Modeling a Diet Planner for Livestock Using Fuzzy Logic Approach and Ontology Model
Saraswathi Sivamani, Hong Geun Kim, Changsun Shin, Jang‐Woo Park, Yongyun Cho · Advanced science and technology letters · 2016
As a known fact, the basic ontology is not sufficient to handle the vague data to derive a good semantic service, as the modelled ontology has the set of entities with the defined relationship. To overcome this, the fuzzy logic is used to handle the uncertain data, to improvise the performance. This paper proposes the fuzzy type ontology with the knowledge representation in the process of diet planner for the livestock. As the nutrition requirement varies for cow with the age, BMI, and health, the diet for each type of cow differs, in respect to the food served on each day, the fuzzy technique is used to decide the amount of food needs to be served for the livestock. This papers shows the effective way to drawn the perfect diet plan for the livestock.