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Top1.0 Introduction
As per the study paper of Jennex (2005), Knowledge Management (KM) may be defined as the practice of selectively using knowledge from previous experiences of making decisions to current and future decision-making process with the main objective of improving the organization’s effectiveness. In this context, it has viewed a Knowledge Management System (KMS), as that system which is created to facilitate or improve the capture, storage, retrieval, transfer, and reuse of knowledge. The perception of KM and KMS is that they holistically combine organizational and technical solutions to achieve the goals of knowledge retention and reuse to ultimately improve the effectiveness of organizational and individual decision making.
Further, it has been pointed out by Jennex and Olfman (2006) in their research paper that for successful implementation of KM in an organization and for ensuring strong quality of KMS, it is necessary to give focused attention towards strengthening KM support tools and their architecture as well as properly maintaining the same. The same in turn is also expected to provide proper knowledge maps of the databases.
In this context, Soft Computing (SC) technique being a part of Artificial Intelligence (AI) may be considered as a KM support tool. In fact, the Soft Computing (SC) technique consists of several fields of Artificial Intelligence (AI) namely, Artificial Neural Networks (ANNs), Fuzzy Logic (FL), Genetic Algorithms (GA), Machine Learning (ML), Probabilistic Reasoning (PR), etc. Hence, SC is a new paradigm in computing based on a creative mix of comparatively newer computing techniques as mentioned above.
Thus, Soft Computing (SC) may be considered as the combination of various newly emerging techniques, whose goal is to exploit tolerance for imprecision, uncertainty and partial truth, so as to achieve tractability, robustness and low solution cost. In effect, the role model for soft computing is the human mind. The basic ideas underlying soft computing in its current form have links to many earlier research studies namely, Zadeh’s 1965 paper on fuzzy sets; the 1973 paper on the analysis of complex systems and decision processes; and the 1979 report (1981 paper) on possibility theory and soft data analysis.
Basically, Soft Computing (SC) is having the capability of effectively dealing with uncertainty, vagueness, imprecision and sub-optimality aspects in data. In fact, SC is having similarity with the human problem-solving methods as well as learning processes. Thus, SC can be gainfully used to solve problems where classical mathematical methods are complex and/ or not feasible to apply due to involvement of very large amount of data and/ or lack of theoretical background knowledge. During the recent years, quite a large number of successful commercial, industrial, economic, finance and business applications of soft computing techniques have been developed.
In the present paper we have taken into consideration several selected schemes/ programs pertaining to different Central Ministries/ Departments/ Sectors of Government of India, based on certain criteria (described later in this paper) and observed that proper Knowledge Management System (KMS) can be developed and implemented in such cases using ANN based soft computing input output model as an effective tool for the same. Further, we have analyzed how the various input and output parameters/ variables (both physical and financial parameters/ variables) associated with each such scheme/ program are related to each other in the light of their basic objectives and the way these can be appropriately represented by an ANN based soft computing input output model in which the expected outputs corresponding to certain inputs can be calculated/ estimated up to a reasonable degree of accuracy.
2.0 REVIEW OF LITERATURES
Over the years quite a number of Soft Computing based techniques (or one or more of its constituent methodologies) particularly Artificial Neural Networks (ANNs) based applications have been developed by several researchers in different fields such as, Engineering, Computer Science, Economics, Management, Business and Finance, Planning, etc. Some of the major works in this regard in the fields of Economics, Finance, Marketing and other areas of Business are briefly discussed below.