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检索条件"主题词=BP Algorithm"

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Fuzzy Neural Network Control of The Garbage Incinerator 2

Fuzzy Neural Network Control of The Garbage Incinerator

引用

2nd International Conference on Information Science and Control Engineering

作者： Yu Xiao-hong Yang Zhu-zhong Yang Tao Chengdu Univ Sch Elect Informat Engn Chengdu 610106 Peoples R China Chengdu Univ Ctr Expt Technol Chengdu 610106 Peoples R China

ISBN: (纸本)9781467368506

In order to solve the problem of garbage treatment effectively, a control method is proposed based on Takagi-Sugeno (T-S) fuzzy neural network model after analyzing the characteristics of garbage incinerators system and the main factors affecting combustion. A T-S fuzzy neural network model for garbage incinerators control is established which utilizes bp learning algorithm for data training. Then a simulation research is carried out to verify the feasibility and superiority. Results show that the T-S fuzzy neural network control can well track the input in a relative short time. The contrast analysis with conventional PID control and fuzzy control is done to show a better performance under the fuzzy neural network control. The fuzzy neural network control method can adapt to the complex garbage incineration process, which makes it high application value.

关键词： Garbage Incineration T-S Fuzzy neural network bp algorithm

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Land suitability evaluation based on artificial neural network

Land suitability evaluation based on artificial neural netwo...

引用

3rd International Symposium on Multispectral Image Processing and Pattern Recognition

作者： Liu, YL Molenaar, M Liu, YF Jiao, LM Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Peoples R China

ISBN: (纸本)0819451819

Artificial Neural Networks (ANN) has many good qualities comparing with ordinary methods in Land Suitability Evaluation. Based on analysis of ordinary methods' limitations, some sticking points of bp model of ANN used in land evaluation are discussed in detail, such as network structure, learning algorithm, etc. The land evaluation of Qionghai city is used as a case study. we know that ANN always can give more reasonable evaluation results from test.

关键词： ANN bp networks bp algorithm land suitability evaluation

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Generation and Optimization of Elastic Extension Rules Based on Cloud Computing

Generation and Optimization of Elastic Extension Rules Based...

引用

International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS)

作者： Wu DaQin Wang Shanshan Jilin Businees & Technol Coll Dept Informat Engn Changchun Jilin Peoples R China

ISBN: (纸本)9781509060610

With the cloud computing development, elastic scaling capability is an important factor to ensure the quality of cloud services. In this paper, the author designed resource requirement model about web system based on neural network under the certain quality of service on cloud platforms. According to the model, the method and mechanism for elastic scaling is realized by bp algorithm on cloud platforms.

关键词： Elasticity Cloud Computing bp algorithm Neural Network

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NNPID applied in the hydraulic AGC system 6

NNPID applied in the hydraulic AGC system

引用

6th International Conference on Fluid Power Transmission and Control (ICFP 2005)

作者： Wang, YQ Wang, HF Zhang, W Zhu, DD Yanshan Univ Coll Mech Engn Qinhuangdao Peoples R China

ISBN: (纸本)7506274027

A new neural network PID (NNPID) controller, which is based on PID by means of neural network's ability of self-learning and adaptive, is presented. The NNPID controller is designed by combining neural network with PID control strategy. Additional momentum method, that is an improved bp algorithm, is used in the neural network is analyzed. This paper presents the control for the highly nonlinear, time-varying hydraulic AGC of rolling mills based on the NNPID controller. The simulation shows that the dynamic quality of the system is improved, and NNPID has good adaptability.

关键词： PID control Neural Network bp algorithm hydraulic AGC

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Application of the Artificial Neural Networks in Strip Shape Defect Identification

Application of the Artificial Neural Networks in Strip Shape...

引用

2nd International Symposium on Test Automation and Instrumentation

作者： An Shiqi Qingdao Univ Sci & Technol Automat & Elect Engn Inst Qingdao 266042 Peoples R China

ISBN: (纸本)9787506292207

An intelligent pattern recognition used artificial neural networks is presented in this paper to meet the requirement of controlling stripe shape in cold rolling. The cold-rolled products are characterize into several types based on its irregularity, 'left wave', 'right wave', 'center buckle', 'edge wave', 'W-type', and 'M-type'. The developed identification algorithm calculates for each type of irregular strip shape using neural network and experiment data. The work is studied by taking a double-stand reversing cold rolling mill as example. The method improves the speed and the accuracy of strip shape identification.

关键词： Strip shape defect identification artificial neural networks bp algorithm reversing cold rolling mill

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IMPROVED algorithm OF THE BACK PROPAGATION NEURAL NETWORK AND ITS APPLICATION IN FAULT DIAGNOSIS OF AIR-COOLING CONDENSER

IMPROVED ALGORITHM OF THE BACK PROPAGATION NEURAL NETWORK AN...

