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检索条件"主题词=BP Algorithm"

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Safety Assessment of the General Overhead Traveling Crane Metal Structure Based on bp Neural Network

Safety Assessment of the General Overhead Traveling Crane Me...

引用

2nd International Conference on Engineering Design and Optimization (ICEDO 2011)

作者： Xu, Gening Zhang, Qian Taiyuan Univ Sci & Technol Sch Mech & Elect Engn Taiyuan 030024 Shanxi Peoples R China

ISBN: (纸本)9783037852590

Safety assessment of bridge crane metal structure is widely needed. A general bridge safety assessment model of metal structure based on bp neural network is established. bp neural network is suitable for the problem that is not fully known and the adaptability of the dynamic system, and can facilitate the assignment and statistics of the safety evaluation system. Matlab7.0 software is used for the network training process. Through the training, samples to be tested were verified for the feasibility of the security model. The security model based on bp neural network for the general overhead traveling crane structure could provide a safety assessment and evaluation methods.

关键词： bp Neural Network bp algorithm the General overhead traveling crane metal structure Safety Assessment

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A method based on bp neural network to detect SIP DOS flooding attack

A method based on BP neural network to detect SIP DOS floodi...

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International Conference on Information Technology and Management Innovation (ICITMI2012)

作者： Cheng, Haixiu Zeng, Bi Guangdong Univ Technol Fac Comp Guangzhou Guangdong Peoples R China

ISBN: (纸本)9783037855744

In order to detect the SIP flooding attacks in IMS (IP Multimedia Subsystem) network, the paper proposes a flooding attack detection method based on bp neural network, and analyses causes of SIP flooding attack, and thus determine the bp the input of the neural network characteristics. The simulation results show that this method has better detection performance.

关键词： Session Initiation Protocol flooding attacks bp neural network bp algorithm

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A Study of Data Fusion Based on Combining Rough Set with bp Neural Network

A Study of Data Fusion Based on Combining Rough Set with BP ...

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9th International Conference on Hybrid Intelligent Systems (HIS 2009)

作者： Gao, Wei Wen, Jingxin Jiang, Nan Zhao, Hai Northeastern Univ Shenyang Inst Chem Technol Inst Informat & Technol Shenyang Peoples R China Northeastern Univ Shenyang Inst Chem Technol Shenyang Peoples R China Northeastern Univ Inst Informat Technol Shenyang Peoples R China

ISBN: (纸本)9780769537450

Based on rough set and basic theory of data fusion, the data fusion algorithm combining rough set theory and bp neural network is studied. Since rough set theory can effectively simplify information, cut down the tagged dimension. This paper will be rough set theory and neural networks combined, using channel capacity of knowledge relative reduction algorithms to simplify the input information. Rough set theory is first used to process the sample data, and eliminate the redundant information, then reduce the scale of neural network, improve the identification rate, and improve the efficiency of the whole data fusion system. The effectiveness of the improved algorithm is demonstrated by an example compared with the traditional neural network system.

关键词： rough set neural network bp algorithm data fusion attribute reduction

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Application of modified bp neural network to recognition of characters

Application of modified BP neural network to recognition of ...

引用

2nd International Symposium on Instrumentation Science and Technology (ISIST 2002)

作者： Li, LL Ding, XH Deng, SX Hefei Univ Technol Coll Instrumentat Sci Hefei 230009 Anhui Peoples R China

ISBN: (纸本)7560317685

Based on the simple feature extraction, the neural network is trained by inputting ideal and noisy samples, and the modified bp algorithm is applied to recognize, the 26 English alphabets and the 10 digits, which increases the network's ability to tolerate fault and correctly recognize the characters that contain a mass of noise. The network was trained twice, in order that the network's recognition rate to the ideal characters didn't decline, still had two set of ideal samples as input at the second training, and the output weights of first training were input as initial weights at the second training. In order to obtain the perfect structure parameters of network and research each parameter's effect on the performance of network, a large number of simulation tests were conducted. Finally, recognition rate above 95% was obtained on the condition that the noise's mean was 0.2, and achieved 100% recognition rate to the ideal characters.

关键词： Artificial neural network bp algorithm character recognition feature extraction recognition rate weights thresholds

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Water Demand Forecasting in Hubei Province with bp Neural Network Model

Water Demand Forecasting in Hubei Province with BP Neural Ne...

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Global Conference on Civil, Structural and Environmental Engineering / 3rd International Symp on Multi-field Coupling Theory of Rock and Soil Media and its Applications

作者： Tang, Zhenquan Liu, Gang Xu, Wennian Xia, Zhenyao Xiao, Hai China Three Gores Univ Coll Hydraul & Environm Engn Yichang 443002 Hubei Peoples R China

ISBN: (纸本)9783037855386

Prediction of water demand is a basic link in water resources plan and management. Reasonable and accurate prediction of storage helps to develop the plan of water resources the next year, which is very favorable to improve the utilization ratio of water resources and reduce the waste of water resources. This paper uses bp neural network to simulate and predict the water content based on the data of water in recent ten years in Hubei province and evaluates the forecast results. The results show that bp neural network for water demand prediction is feasible.

