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Title: Water Wave Optimization Algorithm for Medical Datasets
Authors: Mittal, Lokinder Singh
Kumar, Yugal [Guided by]
Keywords: Clustering
Water wave optimization
Medical datasets
Issue Date: 2019
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: Clustering is a tool for data mining used to extract the hidden information of various structures and “clusters” found in large data sets. In the fields of science and engineering, it is observed that the trend has shifted toward the use of nature-inspired computing techniques. The report presents the new meta-heuristic, that is, the Water Wave Optimization (WWO) technique for solving various global optimization problems. Vibrating Particle System is population based meta-heuristic algorithm based on the damped free vibration of single degree of freedom system. We have evaluated the proposed algorithm on a set of 5 benchmark datasets based on “health care” taken from the UCI Machine Learning Repository. The computational results show that WWO outshines the other state-of-the-art algorithms in terms of calculations and accuracy measures.
Appears in Collections:B.Tech. Project Reports

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