Forecasting the Cost of Water Using a Neural Network Method in the Municipality of Isfahan

Authors

1 Assistant Professor, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran

2 MSc, Department of Mechanical Engineering, University of Isfahan, Isfahan, Iran

3 MSc, Department of Mechanical Engineering, Semnan University, Semnan, Iran

Abstract

Decision making on budgeting is one of the most important issues for executing managers. Budgeting is a major tool for planning and control of projects. In public and non-profit organizations and institutions, estimating the costs and revenues plays an important role in receiving credit and budgeting. In this regard, in the present paper the case of Isfahan municipality is considered. One of the main expenditures of the 14 districts of Isfahan is the costs related to water. Predicting the total cost of water helps the municipality of Isfahan to optimize the water use in its 14 urban zones. Thus, in this study the total cost of water in the districts of Isfahan is estimated using regression analysis and neural network models. Then the results of the methods are compared with each other to minimize the deviations from the approved budget. Finally, the neural network method is selected as the main simulation method for forecasting the total cost of
water in the districts of Isfahan.

Keywords

Journal of Optimization in Industrial Engineering

Volume 5, Issue 11
Summer and Autumn 2012
Pages 73-85

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