引用

7th International Conference on Wavelet Analysis and Pattern Recognition

作者： Li, Yong Fu, Yang Zhang, Si-Wen Li, Hui NE Dianli Univ Sch Energy Resources & Mech Engn Jilin 132012 Peoples R China

ISBN: (纸本)9781424437276

This paper addresses the application of neural network to air-cooling condenser faults diagnosis. For traditional Back Propagation (bp) neural network algorithm, the learning rate selection is depended on experience and trial. In this paper, an improved bp neural network algorithm with self adaptive learning rate is proposed using the fundamental equation. Unlike existing algorithm, self adaptive learning rate depends on only network topology, training samples, average quadratic error and error curve surface gradient but not artificial selection. The train results show iteration times is less than that of traditional algorithm with constant learning rate and it is a feasible method to diagnose air-cooling condenser faults.

关键词： Artificial neural network bp algorithm Steam turbine Air- cooling condenser Fault diagnosis

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The back propagation neural network model of non-periodic defected ground structure

The back propagation neural network model of non-periodic de...

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Global Symposium on Millimeter Waves

作者： Li Yuan Liu Jiao Ye Chunhui Tianjin Univ Sch Elect Informat Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9781424418855

Presently, electromagnetic field numerical value analysis methods such as finite difference time-domain (FDTD) method are generally used to calculate the DGS, although these methods are accurate, they are also computationally expensive. In this paper, a neural network model of a novel defected ground structure is established. Since the neural network model has the advantages of great precision and effectiveness, the developed design model can be used to take the place of the FDTD method of the DGS, being a kind of aid tool of circuit design. The neural network models of two different non-periodic DGS have been developed, at the same time the circuit of the according DGS is designed and manufactured. The result of computer simulation and product measurements are obtained to demonstrate the effectiveness of the method.

关键词： neural network non-periodic DGS bp algorithm

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Image Transmission with UEP-LT over MIMO Channels

Image Transmission with UEP-LT over MIMO Channels

引用

22nd Wireless and Optical Communications Conference (WOCC)

作者： Zhang, Wuping Jing, Xiaorong Zhang, Zufan Chen, Qianbin Chongqing Univ Posts & Telecommun Chongqing Key Lab Mobile Commun CQUPT Chongqing Peoples R China

ISBN: (纸本)9781467356978;9781467356992

The Luby Transform (LT) codes have been suggested as an efficient solution for multimedia communications over erasure packet network, and provide equal error protection (EEP) for all input symbols. However, for the progressive image transmission, the significant source bits are generally located ahead of the bit streams of the encoder output, which are more important for the reconstruction of the image. Therefore, the LT codes based on EEP (EEP-LT) scheme is not suitable for the progressive image transmission. In the paper, based on the LT codes, a novel unequal error protection (UEP) scheme is proposed for image transmission over multiple input multiple output (MIMO) channels, which is named UEP-LT scheme. Simulation results confirm the efficiency of the proposed scheme.

关键词： MIMO progressive source LT codes bp algorithm unequal error protection

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New Research on Harmonic Detection Based on Neural Network for Power System

New Research on Harmonic Detection Based on Neural Network f...

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3rd International Symposium on Intelligent Information Technology Application

作者： Chen Ying Lin Qingsheng Nanchang Univ Sch Informat Engn Nanchang Peoples R China

ISBN: (纸本)9780769538594

Analysis and control for power quality by neural network is a new research field in electrical power system. Rapid and reliable extract the harmonic components determine the overall performance of Active Power Filter (APF). This paper presents a new three-layer feedforward neural network based on error back-propagation algorithm that the training sample without time delay, which can detecting harmonics for power system in real-time. With the simulation study using Mat lab, the simulation results illustrate that the harmonic detection method based on neural network is feasible, which can quickly detecting the harmonics for nonlinear load.

关键词： harmonics detection APF feedforward neural network bp algorithm

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Application of combinatorial probabilistic neural network in fault diagnosis of power transformer

Application of combinatorial probabilistic neural network in...

引用

6th International Conference on Machine Learning and Cybernetics

作者： Liang, Yong-Chun Sun, Xiao-Yun Liu, Dong-Hui Sun, Hui-Qin Hebei Univ Sci & Technol Dept Elect Engn Shijiazhuang 050054 Peoples R China

ISBN: (纸本)9781424409723

Probabilistic Neural Network (PNN) overcame the shortcomings of entrapment in local optimum, slow convergence rate which was in bp algorithm. With enough training samples, PNN obtained the optimal result of Bayesian rules. Because of the fast training rate, the training samples can be added into PNN at any time. So, PNN is fit to diagnose the fault of power transformer and has auto-adaptability. In order to improve the classification accuracy, the conception of combination is introduced into PNN. The fault diagnosis of power transformer is consisted of 4 Probability neural networks in this paper. PNN1 is used to classify the normal and fault. PNN2 is used to classify the heat fault and partial discharge (PD) fault. PNN3 is used to classify the general overheating fault and severe overheating fault. PNN4 is used to classify the partial discharge fault, and energy sparking or arcing fault. The example shows that the effect of combinatorial PNN is a good classifier in the fault diagnosis of power transformer. The combinatorial PNN has better diagnosis accuracy than bpNN and FUZZY algorithm.

关键词： probabilistic neural network bp algorithm Bayesian rules diagnosis power transformer

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