| 摘要 |
<p>PROBLEM TO BE SOLVED: To predict a water distribution demand amount with high precision by displaying a graph of the correspondence relation between the water distribution demand amount of learnt data and temperature with output unit values for respective values of an input unit of a neural network while the neural network is learning. SOLUTION: While the neural network used to predict the water distribution demand amount is learning, the learnt data 9 including items of the water distribution demand amount, temperature, dates, days of the week, weather, etc., are stored in a working memory 5 by a neural network learning control part 2. Here, the neural network learning control part 2 learns according to the learnt data 9 in the working memory 5 and various set values in a condition table and updates the combination coefficient between an input layer and an intermediate layer and the combination coefficient between the intermediate layer and an output layer. After the learning is finished when learning end conditions in the condition table are met, the graph of the correspondence relation between the learnt data 9 and water distribution demand amount is displayed on the device 12 through an output control part 7.</p> |
