Comparative between cost prediction using statistical methods and neural networks

Subject Areas : Management Accounting

امیر محمدزاده ¹ (مسئول مکاتبات)
نسرین مهدی پور ² (ندارد)
آرش محمدزاده ³ (ندارد)

Received: 2011-10-23 Accepted : 2011-12-06 Published : 2011-09-23

Keywords: Isfahan municipality, Regression Model, Artificial Neural Networks, Forecasting, cost of water, Prediction,

Abstract :

Prediction of total cost of water helps the Isfahan municipality to optimize thewater usage in its 14 urban zone. The total cost of water, basically, depends ondifferent parameters. Generally, the analytically prediction of the total cost is verydifficult if not impossible. Thus, applying intelligent systems such as neural networkmodels can be a good alternative. In this paper, using multi-layer perceptron neuralnetwork and error back propagation algorithm, the total cost of municipal water in theIsfahan municipality is calculated based on parameters such as per capita populationand area of each urban zone. In this paper, a model for simulation and prediction ofthe annual total cost of water in Isfahan municipality is developed. The simulationmodel is developed using the regression and the neural network model is built usingdata from 2004 to 2009. Finally, the neural network method is selected as the mainsimulation method for forecasting the total cost of water in the 14 urban zones ofIsfahan.