The Model and Application of the Investment Risk Comprehensive Evaluation about the Electric Power Project Based on BP Neural Network

BP neural network has been successfully used in the gas well productivity prediction, but as a result of neural network is sensitive to the number of input parameters, we had to ignore some factors that is less important to the gas well productivity. In addition, the existing various productivity prediction method cannot consider the influence of some important qualitative factors. This article integrated the advantages of fuzzy comprehensive evaluation and BP neural network, fuzzy comprehensive evaluation method is used to construct the BP neural network's input matrix, and BP neural network learning function is used to solve the connection weights, so as to achieve the aim of predicting gas production. This method not only can consider as many factors influence on gas well production, ut also can consider qualitative factors, so the forecast results of the new model are more realistically close to the actual production situation of reservoirs.

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Application of Genetic BP Neural Network in Safety Comprehensive Evaluation of Tailing

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.687-691.2402 ◽

2014 ◽

Vol 687-691 ◽

pp. 2402-2406

Author(s):

Song Jiang ◽

Hui Wen He ◽

Hong Bo Liu ◽

Kang Ting Lv

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Bp Neural Network ◽

Comprehensive Evaluation ◽

Evaluation Model ◽

Threshold Value ◽

Generalization Ability ◽

Learning Speed ◽

Security Levels ◽

Improved Accuracy

Based on safety assessment factors determined by operation characteristics of a certain tailing ,genetic BP neural network evaluation model is established. To overcome such problems of BP neural network as slow convergence ,poor generalization ability and easy to fall into local minimum value,this paper proposes to use genetic algorithm to optimize threshold value,weights and structure of neural network. Thus,by taking advantage of extensive mapping ability of neural network and global search ability of genetic algorithm,neural network and genetic algorithm will have complementary advantages and the learning speed of network will be accelerated. The application of the described method shows optimized fitting precision,improved accuracy and efficiency ,and enhanced generalization ability of BP neural network. In conclusion,this model can effectively reflect and accurately evaluate non-linear relations between security levels and evaluation factors in tailing.

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Safety Assessment of Transmission Grid Based on Fuzzy Comprehensive Evaluation and BP Neural Network

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.439-440.528 ◽

2010 ◽

Vol 439-440 ◽

pp. 528-533

Author(s):

Yuan Sheng Huang ◽

Wei Fang ◽

Cheng Fang Tian

Keyword(s):

Neural Network ◽

Bp Neural Network ◽

Safety Assessment ◽

Evaluation Method ◽

Comprehensive Evaluation ◽

Fuzzy Comprehensive Evaluation ◽

Transmission Grid ◽

Comprehensive Evaluation Method ◽

System Method ◽

Grid Based

In the practice of safety assessment on transmission grid, there is the variation degree of many indexes which can not be accurately described, and fuzzy comprehensive evaluation method can reflect the safety degree of every element. In addition, the combination use of BP neural network and expert system method can determine impact extent of assessment factors on safety of transmission grid and the weight of each factor relative to safety of transmission grid. Therefore, the paper proposes the safety assessment of transmission grid based on BP neural network and fuzzy comprehensive evaluation. Finally, an example is used to prove the method is high precision and practical.

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