Price information evaluation and prediction for broiler using adapted case-based reasoning approach
Predicting the upcoming broiler market price is important for the producers in developing their production plan. Effective price prediction model can aid producers to prevent over production or production shortage of broilers in advance. This research proposes an adapted CBR approach for predicting broiler price. The results indicate that the proposed adapted CBR approach demonstrates superior prediction performance than un-adapted CBR approach, CART, artificial neural nets and linear regression with at least 50% less of mean average error. This study finds that adjusting the price of the most similar case by considering the similarity distance to the case being predicted is a key to improve the prediction accuracy of the case-based broiler price estimation model.
case-based reasoning broiler price case adaptation genetic algorithms