Research On Rice And Wheat Combine Selection And Its Decision Support System

In recent years, in our country the production and sale of combines have increased rapidly. At present, the combine's retained quantity of our country is about 300 thousand suits, which have improved the machinery harvesting level of rice and wheat, and improved the laboring conditions and created distinct social benefit and economic benefit. However, because of the technical difficulties, low standardization, low all-purpose capacity and economic problems etc., all of these factors restrict the development of the rice and wheat machinery harvesting market, and then the machinery harvesting level is still low. Another reason is that we always follow experts' subjective appraisements and experiences to select combines, but these experiences are lack of reliability sometimes.At present, in our country the general existing problems on rice and wheat combines are high harvesting operation costs and low efficiency of fund using, and we are still lack of practicable way to make field planning and select combines compared with developed country. In order to solve these problems, this thesis, referring to domestic and foreign main research achievements and integrating the actual situation of Co., Ltd. of agriculture reclamation Group of Jiangsu province, developed Decision Support System (DSS) of rice and wheat combine selection by agricultural intelligent system as platform. This DSS is composed of five components, including user interface (person and computer dialoguing system), intelligent decision module, database and its management system, knowledge base and its management system and data-querying module (including fact-querying and result-querying).By convenient user interface, user can directly input decision-making parameters such as prospective harvesting crop areas, harvesting crop type, conduction of straw return to fields or not, reliability and fittings provisions requirement and so on. Then the intelligent decision module uses data in the database (in the database storing initial data about combines' size, power, actual productivity, average fuel consumption, purchase price, reliability, fittings provision, feeding mode and operators' wage etc.) and exerts experts' experiences and knowledge stored in knowledge base to deduce and explain through considering all above decision parameters. In this process this system can suggest user some rice and wheat combine models (probably more than one) that satisfies therequirement, and then this system calculates these combines' harvesting unit costs and selects the combine with minimum unit cost among these as the best combine. This system is developed by agricultural intelligent system developing platform PAID4.0 (stand-alone version), which has convenient user interface that makes farmers can easily use it without any computer knowledge. User only has the right to input data, make decision and query.The research result shows that this system can be used to guide user to select combines effectively, whdch can avoid unilateralism and blindness of traditional selection through experience. Based on minimum unit cost to select combine, we can effectively improve the fund return rate, and then increase the economic benefit of agricultural production.