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- W2362798941 abstract "Based on the analysis of the advantages of genetic algorithm and BP neural network in depth, this article proposes a modified model of genetic algorithm neural network (GANN), of which principle is to obtain the best network architecture by using the GA to optimize the structure and connection weights of the neural network. In this process, taking all the parameters as a whole and code as chromosome, we can get network optimization through genetic iteration. and then BP network can be used to search the local optimum. The genetic algorithm is adaptable because it searches space without any special requirement. Besides, the capability of its global optimization is so strong that it can search the optimum effectively in the whole dimension of solution space. However, this method is limited by its weak adjustment and fault tolerance. Compared with this, the neural network is good at distributed storage and fault-tolerant and in addition, its self-learning, self-organization and self-adaptation is also very strong. So that the neural network can implement self-organization and adjust itself through training, or learning to deal with those problems that contain vatious information, fuzzy information or unclear inference rules. its searching capability is, however, poor, and easy to fall into local optimum. According to the respective advantages and disadvantages of the two methods, this article studies the algorithm of complementation of the advantages of GA NN together. The application of the algorithm to the investment decision of XinChang gas field shows that the evaluation results are more reasonable and objective." @default.
- W2362798941 created "2016-06-24" @default.
- W2362798941 creator A5068974069 @default.
- W2362798941 date "2008-01-01" @default.
- W2362798941 modified "2023-10-13" @default.
- W2362798941 title "A GENETIC OPTIMIZATION-BP NETWORK MODEL IN THE DECISION OF GAS FIELD DEVELOPING PLAN" @default.
- W2362798941 hasPublicationYear "2008" @default.
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