Enhancing the Prediction of Underwater Wireless Communication using Machine Learning Techniques and Related Issues
- Resource Type
- Conference
- Authors
- Saravanan, M.S; Naveen, V.; Kumar, S.Selvin Pradeep; Dilli Ganesh, V; Sivashankar, S; Bhaskar, K. Vijaya
- Source
- 2023 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI) Data Science, Agents & Artificial Intelligence (ICDSAAI), 2023 International Conference on. :1-5 Dec, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Wireless communication
Training
Logistic regression
Wireless sensor networks
Linear regression
Prediction algorithms
Underwater acoustics
Novel Logistic regression
Linear Regression
Wireless Sensor Network
Acoustic Wireless Sensor
Underwater Acoustic Wireless Sensor
- Language
This research aims to enhance the prediction of underwater wireless communication for underwater wireless sensor networks using Logistic Regression compared with Linear Regression Algorithms. To forecast the functionality of underwater wireless sensor networks Linear Regression and Novel Logistic Regression algorithms were used with different training and testing splits with Underwater Acoustic Wireless Sensor. A sample size of 20 (Each 10 from Group 1 and Group 2) is calculated by fixing a G-power of 0.8, alpha and beta values of 0.05 and 0.2, and a confidence interval of 95%. With a statistical significance value of 0.001 (p