| 摘要 |
<p>PROBLEM TO BE SOLVED: To predict various plant loads by an analyzable neural network, and to provide a steady simulator, an optimum operating method and an optimum designing method of a plant. SOLUTION: Various kinds of loads such as power load, thermal load, air load and the like are predicated by using the neutral network of an analyzable hierarchical structure wherein a fully-coupling part having plural input layer elements and plural intermediate layer elements are provided, and the intermediate layer elements are coupled to all of the input layer elements, and a loosely- coupling part wherein the intermediate layer elements are coupled to a part of plural input layer elements. The neutral network is built by the learning using result values of input factors such as a weather condition, a day of the week, the distinction of business day and holiday, an operating condition of the plant, an operating pattern of a plant elements and the like, and result values of various loads, and the weather condition of the predicted date as a predictor is inputted with other input factors to predict the objective plant load.</p> |
