Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) Indonesian Journal of Electrical Engineering and Computer Science
Francis Thomas Josh
Karunya Institute of Technology and Sciences
Economics, Econometrics & Finance

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Machine learning based smart weather prediction Rajasekaran Meenal; Kiruthic Kailash; Prawin Angel Michael; Jeyaraj Jency Joseph; Francis Thomas Josh; Ekambaram Rajasekaran
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp508-515

Abstract

Weather forecasting refers to the prediction of atmospheric conditions depending on a given time and location. Weather prediction is essential and it plays a significant role in many sectors namely energy and utililities, marine transportation, aviation, agriculture and forestry to a greater extent. Accurate weather forecast mechanism help the farmers for suitable planning of farming operations that will prevent crop losses. In this work, the weather parameters namely precipitation, relative humidity, wind speed and solar radiation were predicted for few Indian locations using the conventional temperature based empirical models and machine learning algorithms such as linear regression, support-vector machine (SVM) and decision tree. Forecasting of weather parameters, on which agriculture depends, will increase the overall yield and it helps farmers and agricultural-based businesses to plan better. From the current results, it is observed that machine learning (ML) based methods had a better prediction results than the physics based conventional models for weather forecasting with mean square error of 0.1397 and correlation coefficient of 0.9259. The objective of this work is to arrive at an optimized end result and a better weather prediction using the Machine learning models with lesser computational effort.
Energy-efficient multilevel inverter for electric vehicles using wireless sensor network monitoring Nishalini Delcy; Francis Thomas Josh; Kannadhasan Suriyan
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v15.i1.pp130-137

Abstract

This research presents a unique energy-efficient routing strategy aimed at optimizing energy consumption and prolonging network longevity using an innovative clustering probability. Cluster-based routing algorithms facilitate versatile configurations and extend the network's lifetime until the last node ceases operation. This study introduces an energy-efficient hierarchical clustering algorithm for wireless sensor networks (WSNs), enhancing the low-energy adaptive clustering hierarchy (LEACH) algorithm. The objective of this algorithm is to reduce power consumption by the strategic selection of new cluster heads (CH) in each data transfer round and to prevent network conflicts. This objective is accomplished by employing an efficient function to identify the optimal CH nodes in each cycle, considering the current energy levels of the sensors. The suggested technique enhances the cluster formation process by utilizing the reduced distance to the base station. This study findings will enhance packet scheduling algorithms for data aggregation in WSNs to minimize the number of packets transmitted from sensors to CH. Simulation findings validate the system's efficacy in comparison to alternative compression techniques and non-compression scenarios utilized in LEACH and multi-hop LEACH.
Co-Authors Ekambaram Rajasekaran Jeyaraj Jency Joseph Kannadhasan Suriyan Kiruthic Kailash Nishalini Delcy Prawin Angel Michael Rajasekaran Meenal