Predicting Human Position Using Improved Numerical Association Analysis for Bioelectric Potential Data
Bioelectric potential of plants as a biological monitoring to detect a human behavior is very interesting to investigate. One benefit is to know the human positions in a room. This study used association analysis which optimized by combination particle swarm optimization with Cauchy distribution, we called PARCD method. Real data sets of the bioelectric potential plant were used to obtain rules and to examine the accuracy. This proposed method shows that the number of rules generated and matched from PARCD method is better than previous method. Furthermore, the proposed method performed a robust prediction with the competitive accuracy.
KeywordsBiological monitoring Bioelectric potential of plant Position estimation PARCD
This work was supported by JSPS KAKENHI Grant No. 17K00783 and STMIK AMIKOM Purwokerto, Indonesia.
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