海洋科学2016，Vol.40Issue(5)：103-108,6.DOI:10.11759//hykx20141113001
基于灵敏度分析的海洋油气资源BP神经网络预测模型的优化
Structure optimization of ocean oil and gas resources via BP neural network prediction model based on sensitivity analysis
摘要
Abstract
To resolve problems existing in the backpropagation (BP) neural network structure design, we used the sensitivity analysis method to optimize the BP neural network prediction model. First, we investigated the impact factors of the input and output attributes of the network by combining the BP algorithm and parameter sensitivity analysis. Then, based on an accurate premise, we optimized the input attributes of the BP network and simplified the model network structure to improve the network’s generalization ability and to greatly reduce the subjective choice of the structural parameters. Lastly, taking ocean oil and gas resources prediction as an example, we estab-lished the BP neural network prediction model using the measured data, and conducted a sensitivity analysis and prediction accuracy evaluation. The results indicate that the optimized model can effectively improve the stability of the prediction results with no loss in prediction accuracy.关键词
BP神经网络/网络结构设计/灵敏度分析/模型优化Key words
BP neural network/network structure design/sensitivity analysis/model optimization分类
信息技术与安全科学引用本文复制引用
赵健,刘展..基于灵敏度分析的海洋油气资源BP神经网络预测模型的优化[J].海洋科学,2016,40(5):103-108,6.基金项目
山东省自然科学基金项目(ZR2014DQ008) （ZR2014DQ008）
中国石油科技创新基金项目(2015D-5006-0302) （2015D-5006-0302）
中央高校基本科研业务费专项基金(16CX02031A)@@@@Shandong Provincial Natural Science Foundation, China, No. ZR2014DQ008 （16CX02031A）
PetroChina Innovation Foundation, No.2015D-5006-0302 （）
the Foundamental Research Funds for the Central Universities, No.16CX02031A。 （）
