基于BP的油田产能成功度综合后评价模型研究  

Comprehensive Post Evaluation Model of Success for Productivity Construction Based on BP Fuzzy Neural Network

作　　者：杜睿山[1] 唐世伟[1] 王辉[1] 肖红[1] 刘芳[1] 

机构地区：[1]东北石油大学,大庆163318

出　　处：《计算机与数字工程》2014年第8期1325-1328,1426,共5页Computer & Digital Engineering

基　　金：黑龙江省教育厅科学技术研究项目(编号:12521055)资助

摘　　要：详细分析油田产能建设项目后评价相关指标,及其对最终综合后评价结果的影响之间的关系,建立油田产能建设项目综合后评价模型。基于成功程度综合后评价模型,在评价标准相对隶属度成功应用的基础上,进行模糊处理,用神经网络来改善的评价模型,增高评价结果的准确性。该模型不但弥补了传统成功度模型主观估计权重的缺陷,并考虑到各个评价指标对综合后评价结果的影响,科学、客观地评价项目,实验结果证明了该方法的有效性。The evaluation of productive capacity construction project of oilfield,the relationship between each index and the effect on the final results of the evaluation are analyzed detailedly,the comprehensive post evaluation model is established.On the basis of comprehensive post evaluation model of success,relative membership degree is applied to obfuscate the evaluation standards and the success degree of evaluation,and then is evaluated by the neural network,to improve the accuracy of the evaluation results.The model not only aims to make up for deficiencies of estimating weights subjectively on the traditional model,but takes into account the impact of the evaluation to the results,evaluates the project scientific and objectively.Experimental results demonstrate the method is effective.

关 键 词：产能建设 后评价模型 BP神经网络 成功度评价 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]