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实行负荷预测是空气调节系统优化运行的基础,如何选择工程应用切实可行的方法,仍然是一个值得探讨和研究的问题。支持向量机(SVM)算法在解决小样本、非线性及高维模式识别中表现出许多特有的优势。本文将支持向量机算法引入空调负荷预测中,对深圳市夏季六、七月份的逐时空调负荷,分别用SVM模型和armax模型进行了训练和预测,结果表明SVM模型适用于空调负荷预测,具有很好的泛化能力。
The implementation of load forecasting is the basis of the optimal operation of air-conditioning system. How to choose a practical method for engineering application is still a problem worth exploring and studying. Support Vector Machine (SVM) algorithm has many unique advantages in solving small sample, non-linear and high-dimensional pattern recognition. In this paper, the support vector machine (SVM) algorithm is introduced into the air conditioning load forecasting. The summer air conditioning loads in June and July in summer are respectively trained and predicted by SVM model and armax model. The results show that SVM model is suitable for air conditioning load forecasting, Very good generalization ability.