Comparative Analysis of Machine Learning Techniques in Sale Forecasting

Abstract

Forecasting is a systematic attempt to examine the future by inference from known facts. Sales forecasting is an ballpark figure of sales during a specified future period. Formerly, it was a manual process using the mathematical formulas. Due to the advent of computer the process of sale forecasting is fast and accurate. Machine learning, a subfield of Artificial Intelligence, has many algorithms that are used for forecasting. The aim of this research paper is to present a comparative analysis between the traditional methods of forecasting and machine learning techniques. A new technique known as combine approach which constructs from both moving average and ANN and interesting results so obtained are presented here. Experimental setup uses MATLAB.