Abstract

In literature there are many methods for forecasting time series and grey system theory based methods are one of them. Grey system based models need little origin data, have simple calculate process and higher forecasting accuracy with lower estimation errors, they have been widely used in the prediction of a lot of research fields. Grey theory, originally developed by Deng (1982). Grey System Theory focuses on model uncertainty and information insufficiency in analyzing and understanding systems. Recent years, researchers have worked to propose new models that incorporate the grey prediction theory with theories to enhance the forecasting precision. Common part of these purposed models to focus on improving the grey predictive abilities to obtain higher forecasting accuracy. Genetic algorithm is one of the most known metaheuristic techniques. It is population based random search procedure that starts with random initial population. In this study genetic algorithm metaheuristic used to supplement the grey prediction model and determine the grey model coefficients. Also the grey forecasting models have been developed and compared with genetic algorithm implantation.The analysis has been done for the period of 2011-15 of the advertising expenditure in the print media namely magazines and newspapers in the Sultanate of Oman, and predictions for the year 2016. Genetic algorithm based grey prediction models used and compared with grey prediction models. Genetic algorithm outperformed basic grey prediction models. Purposed methods used for generating forecast models for Oman Media Outlook dataset. Time series include net advertising spends with type Newspapers, Magazines and Total spends. We generated 4 models for these time series and used GM(1,1) and BGM(1,1) methods and their GA integrated models namely GA-GM(1,1) and GA-BGM(1,1). Models’ results of three type ad spend dataset show that GA integrated GA-GM(1,1) and GA-BGM(1,1) models make the forecast with lower errors than GM(1,1) and BGM(1,1) models. From analysis results it can be seen that there is a steady increase of expenditure in both the media. GA and BGM models show that the increase is to a total of 80,72340248 - 81,05404513 and 81,52535954 – 82,39371685 respectively. The upward trend represents increasing creativity from the producers and the changing tastes and requirements of the readers.

Keywords: Genetic Algorithm, Grey Prediction Method, Grey System Theory