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What is Sales Forecasting

Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
is a quantitative prediction of the future sales pattern. In this paper, this pattern is a time series.
Published in Chapter:
Applications of Evolutionary Neural Networks for Sales Forecasting of Fashionable Products
Yong Yu (The Hong Kong Polytechnic University, Hong Kong), Tsan-Ming Choi (The Hong Kong Polytechnic University, Hong Kong), Kin-Fan Au (The Hong Kong Polytechnic University, Hong Kong), and Zhan-Li Sun (The Hong Kong Polytechnic University, Hong Kong)
DOI: 10.4018/978-1-60566-766-9.ch018
Abstract
The evolutionary neural network (ENN), which is the hybrid combination of evolutionary computation and neural network, is a suitable candidate for topology design, and is widely adopted. An ENN approach with a direct binary representation to every single neural network connection is proposed in this chapter for sales forecasting of fashionable products. In this chapter, the authors will first explore the details on how an evolutionary computation approach can be applied in searching for a desirable network structure for establishing the appropriate sales forecasting system. The optimized ENN structure for sales forecasting is then developed. With the use of real sales data, the authors compare the performances of the proposed ENN forecasting scheme with several traditional methods which include artificial neural network (ANN) and SARIMA. The authors obtain the conditions in which their proposed ENN outperforms other methods. Insights regarding the applications of ENN for forecasting sales of fashionable products are generated. Finally, future research directions are outlined.
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