Paper Info
Title
A service model for nutrition supplement prediction based on Fuzzy Bayes model using bigdata in livestock.
Abstract
The paper proposes a novel method in the decision support system for the nutritional management of livestock using the Bayesian model based on fuzzy rules. The objective is to analysis the decision based on fuzzy rules over the nutrition management that helps to improve the health of the livestock. Bayesian logic mainly focuses on the probabilities of the food intake with respect to the Food Intake Amount, Cow Stage and weight of the livestock. The conditional probability of the Bayesian reasoning is introduced along with the fuzzy rule, to determine the health status of the livestock. The fuzzy logic technique helps to decide on the decision system, when there are more than one dependencies. In this paper, the total digestible nutrient of the cow is determined over the period of time to get the rate of probability, and the fuzzy rule is applied to determine the health status of the cow, to predict the nutritional intake in the livestock.
Year
DOI
Venue
2018
10.1007/s10479-017-2490-7
Annals OR
Keywords
Field
DocType
Fuzzy logic, Bayesian model, Big data, Livestock nutrition management, Conditional probability
Data mining,Mathematical optimization,Bayesian inference,Conditional probability,Fuzzy logic,Decision support system,Livestock,Statistics,Mathematics,Bayes' theorem,Bayesian probability,Fuzzy rule
Journal
Volume
Issue
ISSN
265
2
0254-5330
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Saraswathi Sivamani162.33
Jongsun Choi2276.10
Yongyun Cho39821.02