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首页> 外文会议>International Conference on High Technology for Sustainable Development >Comparative Post-Optimal Analysis to Effectively Forecasting the Subscriber's Daily Natural Gas Consumption
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Comparative Post-Optimal Analysis to Effectively Forecasting the Subscriber's Daily Natural Gas Consumption

机译：比较优化分析，以有效预测用户日常天然气消费量

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Although there are developments to predict energy consumption, the topic has not been exhausted and remains relevant. It should also be noted that each author uses the power of models differently to interpret inputs and outputs and their effects on the consumption process. Cutting costs and improving operational efficiency is something that energy and utility companies are continually working towards. It’s a constant battle, and the work is never complete. This study offers a comparative post-optimal analysis to effectively predict daily consumption through statistical processing of input data and methods of stochastic optimization are applied. Input data are defined indicators of factors affecting the consumption process. These indicators are sampled in the stochastic process.
机译：虽然存在预测能量消耗的发展，但该话题尚未耗尽并保持相关性。 还应注意，每个作者使用模型的力量不同地解释输入和输出以及它们对消费过程的影响。 切割成本和提高运营效率是能源和公用公司不断努力的东西。 这是一个不断的战斗，工作永远不会完成。 本研究提供了比较的最佳优化分析，以通过对输入数据的统计处理有效地预测日常消耗，并且应用随机优化方法。 输入数据是影响消耗过程的因素的定义指标。 这些指标在随机过程中进行采样。

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