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2009中国控制与决策会议

作者： Liansheng Liu~1,Jianfang Zhang~(1,2) 1.Basic Experiment Center,Civil Aviation University of China,Tianjin 300300 2.Engineering Technique Training Center,Civil Aviation University of China,Tianjin 300300

Because of the limitation of the expert system which is based on the rule,this text proposes introducing the neural network technology into the fault diagnosis *** we recommend the frame and the principle of the exper... 详细信息

关键词： Fault Diagnosis Expert System Neural Network bp algorithm

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Design Wireless Multi-sensor Fire Detection and Alarm System Based on ARM

Design Wireless Multi-sensor Fire Detection and Alarm System...

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2009 9th International Conference on Electronic Measurement & Instruments（ICEMI’2009）

作者： Haibing Hu Gang Wang Qixing Zhang Jinjun Wang Jun Fang Yongming Zhang (State Key Laboratory of Fire Science China University of Science and Technology,Hefei 230027,China)

The system uses nRF2401 for short-range wireless communications,GPRS for long-distance wireless communications,ARM9 for center console,Wireless Multi-sensor Fire Detector for node,and bp algorithm is used for judging the probability of *** Multi-sensor Fire Detector is formed of the low-power electrochemical carbon monoxide sensor,photoelectric smoke detector and semiconductor temperature *** algorithm program is embedded in the S3C2440A *** samples of bp algorithm were derived from the fire detection standard room of the State Key Laboratory of Fire Science of *** console uses Em GIS(embedded GIS) to show where the fire break out and uses GPRS to transmit SMS to the fire command *** system is low false alarm rate,low cost,fast response and convenient to install.

关键词： ARM9 Multi-sensor fire detector Em GIS nRF2401 GPRS bp algorithm

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Vehicle Types Recognition Based on Neural Network

Vehicle Types Recognition Based on Neural Network

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2009 International Conference on Computational Intelligence and Natural Computing(CINC 2009)

作者： Xin-bo ZHANG, Li JIANG College of Information and Electronic Engineering ZheJiang Gongshang University Hangzhou,zhejiang,china

As a key technology of intelligent transportation system, higher identification accuracy, robustness and real-time are needed in vehicle recognition. Therefore, in view of the features of vehicle types, this paper proposes a bp neural network car types classifier method based on fuzzy C-means clustering. First, on the basis of the pretreatment of the images of the vehicle ,we abstract the features of car types from images and classify the massive dataes by fuzzy C- means clustering algorithm. Then, design the bp neural networks to train and test the classified data. Finally it is carried on compressive judgment by the computer. Experiments prove the validity of the classifier. It can recognize the highway vehicle types rapidly.

关键词： character abstraction fuzzy c-means clustering bp algorithm

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An Improved Normalized bp Based Decoding algorithm for LDPC Codes

An Improved Normalized BP Based Decoding Algorithm for LDPC ...

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2008 the IET 2ND International Conference on Wireless,Mobile & Multimedia Networks

作者： Haigang Zhang Dongfeng Yuan Cheng-Xiang Wang School of Information Science and Engineering Shandong University Joint Research Institute for Signal and Image Processing School of Engineering & Physical SciencesHeriot-Watt University

A uniformly most powerful(UMP) belief propagation(bp) based algorithm is referred to as a simplified version of a bp algorithm with reduced complexity but performance loss for low density parity check(LDPC) *** compensate the performance loss,the normalized bp based algorithm was proposed,where the normalization factor was derived by mean ratio or by minimizing the mean square *** this paper,an improved novel normalized bp based algorithm is *** normalization uses multiplicative factor instead of divisional *** novel scheme shows better performance than the existing normalized bp based algorithms while keeping the same implementation *** simulation is done for two kinds of LDPC codes:random constructed codes and finite geometry codes. At high signal-to-noise ratio(SNR) region,the proposed scheme can achieve even better performance than bp algorithm for short length random constructed LDPC codes.

关键词： LDPC codes bp algorithm Normalized bp

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Simulation-based validation of improved bp-based decoding algorithms of LDPC codes

Simulation-based validation of improved BP-based decoding al...

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3rd IEEE International Symposium on Control, Communications and Signal Processing (ISCCSP 2008)

作者： Abdelhedi, Manel Tlili, Fethi Slama, Larbi Ben Hadj ENIT SYSCOM Lab Tunis Tunisia CIRTA COM LAB SUP COM Tunis Tunisia SYSTEL LAB SUP COM Tunis Tunisia

ISBN: (纸本)9781424416875

Low-density parity-check (LDPC) codes deliver very good performance when decoded with the bp algorithm. Unfortunately, this algorithm has the disadvantage to be complex for implementation. In this paper, we investigate the bp algorithm and its simplifications (bp-Based, normalized bp-Based, offset bp-Based). Previous works on normalized and offset bp-Based proposed theoretical values for the offset and normalization factors, we perform simulations which allow to validate these theoretical results.

关键词： LDPC codes bp algorithm bp-based algorithm normalized bp-based algorithm offset bp-based algorithm

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Design Wireless Multi-sensor Fire Detection and Alarm System Based on ARM

Design Wireless Multi-sensor Fire Detection and Alarm System...

