煤田地质与勘探2011，Vol.39Issue(4)：8-12,5.DOI:10.3969/j.issn.1001-1986.2011.04.003
GA-BP神经网络模型在彬长矿区测井岩性识别中的应用
Application of genetic-BP neural network model in lithology identification by logging data in Binchang mining area
刘明军 1李恒堂 1姜在炳1
作者信息
- 1. 中煤科工集团西安研究院,陕西西安710054
- 折叠
摘要
Abstract
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.关键词
测井数据/BP神经网络/遗传算法/岩性识别Key words
logging data/ BP neural network/ genetic algorithm/ lithology identification分类
天文与地球科学引用本文复制引用
刘明军,李恒堂,姜在炳..GA-BP神经网络模型在彬长矿区测井岩性识别中的应用[J].煤田地质与勘探,2011,39(4):8-12,5.
