimum solution sometimes, and opt-aiNet converged more quickly than GA in most cases. Experimental results show that optaiNet is an effective way to optimize the 802.11 Wireless LANs planning problems. © 2010 IEEE.

关键词： Genetic algorithms

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A novel hybrid particle swarm optimization algorithm merging crossover mutation and chaos

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Huagong Xuebao/CIESC Journal 2010年第11期61卷 2861-2867页

作者： Liu, Zhao Qi, Rongbin Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

To solve the premature convergence problem of particle swarm optimization(PSO) in dealing with complex high dimensional function optimization, a novel hybrid particle swarm optimization algorithm merging crossover mutation and chaos(CMCPSO) was proposed. The main approaches included using chaos strategy to initiate positions and velocities of all particles in the design space, introducing crossover operation in each iteration to increase the diversity of particles, breaching the restrictions of local optimization points with a new chaotic disturbance mechanism and mutation operation during the later computation period. Four standard test functions were selected to have a simulation study on the proposed algorithm. The results showed that CMCPSO had a fast convergence rate and effective global optimization ability. © All Rights Reserved.

关键词： Merging

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Differential evolution inspired clone immune multi-objective optimization algorithm

Differential evolution inspired clone immune multi-objective...

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International Conference on Electrical and control Engineering, ICECE 2010

作者： Xu, Bin Wang, Honggang Qi, Rongbin Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education School of Information Science and Technology East China University of Science and Technology NO 130 Meilong Road 200237 Shanghai China

ISBN: (纸本)9780769540313

This paper proposes a novel multi-objective optimization algorithm: differential evolution inspired clone immune multi-objective optimization algorithm (DECIMO). The novel algorithm uses a space-filling experimental design named symmetric Latin hypercube design (SLHD) to initialize the population which can obviously improve the uniformity of the individual distribution. A permutation of population individual indexes is generated and then a neighborhood for each population individual is defined according to the permutation. A differential evolution inspired neighborhood recombination operator, which based on the neighbors of each population member, is proposed to balance the exploration and exploitation abilities of the algorithm with no compromise of efficiency. The DE inspired operator is then invoked into the clone immune algorithm (CIA) to solve multi-objective problems (MOPs). We compare the proposed algorithm with NSGA2 and SPEA2 by executing it to 5 famous test functions. The results show that the proposed algorithm can fast converge to the global Pareto front and also can sustain a very uniform distribution. It is a potential algorithm for solving MOPs. © 2010 IEEE.

关键词： Multiobjective optimization

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Soft-sensing of turbine steam flow based on CQGAPSO

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Huagong Xuebao/CIESC Journal 2010年第11期61卷 2855-2860页

作者： Tang, Qifeng Zhao, Liang Qi, Rongbin Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

Turbine steam flow is an important parameter for analyzing turbine operating efficiency. In order to solve such problems as lack of detection information, poor reliability of traditional measurement method, high cost and difficult installation of non-contact measurement method etc., a soft-sensing model based on the cooperative quantum genetic algorithm particle swarm optimization(CQGAPSO) and a well-defined part-connected neural network(NN) was proposed. It could eliminate some adverse effects of approximation ability caused by redundant structure of NN. The amplitude-based coding method and cooperation mechanism improved the learning efficiency, approximation precision and generalization of NN. The soft-sensing experimental results of turbine steam flow showed that the soft-sensing model of turbine steam flow could obtain higher prediction accuracy and greater robustness than the all-connection NN and other models. © All Rights Reserved.

关键词： Steam turbines

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Support vector regression based on multi-scale wavelet kernel for propylene concentration estimation and application

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Huagong Xuebao/CIESC Journal 2010年第6期61卷 1486-1494页

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

Support vector regression based on multi-scale wavelet kernel has strong robustness and good generalization ability, but it is critical for it to choose appropriate model parameters. Obviously, the multi-scale kernel method has more difficulty in model selection than the single kernel approach. This paper proposed an approach about how to develop support vector regression based on multi-scale wavelet kernel. It applied quantum clustering to data partition in order to determine the scale parameter of the multi-scale kernel, resorted to the support vector data description algorithm to calculate the kernel width of the corresponding data points, and then used cultural algorithms to optimize the kernel width and the remaining parameters. The results showed that the multi-scale kernel method outperformed the single wavelet approach and the Gaussian method. The experiments about three regression data sets-Boston housing, Bodyfat and Santa demonstrated that in contrast with the Gaussian approach, the present multi-scale wavelet support vector regression made the mean squared error of test sets decrease by 6.8%, 62.0% and 91.3%, respectively. Meanwhile, the proposed approach exhibited good generalization ability for propylene concentration estimation in the bottom byproduct of propylene fractionation tower. It not only enabled the model output of training set for propylene concentration to show little difference with the actual output, but also made the relative error of test set down to 0.211. Compared with other methods, it had the minimal prediction error. © All Rights Reserved.

关键词： Errors

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Dynamic soft sensor modeling based on time series error compensation

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Huagong Xuebao/CIESC Journal 2010年第2期61卷 439-443页

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

Because static soft sensor modeling can not reflect the dynamic information of industrial processes, which lead to worse estimation precision and robustness. A dynamic soft sensor modeling based on least square vector machine(LS-SVM) and ARMA time series prediction modeling was presented. A static soft sensor model based on LS-SVM was established firstly, and then dynamic correction in the static model was made by using the dynamic estimation of prediction error in ARMA to improve the dynamic response characteristics. Finally, the proposed LSSVM-ARMA was used to predict the concentration of ethane in ethylene distillation. Simulation indicated that this method featured good approximation and good generalization ability as compared with LSSVM, and could be used in soft sensor. © All Rights Reserved.

关键词： Time series

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Design and implementation of automatic arithmetic generation system based on remote speech recognition

Design and implementation of automatic arithmetic generation...

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IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS)

作者： Yin, Xiangyuan Ling, Zhihao Guan, Liping Zhang, Luping Information Science and Engineering School of East China University of Science and Technology Shanghai China Zhejiang Wanli University Ningbo China Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education Shanghai China

ISBN: (纸本)9781424465835

In this paper, an automatic arithmetic generation system which can be remotely controlled by a particular speaker is designed and implemented to improve children's interest in learning math and facilitate parents to supervise children. The system is composed of the sender subsystem and the receiver subsystem. The sender subsystem is responsible to recognize speech and send the control command, and then the receiver subsystem can receive the command and execute corresponding program. The hardware system is made up of the SPCE061A microchip, keyboard, NRF2401 and LCD SPLC501 etc. The software system mainly achieves the following functions: recognition of speech, the control of NRF2401, random generation of arithmetic test samples, adjustment of different level, and supply of the correct answer. Finally, the system is experimented in some children. The result of experiment shows the system can greatly improve children's interest in learning math. ©2010 IEEE.

关键词： Speech recognition

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Differential Evolution Inspired Clone Immune Multi-objective optimization Algorithm

Differential Evolution Inspired Clone Immune Multi-objective...

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International Conference on Electrical and control Engineering (ICECE)

作者： Xu Bin Wang Honggang Qi Rongbin Qian Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai China Key Laboratory of Advanced Control East China University of Science and Technology Shanghai China

关键词： Cloning Algorithm design and analysis optimization Evolutionary computation Erbium Hypercubes Measurement

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