A statistical fuzzy inference system for analyzing temperamental groups in neuro-linguistic programming

Abstract

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.