期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2021
卷号：3
期号：9
页码：733-739
DOI：10.35629/5252-0309520521
语种：English
出版社：IJAEM JOURNAL
摘要：Energy consumption has been broadly studied within the laptop architecture discipline for decades. While the adoption of electricity as a metric in device gaining knowledge of is rising, most people of research is still by and large centered on obtaining high stages of accuracy without any computational constraint. We accept as true with that one of the motives for this loss of hobby is due to their loss of familiarity with techniques to evaluate energy intake. Lack of hobby is due to their lack of familiarity with techniques to evaluate energy intake. To address this undertaking, we gift a overview of the one-ofa-kind methods to estimate power intake in popular and device learning applications in particular. Our intention is to offer useful guidelines to the system gaining knowledge of network giving them the essential expertise to apply and build particular power estimation methods for machine learning algorithms. This study addresses that venture with the aid of providing a overview of the key tactics to estimate strength intake from the laptop architecture field, mapped to machine studying programs. We additionally describe the modernday techniques to estimate power intake mainly for statistics mining and convolutional neural networks.
