Jegadit S Saravanan

Jegadit S Saravanan

He/Him

Incoming MS CS @ UIC, BTech CSE @ AVV,CBE. Founder of DWMC, Robotics Engineer & ML/DL Researcher. Ex-Research Intern at TIFAC-CORE in Cybersecurity

Publications

Enhancing AUV Sensor Precision with Adaptive Genetic Algorithm aided Kalman Filtering

Published in 15th ICCCNT conference, Indian Intitute of Technology Mandi, India, 2024

Accurate sensor data is crucial for the successful operation of Autonomous Underwater Vehicles (AUVs). However, dynamic underwater environments and inherent sensor limitations pose significant challenges. This paper investigates using the Kalman filter to enhance instantanoius sensor data accuracy in AUV navigation by integrating with Genetic Algorithms (GAs). The proposed Adaptive Genetic Algorithm-based Kalman Filter (AGAKF) adjusts filter parameters in real-time using GAs as compared to the existing methods that use batch processing. Extensive simulations and comparisons show that AGAKF achieves superior noise reduction and better signal preservation than the existing techniques, enhancing AUV navigation accuracy in diverse underwater environments.

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AI based parameter estimation of ML model using Hybrid of Genetic Algorithm and Simulated Annealing

Published in 14th ICCCNT conference, Indian Intitute of Technology Delhi, India, 2023

In this study, parameter estimation of ML models, here specifically, random forest classifier was conducted on a heart disease dataset. We have suggested a new approach to machine learning that hybridizes genetic algorithm with simulated annealing for estimating the hyperparameters of the random forest classifier. This application of hybrid optimization helped in increasing the accuracy of the machine learning model by 10% and is very promising in comparison to various different classification methods for this same problem.

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