This paper presents an application of an artificial neural network model in forecasting urban water demand using MATLAB software. Considering that in any planning process, the demand forecast plays a fundamental role, being one of the premises to organize and control a set of activities or processes. The versatility of the short, medium and long-term prediction that is provided to the company that offers the water distribution service to determine the supply capacity, maintenance activities, and system improvements as a strategic planning tool. Shown to improve network performance by using time series water demand data, the model can provide excellent fit and forecast without relying on the explicit inclusion of climatic factors and number of consumers. The excellent accuracy of the model indicates the effectiveness of forecasting over different time horizons. Finally, the results obtained from the Artificial Neural Network are compared with traditional statistical models.
This research presents an application of artificial neural networks in demand forecasting by using MATLAB Software. Keeping in mind that in any planning process forecasts play a fundamental role, being one of the bases for; planning, organizing and controlling production. It gives priority to the most critical nodes and their key activities, so that, the decisions made about them will generate the greatest possible positive impact. The methodology applied demonstrates the quality of the solutions found which are compared with traditional statistical methods to demonstrate the value of the solution proposed. When the results show that the minimum quadratic error is reached with the application of artificial neural networks, a better performance is obtained. Therefore, a suitable horizon is established for the planification and decision making in the metal-mechanical industry for the use of artificial intelligence in the production processes.
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