关键词： Artificial neural network bp algorithm Water demand prediction

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Modeling and Simulation of Screw Axis Based on PSO-bp Neural Network and Orthogonal Experiment

Modeling and Simulation of Screw Axis Based on PSO-BP Neural...

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2nd International Symposium on Computational Intelligence and Design

作者： You Zhang-ping Li Sheng-yu Li Wan-li Li Zi-guang Tongji Univ Coll Mech Engn Shanghai 200092 Peoples R China Lishui Univ Coll Mech Engn Lishui Peoples R China Changsha Univ Sci & Technol Changsha Hunan Peoples R China

ISBN: (纸本)9780769538655

It is a trouble thing to build theoretical model for stir characteristics of screw axis with variable diameters and different pitches, so a called PSO-bp Neural Network (NN) model was employed. In this mode, Particle Swarm Optimization (PSO) algorithm is used to train weights and thresholds of artificial neural network instead of bp algorithm, to overcome drawbacks of bp algorithm. To avoid the slow search speed around global optimum in the PSO-bp algorithm, a heuristic way was adopted to give a transition from particle swarm search to gradient descending search. To validate the model, a group of orthogonal experiments were designed and performed, and simulation experiment was carried out with the NN model. Simulation and experiment results indicate that PSO-bp NN is an effective training algorithm, and it provides an effective modeling approach of screw axis with variable diameters and different pitches.

关键词： particle swarm optimization bp algorithm modeling simulation orthogonal experiment neural network

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Integrated risk early warning of institutional investors based on bp network

Integrated risk early warning of institutional investors bas...

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13th International Conference on Management Science and Engineering

作者： Tian Qing-feng Yang Nai-ding Jiang Ji-jiao Northwestern Polytech Univ Sch Management Xian 710072 Peoples R China

ISBN: (纸本)7560323553

This study was aimed at developing an integrated risk early warning pattern of institutional investors with bp network. By indicating advantages of bp network in dealing with various risk factors, it's formed an integrated risk early warning model, which is optimized structurally through training and testing. It presents a type of an improved bp network algorithm with adjusting function by fuzzy inference and applies it to the optimization of risk early warning indexes. The simulation shows that this model will be well on describing the holistic risk status, distilling key risk factors, and adopting systematic risk countermeasures for institutional investors.

关键词： artificial neural network bp algorithm fuzzy inference system risk management

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Parallel Implementation of bp Neural Network for Traffic Prediction on Sunway Blue Light Supercomputer

Parallel Implementation of BP Neural Network for Traffic Pre...

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International Conference on Machinery, Electronics and Control Simulation (ICMECS)

作者： Feng, Jinqiao Gu, Weidong Pan, Jingshan Zhong, Hongjun Huo, Jidong Comp Ctr Shandong Prov Jinan 250014 Shandong Peoples R China Natl Supercomp Ctr Jinan Jinan 250101 Shandong Peoples R China

ISBN: (纸本)9783038352105

Parallelized training algorithm of MLP-bp neural network is implemented on the Sunway Blue Light Supercomputer. Efforts are mainly focused on the dada parallel method based on the characteristics of the training process. The implementation mainly depends on MPI techniques, which ensures the universality of the application. A new strategy of data partition and storage is applied in the parallelism. Tests of short-term traffic prediction which is significant in the intelligent transportation system are carried out to verify the accuracy and efficiency of the routines.

关键词： bp algorithm artificial neural network parallelization short-term traffic prediction

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Adaptive bp Wavelet Neural Network Method for Soft Fault Diagnosis in Analog Circuit

Adaptive BP Wavelet Neural Network Method for Soft Fault Dia...

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International Conference on Mechatronics and Computational Mechanics (ICMCM 2012)

作者： Cong, Wei Jing, Bo Yu, Hong-Kun Air Force Engn Univ Aeronaut & Astronaut Engn Coll Xian 710038 Shaanxi Peoples R China

ISBN: (纸本)9783037856598

Because of the diversity and complexity of soft fault in analog circuit, the rapid and accurate diagnosis is very difficult. For this, an adaptive bp wavelet neural network diagnosis method of soft fault is proposed. It combines the time-frequency localization characteristics of wavelet and the self-learning ability of neural network in soft fault diagnosis of analog circuit, and by introducing the adaptive learning rate the diagnosis ability of bp wavelet neural network model can effectively be improved. In addition, PSPICE software is used to obtain the simulation data of actual analog circuit for the experiment. The results also verify the validity of the proposed method.

关键词： Wavelet neural network Adaptive learning rate bp algorithm Soft fault diagnosis

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Recognition of industrial parts based on bp neural network

Recognition of industrial parts based on BP neural network

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2nd International Symposium on Instrumentation Science and Technology (ISIST 2002)

作者： Liu, B Jiang, LF Shi, LH Harbin Univ Sci & Technol Coll Measure Control Technol & Commun Engn Harbin 150080 Peoples R China

ISBN: (纸本)7560317685

The human-computer communication mode is adopted to identify the parts. In the-course of Pattern Recognition, We adopted bp neural network and brings forward a sort of improved bp algorithm based on the limitation of the bp algorithm. When the bp neural network algorithm is applied for identification of industrial parts, the speed and accuracy of identification is improved greatly. The practices indicate that this system can increase productivity and guarantee the quality of products.

关键词： image processing neural network bp algorithm pattern recognition

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