作业帮请将下面的英文翻译成中文 感激不尽!谢绝机器直翻!
来源：学生作业帮 编辑：拍题作业网作业帮 分类：英语作业 时间：2024/04/30 12:00:23
请将下面的英文翻译成中文 感激不尽!谢绝机器直翻!
There are various methods adopted for the forecasting of future market price. One approach to predict the market behaviors is regression. The basic idea is to use the historical prices, quantity and other information such as load forecast, and temperatures to predict the MCPs. That is, use history and other estimated factors in the future to ‘‘fit’’ and ‘‘extrapolate’’ the prices and quantity.
Important methodological issues and techniques for electricity load and price forecasting are presented in. Computationally intensive methods like variable segmentation, multiple modeling, combinations and neural networks for forecasting demand side and strategic simulation using artificial agents for the supply side are used. Conceptual framework for designing price forecasting approaches are presented . Modeling competitive market behavior in capturing uncertainty in inputs/outputs with adaptability and transparency is presented. Model of Market-clearing price (MCP) and Database for forecasting electricity prices is described. Forecasting Energy prices using neural networks and fuzzy logic and their combination is discussed in . Historical behaviors of spot prices was evaluated for these methods. Emphasis is placed on the identification of important parameters which influence the forecasted quantity. Basic framework of artificial neural network for load forecasting based on historical load data and temperature is presented . A multi layer perception using three hidden layers is implemented for accurate load forecasting.
该论文是基于神经网络的电价预测 谢谢各位啦！
There are various methods adopted for the forecasting of future market price. One approach to predict the market behaviors is regression. The basic idea is to use the historical prices, quantity and other information such as load forecast, and temperatures to predict the MCPs. That is, use history and other estimated factors in the future to ‘‘fit’’ and ‘‘extrapolate’’ the prices and quantity.
Important methodological issues and techniques for electricity load and price forecasting are presented in. Computationally intensive methods like variable segmentation, multiple modeling, combinations and neural networks for forecasting demand side and strategic simulation using artificial agents for the supply side are used. Conceptual framework for designing price forecasting approaches are presented . Modeling competitive market behavior in capturing uncertainty in inputs/outputs with adaptability and transparency is presented. Model of Market-clearing price (MCP) and Database for forecasting electricity prices is described. Forecasting Energy prices using neural networks and fuzzy logic and their combination is discussed in . Historical behaviors of spot prices was evaluated for these methods. Emphasis is placed on the identification of important parameters which influence the forecasted quantity. Basic framework of artificial neural network for load forecasting based on historical load data and temperature is presented . A multi layer perception using three hidden layers is implemented for accurate load forecasting.
该论文是基于神经网络的电价预测 谢谢各位啦！
在预测未来市场价格时可以采取各种各样的方式.一种预测市场行为的方式是回归复原法.其基本理念是用历史价格、总量及其他信息,例如负荷预测和温度推算市场出清价格.即是,用历史价格因素和其他未来可评估的因素来推测和得出一个和未来市场接近的价格和总量.
先第一段.好困.明天帮你翻第二段.
如果你能够给一些关于材料的背景会更好一些.
翻译得不是很专业,
先第一段.好困.明天帮你翻第二段.
如果你能够给一些关于材料的背景会更好一些.
翻译得不是很专业,