Research And Application Of Expert System For Diagnosis Of Animal Diseases

Expert System is an intelligent computer program, which can use expertise and reasoning to solve the problems that can only be solved by domain experts. It has been the researching focus of the artificial intelligence of the whole world.Great benefits have been brought by its application in the fields of agriculture. When an animal shows disease symptoms, it is important to make an accurate diagnosis to support control strategies. Diagnosing disease in animals requires considerable expertise. Only a few experts have the ability to do this, and each expert has his own- specific domain. To retain expertise and to make it more generally accessible, expert system for animal disease diagnosis should be developed.Knowledge acquisition is the "bottle neck" problem in the development of artificial intelligence. It is also a problem in developing diagnostic expert system for animal disease. To acquire accurate knowledge, this paper presents four knowledge acquisition resources for developing diagnostic expert system for animal diseases. They are books, experts, journals and internet/intranets. Their importance are listed as follows: books> experts > journals > internet/intranets. Many domain experts were consulted and their expertise were acquired.In this paper, a knowledge representation method is presented according to the characters of diagnostic knowledge of animal diseases, which represented as IF THEN CF. Signs is a symptom set, and it has all symptoms of a disease. Disease represents the name of one diseases, and every disease has its own number of symptoms. CF is the probability of the disease to be the result of inference when the symptoms is presented. The sum of CF to one disease is 100.Database-based rulebase and other information-bases are designed in this paper. The advantages of the rule-base with such structure is that it can be used and maintained easily, and operated simply. The rule-base with such structure is the result of simulating the information storage and activation of brain.A new way of inference with both forward and backward chains is presented in the paper, it is the result of simulating experts' thinking during the processes of animal diseases diagnosis. This inference contains two parts. On the first stage, forward chain will be used. A set of hypothesis will be got from the information provided by user through forward chain of this stage. Then the inference mechanism will turn to the second stage to test the hypothesisbe presented to user. Otherwise, the inference will repeat this process.Interface,which is important in determining whether a user prefer to use the system.is a communication intermedium between user and system. A designing object of interface is presented in this paper, which is concise,simple and easy to learn.Reuse is the bases of all scientific research. Expert systems of diagnosis for animal diseases share common parts, therefore, if one of such system has been developed, its thought of construction, controls and components can be used in other expert system's construction. In this paper, some reusing technologies have been discussed, which can be used in the development of diagnostic expert system for any diseases of all animal.Finally, all the methods described before have been used in the development of expert system diagnosis for cow diseases. This expert system contains disease descriptions and offers the ability to diagnose diseases in cows. Digitalized photographic pictures and video materials can be showed by system to support an interaction session. The paper describes the development of the system, the structure of the knowledge-base and the inference mechanism. A prototype has been built for diagnosing adult cow diseases. It is proved that those methods are correct and usable.