To Evaluate Rural Power Consumers Consumption to Detect Power Thieving Activities
Bharat Dangar1, S. K. Joshi2
1Bharat Dangar, Department of Electrical Engineering, Faculty of Technology and Engineering, The M S University of Baroda, Gujrat, India.
2S. K. Joshi, Department of Electrical Engineering, Faculty of Technology and Engineering, The M S University of Baroda, Gujrat, India.
Manuscript received on September 17, 2019. | Revised Manuscript received on October 05, 2019. | Manuscript published on October 30, 2019. | PP: 560-562 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9683109119/2019©BEIESP | DOI: 10.35940/ijeat.A9683.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Power Thieving Activities Evaluation To Rural Areas And Direct Point Connections To Small Rural Consumers Of Weaker Parts Of The Rural Society Is One Of The Major Reasons For Electricity Losses. Poor Quality Of Equipment Used In Rural Areas. Large Scale Rural Electrification Through Long 11kv And LT Lines. Artificial Neural Network Can Be Used To Classification And Detection Of Power Thieving In Rural Areas. Train Algorithm According Standard Features And Conditions Employs In Rural Area. Testing Will Give You Better Idea About Datasets According We Can Take New Decision.
Keywords: Power Thieving, Consumers, Data mining, Support Vector Machine, Sigmoid, power loss, Behavior.