Mathematical Exploration of B2C Electronic Commerce architecture via Back propagation Network Learning Algorithm

Provided by: International Journal of Computer Science and Network Solutions (IJCSNS)
Topic: Big Data
Format: PDF
In this paper, the authors assess the technique of back propagation neural networks to appraise the average response time of B2C electronic commerce architecture. In order to delineate the response time, diverse array of user requests were engaged per unit time. Furthermore, engagement of Back Propagation Network Learning (BPNL) algorithm is used to summarize the average response time and augment the enactment of the system. The comprehensive paper does the comparative investigation to express the average response time for ANN enabled and without-ANN-enabled algorithm.

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