The domain considered, comprises proposed research work applied to investment in agro-based industrial sector using Expert
Systems techniques, CASE technology, Zachman’s Framework, financial analysis, risk analysis, and qualitative analyses. The knowledge-based system, called AIES, enables users to determine the proper feasibility assessment for installation of agro-industries, which encompasses relationships among the many factors of the decision-making process across the domains of economic, financial, legal, technical, marketing, and environmental feasibilities. This system is not limited only to agro-based industries but may be extended to any type of industry and to any long-term investment problems. In view of the existing opportunities and challenges faced by the economies of the Kyrgyz Republic and Pakistan, installation of agro-based industries seems to be the best alternative for faster economic growth and rural poverty alleviation. The AIES consolidates
57 decision-making factors into economical, technical, and general feasibilities in the proposed
Expert System’s Model, along with weight assignments to these parameters. Certainty Factors’ addition formula was adopted to evaluate the ES model. The AIES elicits, extracts, and consolidates the knowledge of experts of a variety of disciplines, like, Managerial and Agricultural Economics, Industrial Management, Statistics, and Information Technology, heretofore unfamiliar with one another’s fields. AIES clarifies and expands existing methods and introduces additional topics, such as risk analyses, and symbolic evaluation of qualitative and uncertain facts, to gives users a chance to assess and understand the system’s reasoning ability and complexities involved in assessment of feasibility for capital investment, thereby improving the user’s confidence in the Expert System’s consultation. The proposed expert system has vast capabilities of dynamic changes and must be advanced incrementally in the span of its life. The biotechnologies of agro-products and their wastes, Traveling Salesman problem, and site location selection for an industry are the most suitable candidate systems for Genetic Algorithms technique (GAs), which may be linked with AIES. The database provides a framework for integration of ES with DBMS leading to another field of research as ESDBMS.