Sales forecasting is one of the most crucial issues addressed in business. Control and evaluation of future sales still seem concerned both researchers and policy makers and managers of companies. this research propose an intelligent hybrid sales forecasting system Delphi-FCBPN sales forecast based on Delphi Method, fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learni...

This paper presents a method of forecasting time series with multiple seasonal cycles based on Generalized Regression Neural Network. This is a memory-based, fast learned and easy tuned type of neural network. The time series is preprocessed to define input and output patterns of seasonal cycles, which simplifies the forecasting problem. The method is useful for forecasting nonstationary time s...

Sri Lanka is mainly an agricultural country and about 40 per cent of its working population engaged in agriculture island-wide. Rice cultivated during two seasons; Maha season (October-March) usually accounts for 65% annual production with the remaining 35% coming from Yala (April-September). The objectives this study are to investigate present trend paddy develop most appropriate time series m...

This paper addresses the problem of forecasting daily stock trends. The key consideration is to predict whether a given will close on uptrend tomorrow with reference today’s closing price. We propose model that comprises features selection model, based Genetic Algorithm (GA), and Random Forest (RF) classifier. In our study, we consider four international indices follow concept distributed lag a...