Farm price prediction using case-based reasoning approach—A case of broiler industry in Taiwan

Abstract

Since Taiwan joined the World Trade Organization (WTO) in 2002, pricing decision has become more essential to the development of the broiler industry. The effective prediction of broiler prices is essential from the viewpoint of the agriculture authority and the Poultry Association, thus a more realistic broiler price structure can assist the government to manage the national production resources more effectively. This research proposes a weighted case-based reasoning (CBR) approach to construct a price prediction model. The genetic algorithm model was adopted to find out the most suitable feature weights for CBR. Previous local production data and economic indices, along with information about imported chicken, were collected to build the prediction model. The experimental results indicated that the proposed CBR approach could exhibit a better prediction performance than the ones exhibited by linear regression, regression tree, and neural nets approaches. The findings also revealed that broiler prices were mostly influenced by the prices of colorful broilers and chicks.