Browsing by Author "Ratnayake, U."

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    A statistical fuzzy inference system for analyzing temperamental groups in neuro-linguistic programming
    (Gampaha Wickramarachchi Ayurveda Institute, University of Kelaniya, Sri Lanka, 2016) Mendis, D.S.K.; Ratnayake, U.; Karunananda, A.S.; Samaratunga, U.
    Neuro-Linguistic Programming describes the fundamental dynamics between mind (neuro) and language (linguistic) and how their interplay affects our body and behavior (programming). Neuro-Linguistic Programming (NLP) is about self-discovery, exploring identity and mission. It also provides a framework for understanding and relating to the 'spiritual' part of human experience. The immediate problem that this poses for a full understanding of human functioning is that the inner subjective experiences of consciousness based in NLP. Manas prakurthi in Ayuverda contributes to the study of personality. Tamas-Rajas-Sattva temperamental groups give rise to the framework of Space-Time-Causation when evolution starts in association with Consciousness Principle in manas prakrti. The objectives should contribute to a better analyzing of the temperamental groups in manas prakrti and to analyze the gap between current state of work and values of NLP. This paper attempts to present a tool to analyze Tamas-Rajas-Sattva temperamental groups that are found in manas prakrti by using a statistical fuzzy inference system. At the initial stage common sense knowledge based on manas prakrti is converted into a questionnaire. Removal of dependencies among the questions in the questionnaire is modelled using principal component analysis. Classification of Tamas-Rajas-Sattva temperamental groups is processed through fuzzy logic module, which is constructed on the basis of principal components. Effective decision making for type of manas prakrti has been derived from sugeno defuzzification technique based on an integrated Principal Component Analysis approach. The statistical fuzzy inference system facilitates an approach to identify the influences to understand the nature of human personality in Neuro-Linguistic Programming.
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    Tacit Knowledge modeling in Intelligent Hybrid Systems
    (2007) Mendis, D.S.K.; Karunanda, A.S.; Samaratunga, U.; Ratnayake, U.
    Knowledge modelling gives the intention of knowledge engineering which applicable for managing information systems. Tacit knowledge is the key issue of knowledge modelling aspect because all knowledge is rooted in tacit knowledge. This paper presents a research, which is incorporated of modelling of tacit knowledge. Here we have used an Intelligent Hybrid system for developing an approach for modelling tacit knowledge. The Intelligent Hybrid system is involved with artificial intelligent techniques, namely fuzzy logic and expert system technology. We primarily used fuzzy logic together with statistical technique of principle component analysis for modelling tacit domains. Tacit knowledge in Ayurvedic sub-domain of individual classification has been acquired through a questionnaire and analysed to identify the dependencies, which lead to make tacit knowledge in the particular domain. In the first place analysis was done using statistical techniques of principle components and the results were not compatible with the experiences of Ayurvedic experts. As such, fuzzy logic has been used to further model the Ayurvedic sub-domain. The result of the modelling of Ayurvedic domain using fuzzy logic has been compatible with the experiences of the Ayurvedic experts. It has shown 77% accuracy in using the tacit knowledge for reasoning in the relevant domain. The development has been done using Visual basic, FLEX expert system shell and the system runs on Windows platform. The Intelligent Hybrid system has been successfully applied for several tacit domains. Performances were very close to handling tacit knowledge by the human expert in tacit domain