Building Energy Model for Citypulse Smart City Traffic using Trees.M5P
Renuka sagar1, U Eranna2
1Renuka Sagar, Research Scholar, Completed M. Tech CNE) Under Visvesvaraya Technological University (VTU), Belgaum, Karnataka, India.
2Dr. U. Eranna, Prof. & HOD, Dept of ECE, Birla Industrial & Technological Museum, Kolkata, India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 752-754 | Volume-8 Issue-5, January 2020. | Retrieval Number: E4959018520/2020©BEIESP | DOI: 10.35940/ijrte.E4959.018520
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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: The main objective of WSN is to increase network lifetime. Energy models are required to achieve this objective[1]. These models reduces no of sensors in any physical condition and achieve higher accuracy. In this paper, we present regression model to identify a relationship between a target variable and attributes in the dataset. We also present statistical[2] relations between target variable and observed variable. Simulation results show that trees M5P builds energy model and classifies the dataset with the Average measured time, Average speed and vehicle count to extend the network lifetime .
Keywords: Linear Regression, Energy model, average speed, vehicle count.
Scope of the Article: RF Energy Harvesting.