Support Planning Transformer Overloading with Big Data Analytics
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Abstract
The common problems that most organizations concern are probably income and reliance problems. This research is to bring up the procedures of solving the overloading transformer effecting PEA's income and reliance to develop and support making transformer inspection and maintenance plans. The research is presenting a new procedure to making a transformer status inspection plan by using the Model of Big Data Analytics as a tool to predict transformer status based on the data of transformer rated 22kV belonging to PEA. The abovementioned model efficiency will be presented in form of the original model which is Distributed Random Forest and Gradient Boosting machine compared with a new model 'Deep Learning' and evaluated by RMSE,MSE and R-square principles.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles published in Journal of Industrial Technology Ubon Ratchathani Rajabhat University both hard copy and electronically are belonged to the Journal.
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