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Prediction method of energy efficiency ratio of central air-conditioning operation based on extreme learning machine

机译：基于极端学习机的中央空调运行能效比预测方法

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摘要

On the premise of accurate prediction of the energy efficiency ratio of the water system of the central air-conditioning unit, the research on the optimization and control of the central air-conditioning system can be better realized. Aiming at the characteristics of high data dimension and large data volume of central air-conditioning unit equipment, a central air-conditioning energy efficiency ratio prediction method based on extreme learning machine is proposed, which can effectively help the energy-saving research of central air-conditioning system. This paper selects the operating data of the central air-conditioning system of a large building, constructs an extreme learning machine data set, builds an extreme learning machine model through the training data set, and determines the optimal number of hidden layer nodes; then uses the test data set and different extreme learning machine models to predict The results are compared, and the number of hidden nodes in the prediction model of the extreme learning machine with the best performance is obtained.
机译：在中央空调单元水系统的精确预测的前提下，可以更好地实现对中央空调系统的优化和控制的研究。针对高数据尺寸的特点和中央空调单元设备的大数据量，提出了一种基于极端学习机的中央空调能效比预测方法，可以有效地帮助中央空气节能研究 - 监管系统。本文选择了大型建筑的中央空调系统的操作数据，构造了一个极端的学习机数据集，通过训练数据集构建了极端学习机模型，并确定了隐藏层节点的最佳数量;然后使用测试数据集和不同的极端学习机模型来预测结果进行比较，并且获得了具有最佳性能的极端学习机的预测模型中的隐藏节点的数量。

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