3) natural gas load
天然气负荷
1.
A BPneuralnetworkbased load forecasting model of natural gas is presented, and in this model all the factors that influence the natural gas load change are taken into account.
提出了一种基于BP神经网络的天然气负荷预测模型,模型中考虑了影响负荷变化的各种因素。
4) natural gas daily load
天然气日负荷
1.
The characteristics of natural gas daily load,the establishment and the optimization process of the forecast model for Beijing City are described.
论述了北京市天然气日负荷的特点、预测模型的建立及优化过程。
5) prediction of natural gas
天然气预测
1.
Through multi-target geochemical survey advances have been made in the study of the back-ground values and distribution characteristics of the elements,study of structure,agriculture and environ-mental pollution,prediction of natural gas and calculation of the pH values.
并且判定深层样对研究深部元素分布、构造研究、根深作物发育、天然气预测;浅层样对浅层元素分布、农业地质、环境污染等研究有着特殊的作用。
6) prediction of gas load
燃气负荷预测
1.
The application study of expert system in optimizing the prediction of gas load is carried out,a model of expert system for prediction of gas load is put forward,and the knowledge representation,inference mechanism and learning mechanism in the model are discussed.
进行了专家系统在燃气负荷预测优化中的应用研究,提出了一个燃气负荷预测专家系统的模型,论述了模型中的知识表示、推理机制和学习机制。
补充资料：石油天然气国际贸易(见石油市场与天然气市场)
石油天然气国际贸易(见石油市场与天然气市场)
石油天然气国际贸易(internotional tradeof011 and只as)见石油市场与天然气市场。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条