Abstract
Cattle is one of the main concerns of people and companies in various countries of the world. This paper built the architecture of the cattle diseases by combining the characteristics of an expert system with a neural network Expert system focuses on diagnosing the possible diseases that affect the life of cattle through constructing knowledge bases. While the Radial base functions, a neural network is proposed for the cattle diseases treatments. A tightly coupled model is used to implement a hybrid intelligence technique for diagnosing and Treatment cattle diseases. The result generated by the system was enough to demonstrate its performance.
Highlights
The EXPERT system applies artificial intelligence(AI) technical based on one or more knowledge
Expert system in the field of aquatic products started in the early 1990s in aquaculture research and development of some experts in the field of disease, disease diagnosis, fishery resource assessment, etc. system [3], such as the networked freshwater shrimp culture expert system [4], fish disease diagnosis and prevention expert system [5,6], fishery resource assessment Home system, in terms of system function, interactivity, operability, etc
Expert systems and neural networks are beneficial in specialized fields; they are occasionally given restricted solutions to deal with specific challenges
Summary
The EXPERT system applies artificial intelligence(AI) technical based on one or more knowledge. Experts provide it to analyze and solve problems in specific areas knowledge, experience and methods, summarizing and forming rules, using software Implemented and stored. ANN has a non-linear mapping function, which, using automated input learning, can approximate any complicated non-linear mapping with arbitrary precision and output samples, so it is suitable for modelling the reasoning process of TCM diagnosis.Hao Yanchao [9] used the neural network method to construct a knowledge. In 2015, Zeinab Abrishami and Hamid Tabatabaee [13] used two Artificial intelligence methods with a knowledge base system; they designed a fuzzy expert system with a multi-layer connectionist to diagnose hypertension.
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