...
首页> 外文期刊>Open Journal of Statistics >Predictive Modeling of Gas Production, Utilization and Flaring in Nigeria using TSRM and TSNN: A Comparative Approach
【24h】

Predictive Modeling of Gas Production, Utilization and Flaring in Nigeria using TSRM and TSNN: A Comparative Approach

机译:使用TSRM和TSNN的尼日利亚天然气生产,利用和燃烧的预测模型:一种比较方法

获取原文
   

获取外文期刊封面封底 >>

       

摘要

Since the discovery of oil and gas in Nigeria in 1956, much gas has been flared because the operators pay little or no concern to its utilization, and as such, trillions of dollars have been lost. In this paper, a model is proposed using Time Series Regression Model (TSRM) and Time Series Neural Network (TSNN) to model the production, utilization and flaring of natural gas in Nigeria with the ultimate aim of observing the trend of each activity. The results show that TSNN has better predictive and forecasting capabilities compared to TSRN. It is also observed that the higher the hidden neurons, the lower the error generated by the TSNN.
机译:自从1956年在尼日利亚发现石油和天然气以来,由于运营商很少或根本不用担心天然气的使用,因此已经燃放了许多天然气,因此损失了数万亿美元。本文提出了一个使用时间序列回归模型(TSRM)和时间序列神经网络(TSNN)进行建模的模型,该模型的最终目的是观察尼日利亚各项活动的趋势。结果表明,与TSRN相比,TSNN具有更好的预测和预测能力。还观察到,隐藏的神经元越高,TSNN产生的错误越低。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号