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- W2367782924 abstract "In order to accurately calculate reservoir properties,the improved Simulated Annealing Differential Evolution Algorithm(SADE) is proposed by combining simulated annaling with differential evolution algorithm.The training of neural network weights in the process of predicting complicated reservoir properties is transformed into an unconstrained optimization problem,and also a new objective function is offered.Then this problem can be solved by SADE algorithm.Compared with other traditional methods,the new objective function is independent of the desired output during the training of neural network,and thus is more suitable for large range of sample data.At the same time,the annealing temperature is used in the algorithm to control the selection process of differential evolution and the differential strategy.In the early stage,the algorithm is of good diversity,while in the late stage,it is of good convergence,overcoming the shortcoming of prematurity in the classical algorithm,and improving the general search ability and robustness.Finally we calculate the field reservoir properties with this algorithm,and obtain good effect." @default.
- W2367782924 created "2016-06-24" @default.
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- W2367782924 date "2012-01-01" @default.
- W2367782924 modified "2023-09-23" @default.
- W2367782924 title "A New Method Predicting Reservoir Properties with Neural Network Based on SADE Algorithm" @default.
- W2367782924 hasPublicationYear "2012" @default.
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