Deep Learning is a function of AI that duplicates the mechanisms of human thought in the processing of information and selection processes. The aim of this study is to apply a technology known as SVMHTMC to improve deep learning. The HTM Cortical Learning Approach and the Support Vector Machine have been combined in this suggested algorithm. The deep learning technique is based on the assumption that the mean absolute percentage error is reduced. Aside from the overlapping duty cycle, the high proportion of which shows the speed of the classifier’s processing function. The findings demonstrate that by halving the value, the suggested set of criteria minimizes the absolute proportion of mistakes. In addition, raise the percentage of overlapping duty cycles by 17%.
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