Decision Support System for Dairy Cattle Management Using Computational Intelligence Technique

Abstract

The good yield of dairy cattle relies upon the quality of the environment and genetic characteristics. This research created a 2-level data classification model for cattle. The data set contains environment of the animal house, factors related to cattle health, nutrition of food and body integrity scores based on the physiological characteristics of ruminants of Thailand. This article utilized artificial intelligence technology by presenting the application of artificial neural networks to classifying the health of cattle so that farmers can take care for daily cattle properly, since healthy cattle can produce good milk. The results of the predictive health of the model are 3 classes: normal, surveillance and risk. The results showed that the models presented in this research were higher than normal neural network structures. The classification results are verified by experts, indicating that the system can accurately analyze data as much as expert 100%. The developed model applies to web applications to facilitate the utilization of farmers and can be additionally created with future livestock use.