中文摘要：

当为在冬季的一个加热模式的一个热泵系统的部分被表明，为在生气流动下面预言一个 reversibly 使用的冷却的塔(RUCT ) 的表演的一个适应 neuro 模糊的推理系统(ANFIS ) 调节。广泛的地试验性的工作被执行以便为训练和预言收集足够的数据。统计方法例如关联系数，变化的绝对部分和根均方差，被给比较预言并且为模型确认的实际价值。与 ANFIS 预言的模拟结果能被用来相当精确地模仿一个 reversibly 使用的冷却的塔的表演。因此， ANFIS 途径能可靠地被用于预报 RUCT 的表演。

英文摘要：

An adaptive neuro-fuzzy inference system （ANFIS） for predicting the performance of a reversibly used cooling tower （RUCT） under cross flow conditions as part of a heat pump system for a heating mode in winter was demonstrated. Extensive field experimental work was carried out in order to gather enough data for training and prediction. The statistical methods, such as the correlation coefficient, absolute fraction of variance and root mean square error, were given to compare the predicted and actual values for model validation. The simulation results predicted with the ANFIS can be used to simulate the performance of a reversibly used cooling tower quite accurately. Therefore, the ANFIS approach can reliably be used for forecasting the performance of RUCT.