Cloud-based electricity consumption analysis using neural network. (28th November 2019) - Kumar, Nand; Gaidhane, Vilas H.; Mittal, Ravi Kant
In recent years, optimisation of the resource usages is necessary to analyse and understand the energy consumption pattern. In the literature, analysis has been carried out using the algorithms, which needs many assumptions, and meeting all the assumptions in practice is a very difficult task. However, there are other methods available to analyse and understand the energy consumption. In this paper, an efficient approach for energy consumption pattern analysis is proposed. It is based on the Levenberg-Marquardt algorithm-based Neural Network (LMNN) and clustering technique. The energy consumption data is collected from the educational institute building using smart system. The various experimentations are carried out on the collected real time database. The experimental results illustrate that the proposed approach is effective and computationally efficient for consumption pattern classification. The performance of the presented approach is found superior to existing clustering approaches.