Recommended Framework for Identifying the Best Project Proposal using Risk Evaluation and Prediction

Abstract

Data Mining plays a major role in Knowledge Discovery using various domains. Decision Making and Clustering is an important concept to group the related information and make the better decisions accordingly. Risk Assessment and Evaluation is a significant task of organizations those provide project grants to Contractors. The success of project and Tender Quotation Amount depends largely on Co-Ordinators ability to determine the risk effectively. This paper focuses the key problem in the corresponding organizations such as good project proposal and bad project proposal. Risk Assessment and Prediction method is applied to evaluate the risk for granting project proposals. This method allows the users for finding the risk percentage to determine whether projects can be sanctioned to a Contractor or not. The proposed idea is tested by extracted data from organizations regarding projects approval and the results proven that it provides better accuracy.