Study On Group Decision Support Systems Of Agricultural Project Investment

Futher research led the author to hold about the existence of multi-attributes characteristic of decision making criteria, fuzziness of decision making environment, ill-structured of decision making problems, and group decision making in the agricultural project investment decision making. Therefore, author proposes three treatment hypotheses as following: It is an effective method to deal with multi-attributes problems that analysis hierarchy process (AHP) may solve multi-attributes problems in agricultural project. Applying fuzzy decision making methods may solve the fuzziness of decision environment in agricultural project investment. Solving ill-structured problems by group decision support systems, inducing decision makers to present and understand the problems by the use interacts with the computer system, improving the decision making effectiveness by electronic meeting. These measures may enhance the decision effectiveness in agricultural project investment.Put above hypotheses together we can propose a comprehensive solving alternative to in hence decision making effectiveness for agricultural project investment: To build fuzzy analysis hierarchy process based on entropy and fuzzy multi-attributes decision making models in the model base of agricultural project investment GDSS. We can to adopt group advices and experiences, promote the opinion integration and improve the solving methods of ill-structured problems that supported by group decision support system. According to this conceptual framework I build the system structure and model base system of agricultural project investment GDSS, to propose a new way for enhance the decision making effectiveness of agricultural project investment.The author proposes that framework and prototype provide technical features aimed at facilitating group communication, inducing decision makers to select and apply appropriate decision methods. It is effective that F-AHP model, based on entropy weight, is applied to agricultural competitive development cases. Using the F-AHP model algorithms that based on fuzzy number and interval arithmetic solve the multi-attributes and fuzzy problems of agricultural project appraisal. Using entropy weight ranking of F-AHP is more efficiency. Using a-cut and index of optimism X. estimate the uncertainty and preference of decision makers. Through analyzing and comparing author concluded that Chen's model, which is more suitable to group decision making of agricultural project investment, will be included in the model base of fuzzy multi-attributes group decision making of agricultural project investment, and it will be as a primary decision making model.The innovation includes that study on how to improve decision making effectiveness of agricultural project investment by multi-subjects research methodology of agricultural project appraisal, group decision support systems, management decision, fuzzy decision, entropy, etc. This paper proposes a system framework and builds a model base of GDSS for agricultural project investment. There are two points distinguish GDSS from traditional DSS. One is adding an intelligent subsystem based on knowledge, another is adding a group subsystem. In the decision models, solving the following problems of appraisal on agricultural project investment: Compare with the traditionalAHP that the F-AHP based on entropy weight can apply to fuzzy decision making of agricultural projects. Model's scale is more accurate. Using a-cut and index of optimism estimate the uncertainty and preference of decision makers. The paper discusses Lee's (1996) two fuzzy multi-attributes group decision making models, and compares it with Chen's model (2001), applies Chen's model to evaluate multi-industry project of agricultural competitive development.In a word, studying on system framework and decision making models of GDSS for agricultural project investment is an initiated and fundamental research.