1) Gas load
燃气负荷
1.
In order to improve the forecasting accuracy,in accordance with the influence factors and characteristics of hour gas load,a model has been established to forecasting hour gas load with OIF(output-input feedback) Elman network.
为提高燃气负荷预测的精度,分析了燃气小时负荷的变化规律和影响因素,建立了燃气小时负荷预测模型,采用具有输出-输入反馈机制的改进Elman(OIF Elman)网络对燃气小时负荷进行预测。
2.
The structure of forecast model by BP neural network is discussed,and the forecast method and program flow of short-term town gas load based on this model are put forward.
论述了BP神经网络的预测模型结构,提出了基于该模型的城市燃气短期负荷预测方法和程序流程,结合某城市燃气负荷数据进行了燃气负荷模拟预测,预测结果和实际情况有很好的一致性。
3.
The rules of hourly,daily and monthly gas load are analyzed on the basis of existing data of gas consumption in a residential area.
根据居民小区现有的用气量数据,对时、日和月燃气负荷规律进行分析,得出燃气负荷的时高峰系数、日高峰系数和月高峰系数,运用时间序列理论对居民燃气时负荷进行了预测。
2) annual gas load
燃气年负荷
4) gas short-period load
燃气短期负荷
1.
Forecasting city gas short-period load based on BP model with varied learning rate;
基于变学习率BP模型的城市燃气短期负荷预测
5) 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。
6) forecast of daily gas load
燃气日负荷预测
1.
Based on the forecast of daily gas load in Anshan City,the method for processing history data of gas load is discussed.
结合鞍山市燃气日负荷预测,论述了历史燃气负荷数据的处理方法。
补充资料：MS6001系列燃气轮机一级空心涡轮叶片
MS6001系列燃气轮机一级空心涡轮叶片
Ms6()()l系列燃气轮机一级空心涡轮叶片 中同科学院金属研究所供稿
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