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The key trend of Agriculture development is precision Agriculture, therefore new and new ADSS Agriculture Decision Support System regarding precision Agriculture illustrate. For that I learn GIS, Web Technologies and Data Mining and implement into ADSS. Intelligent Expert System using GIS Technology according to the foreign advanced experience was forward therefore highly Agriculture production, and the key technologies to implement this system are explained in detail.
Keywords: Agriculture Decision Support System, Geography information System, Data Mining.
In 1980, traditional Agriculture has the problem of environment pollution, poverty of living, waste of resources, etc. and to understand development of Agriculture, researcher from the world had been started to consider new farming methods, therefore precision Agriculture came on and equivalent technologies was started. The precision Agriculture means to improve all kind of Agriculture materials such as seeds, water, fertilizers, pesticides, etc. and to adjust all kind of soil and crop management, according to special condition of farming units therefore highly yield of agriculture that can increase economic benefits. The precision Agriculture can utilize the GIS, GPS, RS technologies, therefore to increase better benefit of economy and environment.
After 1980, rapid development of Network, Artificial Intelligence, GIS and GPS technologies that can afford good technology support for the development of ADSS. GIS application can supervise position and time data to offer decision service and ES application can provide the design for the Agriculture production. With the network technology send Agriculture decision design faster and more convenient to the farmer. It is not provides only a key step to build a decision to guide a farming but also provides a key steps whether or not accomplish the aim of precision. Therefore it is not important only theoretical significance to study and build Agriculture spatial base decision support system but it has practical import.
2. System Principles
Agriculture spatial base decision support system can provides intelligent, networking and visualization services for the managers and producers in Agriculture. It also provides intelligent decision support for the precision fertilization and scientific design for the precision management. System is classified as under.
2.1 Soil GIS
System based on: (a) spatial database menu, the spatial data consist of maps which are saved into Arc view as a relational data document. Map data are analyze by the vector and raster, the attributes are made up of basic information of the soil. All GIS based operation can be performed by spatial data. (b) Map controlling menu, user can select the target map and show all information. (c) Map viewing menu that provides facilities of display, zooming, refreshing and roaming. (d) Map exporting/importing menu, it can export and import map and print the map. (e) Searching and query menu, it is for the search and position search.
2.2Agriculture Intelligent Decision Support System for soil fertilizer using GIS Technology
Through the menus system can mixing information of space database and fertilization database. GIS and Network technology provide the fertilization prescription and intelligence decision for the user of Agriculture production.
2.3Agriculture Expert System ââ‚¬" Soil Fertilization
The main purpose of system is to provide the scientific realize for the precision management. The system consist of knowledge database, human machine, inference machine, comprehensive database etc. it is build up the fertilization database. Fertilizer cannot utilize once, but realized in few stages. Agriculture experts and technical persons have good experience and knowledge, therefore using expertââ‚¬â„¢s knowledge and build up the fertilization knowledge database.
2.4Agriculture Model System ââ‚¬" Soil Fertilization
Fertilization Agriculture model system, which studies nutrient absorptive of crop and fertilizer utilization rate of different farming area of different regions, which can help for the fertilization decision.
3. System Architecture
Figure 1: Architecture of Agriculture Intelligent System
KS-Knowledge System, DM-Data Mining, SS-Spatial System, MS-Model System, WS-Way System, GS-Graph System.
System based on distributed pattern of client server mode. The user browser supplies human interface. Application server performs the services of GIS System, Expert System and Decision Support System. Database server manages all kind of database such as knowledge, spatial, model, method and graph databases.
In the system GIS system is a core. GIS system describes different attributes of Agriculture especially for Farmland. GIS system performs map analysis, map conversion and geography statistics. Knowledge, Method and Model databases are responsible for the management and maintenance of fertilization. According to farm crop category and fertilized plot, system makes available fertilizing scheme for the user by the cooperation machine. System DBA manages all types of databases. According to the demand system can accomplish data mining using spatial data and perform analysis and knowledge discovering by the warehousing techniques.
4. Voice Technologies
Development of Agriculture Intelligent Expert System used following technologies.
GIS System runs through the decision making process in Agriculture for the soil data, nutrient and crop yield. GIS develops and its usages are more flexible and more convenient to develop. MacObjects2.4 Window Edition is an element model of GIS. VC.NET and ASP.NET are used to develop the system.
4.2Information Driving and Drawing Technology
Information drawing and driving technology is really expanding and extending searching technology over the internet. For the decision making data can be drawing and driving easy on internet. System will have good character of interaction and good user friendly within highly authentication.
System work with bulk weight of spatial data therefore database management system have not been able to manage effectively. Data mining technique through the spatial data such as relationship rules, mathematic analysis, and space classifying and cloud theory can determine the useful data from the spatial data to afford domain expert for the revise system.
Decisions making to the user, DSS not only need Graph Database, Spatial Database, Model Database and Method Database but also need excellent software support of knowledge and experience base. Cooperation machine solve this problem. Cooperation machine is a software system that can consist of several databases and communication and coordinate among its.
Agriculture Intelligent Expert System using GIS Technology is considered by merging GIS with Network Technology that can perform networking, image and visual information, intelligent and decision services to the agriculture manufacturer. System based on relationship between fertilizers, soil, and farm crop yield and to guide agriculture production therefore improve agriculture product quality, increase agriculture production and improve fertilizer utilization. This can change traditional way of agriculture and realize precision agriculture that will modernize my country.