Autonomic management by self-optimization for WEINMANN

Abstract

The main goal of autonomic computing is to make the software systems able to manage themselves and minimize the human intervention. Various methods have been used to implement autonomic computing. This research focused on one of the autonomic computing characteristic which is self-optimization. The research tried to implement self-optimization system that helps to get result used to support reports used by doctors for diagnose. To achieve this patient records are collected from sleep disorders and lung function Research Center in Sudan (Army medical hospital) contains 18 attributes from different patients of different situations. And apply case based reasoning algorithm which is problem solving paradigm of artificial intelligence used old experiences as case base in form of problem-solution pair to solve a new problem. The research's result highlights the effect of different similarity measure sand analyzed the performance using accuracy and RMES to select the best similarity measures in similar cases.