Study And Practice Of Web-based Rice Production Expert System

According to the problems and trends in studying Agricultural Expert System (AES), this paper discusses principles and techniques of developing expert systems for crop production, and development of Web-based Rice Production Expert System (WRPES). WRPES uses the structure of Web Browser/Web Server/Database, and is built based on PAID4.0 which is a updated tool for Expert System (ES) building. It integrates theories, experiences and updated research fruits of experts which are authoritative in localagricultural (rice) field. It can be used in all phases of rice production--before ricesowing, when rice growing and after rice harvesting. It can give managing suggestions in different phases of rice growing and measures for optimizing and controlling the ecosystem of rice field. It also provide some other functions, such as, doing fuzzy prediction on rice yield, diagnosing diseases of rice, recognizing pests and weeds in rice fields, and tracking prevention and cure of the diseases, pest and weeds.The research contents and results of this paper presents as following: 1. Development of knowledge base.Knowledge base is a hardcore of WRPES, and it is a key to the function of WRPES. The performance of an ES mainly depends on the quality and quantity of knowledge in knowledge base. Development of knowledge base includes knowledge acquisition and knowledge expression.Knowledge acquisition is on how to collect the wanted knowledge from all kinds of knowledge sources. The sources where the knowledge of WRPES comes from are publications, experiences of experts and some complementary experiments etc.Knowledge expression is on how to formalize the knowledge collected to be stored and used by computers. Considering the complexity and fuzziness of knowledge, the characteristic of practical questions solved by agricultural experts, this paper puts forward a knowledge expressing method called "weighted fuzzy logic producing rules + model" which derives from traditional "producing rules". The method translates all kinds of knowledge, such as, certain knowledge and fuzzy knowledge, qualitative knowledge andquantitative knowledge, into one format, which makes all kinds of knowledge fit the reasoning and interpreting mechanism of PAID4.0 better.Directed by experts of agricultural (rice) field, we take long time to collect the knowledge and experience of experts in agricultural (rice) field, and finally obtain 2858 items of knowledge rules for the knowledge base of WRPES.2. Development of foundational data base.Because soil data, meteorology data, geography data etc, are reasoning proofs or model parameters which can be primary information of ES decision-making, foundation data base is a support base of knowledge base and model base. After designing structures of data tables of foundation data base and then inputting data, we build soil database, agro-meteorology database, agricultural primary information database and rice variety database etc with SQL Server 2000.3. Development of model base.In this part, we discuss fuzzy clustering prediction models on rice yield, diagnosing models of rice diseases, recognizing models of pests and weeds in rice fields. All models present not only in model base but also in knowledge rules of different function modules.4. Spreading application of WRPES.Spreading application of WRPES is the final end. After appraisement, check and accept, WRPES is applied in large demonstrating areas of Hunan (including Changde, Yueyang etc). During the application, we summarize a "321" three-dimensional spreading mode which means "three aspect drive, two network parallel, man and computer tied in, three-dimensional advance", and an application mode called "company + base + famer".