Retraction Notice: Performance Analysis of Multi-objective Data Placement Technique and Sine Optimization Algorithm to Measure Prediction in Large Volume of Data Storage
H. Sudarsan Kumar Raju, M. Nalini, P. Senthil Murugan · 2022 International Conference on Cyber Resilience (ICCR) · 2022
The motto of the study is to optimize the storage locations using a multi-objective data placement technique algorithm and sine optimization and comparing their accuracy. Multi-objective data placement technique algorithm (N=10) and sine optimization algorithm (N=10) was iterated 20 times to optimize the data. Multi-objective data placement technique has significantly better accuracy (99.99%) compared to sine optimization algorithm (99.94%). The statistical significance difference 0.01 (p¡ 0.05 independent sample test) value states that the results in the study are significant. With the limits of the study, a multi-objective data placement technique with credit card fraud detection data offers the best accuracy in data optimization.