• 责任者：Liu Mingjun (Xi’an Research Institute ; China Coal Technology and Engineering Group Corp. ; Xi’an 710054 ; China) ; Li Hengtang
• 刊名：Coal Geology & Exploration
• 出版年：2011
• 卷期：39(4)
• 关键词：地球物理测井 ; geophysical logging
• 页码：p.8-12
• 图表：5 illus., 2 tables, 13 refs.
• 分类号：1600
• issnNo：ISSN1001-1986
• isbnNo：CN61-1155/P

 Based on the analysis of features of Genetic Algorithm (GA) and Back-Propagation Algorithm (BP), it is concluded that the disadvantage of BP algorithm includes large identification specimen in inversion, so a methodology to optimize BP network structure and link weights with GA is proposed and the lithology identification model based on GA optimized BP algorithm is established. Using the basic data from Binchang mining area, the lithology identification function is tested, and the result indicates that the GA-BP neural network model has good identification speed and accuracy.oft-com:office:office" />