Self-organized design of virtual reality simulator for identification and optimization of healthcare software components
Abstract: As in the current trend, the virtual reality-based application is very popular in the medical healthcare system to generate a realistic virtual 3-D simulation environment that users can interact with specialized devices. The increasing demand for advancement in the requirement of the virtual environment of healthcare policies as well as the systems needs changes in the simulation environment. In reference to such requirement, the software industry needs improvement in the development process which reduces the effect of software cost, complexity and resource planning. From last few years, optimization in development of simulation environment’s cost-benefit aspects is also the challenging area. In view of such issues, there are several guided (supervised) and unguided (unsupervised) algorithms are using evolutionary approaches and nature-inspired self-organized swarm intelligence approaches have been developed by the researchers for virtual real-time healthcare search based software system. However, there is still a gap in the development of such a simulation environment for identification of the software component. This paper proposes a self-organizing component identification technique using medoid based ant colony clustering algorithms. The proposed algorithm has been compared to classical centroid-based clustering (K-means,CRUD, and FCA) and evolutionary approach(genetic algorithm) on the case study of the virtual real-time healthcare system. For the accuracy and precision of the approach two already studied cases have also been used.
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