Knowledge-based technology transfer: hybrid architectures of rules, case-based reasoning and neural nets

In the present environment of increasing rate of global change, knowledge is quickly becoming a key resource, and effective utilization of this resource a key edge. Recently, intellectual or knowledge-based technology transfer using computer-based technology has come under study. Researchers have examined such questions as what is the required process or facilitators to best utilize artificial intelligence to transfer knowledge. The question this paper addresses is the knowledge representation and inferencing mechanism most suitable for knowledge transfer. The paper examines the benefits of using hybrid configurations consisting of rule-based expert systems, case-based reasoning, and neural nets. The paper concludes with four possible hybrid configurations.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>