ICTACT Journal on Soft Computing (Apr 2015)
A COMPARATIVE STUDY ON THE PERCEIVED APPLICABILITY OF HONEY BEE MATING OPTIMIZATION ALGORITHM (HBMO) AND PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM BY APPLYING THREE FACTOR THEORY AMONG RESEARCHERS IN TAMIL NADU
Abstract
The perceived applicability of honey bee mating optimization HBMO and Particle Swarm Optimization PSO among the research scholars in Tamil Nadu are understudied. The purpose of the present study is to address this dearth in the literature in three ways: (i) providing descriptive data related to the applicability of these algorithm in their area of study. (ii) Applying Three Factor theory to assess the perceived range of applicability of the two said theories and to develop, a theoretically-based model that predicts the applicability and robustness of the algorithm in comparative basis grounded on the perceptual data collected from the research scholars from all over Tamil Nadu. (iii) Attempting to compare the strength and form of correlation between the factors of influence and perceived applicability of the algorithms in the research process by the researchers. Self-report data were collected from Researchers in Tamil Nadu (n = 869), assessing the levels of individual personal belief factors in influencing the scholars perception of applicability of the algorithm for a range of issues, perception based on the results produced by the application of the algorithm. Perceptions formed in conformity with a group of researchers were analyzed through statistical tools. From the findings analysis, it is evident that perceptions of personal belief level and perception based on conformity with peer group perceptions have significant influences in predicting the applicability of the Algorithms. However, the study results suggest that empirical result is based in on the specified context and level of investigation on which it can produce similar or varied outcomes when the study is conducted to larger domain of subjects.