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2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI'2009)

作者： Haibing Hu Gang Wang Qixing Zhang Jinjun Wang Jun Fang Yongming Zhang State Key Laboratory of Fire Science China University of Science and Technology Hefei 230027China

ISBN: (纸本)9781424438631;9781424438624

The system uses nRF2401 for short-range wireless communications, GPRS for long-distance wireless communications, ARM9 for center console, Wireless Multi-sensor Fire Detector for node, and bp algorithm is used for judging the probability of fire. Wireless Multi-sensor Fire Detector is formed of the low-power electrochemical carbon monoxide sensor, photoelectric smoke detector and semiconductor temperature sensor. bp algorithm program is embedded in the S3C2440A ARM. The samples of bp algorithm were derived from the fire detection standard room of the State Key Laboratory of Fire Science of China. Center console uses Em GlS(embedded GIS) to show where the fire break out and uses GPRS to transmit SMS to the fire command center. The system is low false alarm rate, low cost, fast response and convenient to install.

关键词： ARM9 Multi-sensor fire detector Em GIS nRF2401 GPRS bp algorithm

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The Control System Of GA-bp Fuzzy Neural Network Controller And Elman Network Identifier

The Control System Of GA-BP Fuzzy Neural Network Controller ...

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IEEE International Conference on Automation and Logistics

作者： Cheng Qiming Du Xufeng Zheng Yong Guo Ruiqing Shanghai Univ Elect Power Coll Elect Power & Automat Shanghai 200090 Peoples R China Shanghai Univ Coll Electromech Engn & Automat Shanghai 200072 Peoples R China

ISBN: (纸本)9781424425020

The fuzzy controller with neural network is proposed in this paper, this system consists of a fuzzy neural network controller and a model identification network, the fuzzy neural network controller is optimized by the offline genetic algorithm of global searching ability, and the online bp algorithm ability of local searching. The detailed control algorithm is given, the algorithm of system identification based on modified Elman network is ratiocinated. The simulation result shows the feasibility and validity of the proposed method.

关键词： Fuzzy Neural Network Genetic algorithm bp algorithm Elman Network Fuzzy Control

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Learning TSK Fuzzy Model by GA-bp Method

Learning TSK Fuzzy Model by GA-BP Method

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9th International Conference for Young Computer Scientists

作者： Liu, Jiancheng Jiang, Xinhua Lan, Baohua Cent S Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China

ISBN: (纸本)9781424441983

It is difficult to learn TSK fuzzy model because the problem is multi-constraint and multi-target optimization. GA-bp hybrid learning method for the model is proposed. Some problems related to a species coding means for the model structure, evolution and fitness evaluation strategy are discussed. The error back propagation algorithm (bp) for training the antecedent and consequent parameters during the process of evolution is inferred. The characteristic Of the method requests a little of previous information about objects, and avoids slow convergence, and has better adaptive capability, and is able to obtain compact and accurate fuzzy model from samples, the validity of the method has been demonstrated by an example of function approximation.

关键词： TSK Fuzzy model genetic algorithm bp algorithm

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WEIGHTS OPTIMIZATION OF NEURAL NETWORK VIA IMPROVED BCO APPROACH

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PROGRESS IN ELECTROMAGNETICS RESEARCH-PIER 2008年 83卷 185-198页

作者： Zhang, Y. Wu, L. Southeast Univ Sch Informat Sci & Engn Nanjing Peoples R China

Feed forward neural Network (FNN) has been widely applied to many fields because of its ability to closely approximate unknown function to any degree of desired accuracy. Back Propagation (bp) is the most general learning algorithms, but is subject to local optimal convergence and poor performance even on simple problems when forecasting out of samples. Thus, we proposed an improved Bacterial Chemotaxis Optimization (BCO) approach as a possible alternative to the problematic bp algorithm, along with a novel adaptive search strategy to improve the efficiency of the traditional BCO. Taking the classical XOR problem and sinc function approximation as examples, comparisons were implemented. The results demonstrate that our algorithm is obviously superior in convergence rate and precision compared with other training algorithms, such as Genetic algorithm (GA) and Taboo Search (TS).

关键词： .Genetic algorithm widely sinc RBF FUNCTION APPROXIMATION bacterial XOR chemotaxis FNN bp algorithm IMPROVED BCO

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On hydrologic calculation using artificial neural networks

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APPLIED MATHEMATICS LETTERS 2008年第5期21卷 453-458页

作者： Feng, Lihua Hong, Weihu Zhejiang Normal Univ Dept Geog Jinhua 321004 Peoples R China

Artificial Neural Networks (ANN) deal with information through interactions among neurons (or nodes), approximating the mapping between inputs and Outputs based oil nonlinear functional composition. They have the advantages of self-learning self-organizing, and self-adapting. It is practical to use ANN technology to carry out hydrologic calculations. To this end, this note has fundamentally set Lip a system of calculation and analysis based oil ANN technology, and given all example of application with good results. It shows that ANN technology provides a relatively effective way of solving problems in hydrologic calculation. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： artificial neural networks bp algorithm hydrologic calculation

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