A Heuristic Neural Network Approach for Underwater Parametric Prediction at Bay of Bengal

Abstract

The fundamental ocean properties are vital in predicting the earth’s climate. Such predictions are essential for human life in various terrestrial applications. Therefore, to forecast the parametric variations in the Bay of Bengal with less prediction error, a Heuristic Neural Network (HNN) is proposed by optimizing the solutions of Long Short-Term Memory (LSTM) using swarm intelligence by Repeated Iterative Technique (RIT). The existing algorithms have proved better accuracy only during the sea surface prediction of temperature. The proposed HNN model predicts dominant parameters of the Bay of Bengal for its horizontal and vertical variations from 10 to 2000 m depth. The efficiency of the proposed HNN model is verified by comparing the results with recent prediction algorithms in fusion with LSTM, from which the outcome reveals that the proposed HNN model obtains 98.9% for temperature prediction, 99% for pressure, 98.8% for salinity, and 98.1% for density prediction. The results prove overall good accuracy of forecast compared to the existing prediction techniques.

Keywords:

• Bay of Bengal
• Deployment
• Prediction
• Localization
• Ocean Environment
• Ocean Pollution
• Underwater sensor node

ACKNOWLEDGEMENTS

The authors would like to thank the Ministry of Earth Science (MOES) and Directors of INCOIS and NIOT for providing the ARGO dataset for supporting this research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

D. Menaka

D Menaka is currently pursuing PhD in the Department of ECE, SRM Institute of Science and Technology, Kattankulathur, TN, India. She completed her masters of engineering in communication systems from Kongu Engineering College, Tamil Nadu in 2018 and received the bachelor's degree in electronics and communication engineering from Angel College of Engineering and Technology, Tamil Nadu in 2016. Her research interest include exploring and enhancing communication in underwater wireless sensor network operations and protocols, energy harvesting for underwater wireless communication, networking, deep learning and machine learning. Email: [email protected]

Sabitha Gauni

Sabitha Gauni is currently working as associate professor in the Department of ECE, SRM Institute of Science and Technology, Kattankulathur, TN, India. She has done her PhD in wireless communication in the year 2015. Her area of specialization includes wireless communication, signal processing, optical communication, and image processing. She has filed a patent, “An Optical Wireless charging and data Transfer Apparatus”. She is a member of several professional societies such as IEEE, IEI, IETE, OSI and ISTE. She has published several papers in refereed journals.

Govardhanan Indiran

Govardhanan Indiran is currently working as a software engineer at Temenos India Pvt Ltd, Chennai. He graduated from SRM institute of Science and Technology in the field of electronics and communication engineering. He is proficient in wireless communication, networking and optoelectronics and is zealous about quantum physics, sustainable energy and latest evolving technologies. Email: [email protected]

R. Venkatesan

R Venkatesan is currently the group head of Ocean Observation Systems in National Institute of Ocean Technology and a mentor of Sea front facility NIOT. He has done his doctorate from Indian Institute of Science, Bangalore. His area of interest is ocean observations methods, ocean policy and management. He is recognized by World Meteorological Organization and UNESCO IOC for his outstanding services in global ocean data collection. He also received prestigious MTS Lockheed Martin Award as a chair of MTS India section. He also received National Geoscience Award from Honorable President of India. Presently, he is heading Ocean Observation Group of NIOT. He is also vice chairman–Asia of Data Buoy Cooperation Panel; Chair of International Tsunameter Partnership; Steering committee member Asia-Pacific GOOS UNESCO IOC nominated by Govt. of India; Steering Committee Member for Deep Ocean Observing Strategy (DOOS) Project of UNESCO IOC; Country focal Point Belmont Forum Arctic; Member of Joint WMO/IOC Technical Commission for Oceanography and Marine Meteorology (JCOMM). He worked as regional coordinator of South Asian Seas programme of UNEP, SACEP, Sri Lanka. He is a senior member of IEEE and served as chairman during 2016–2018 in IEEE Oceanic Engineering Society (OES) Indian chapter and at preset he is an executive committee member of IEEE madras section. Email: [email protected]

M. Arul Muthiah

M Arul Muthiah is currently working as Scientist-F of Ocean Observation Systems in National Institute of Ocean Technology. He obtained his post-graduation in electronics engineering from National Institute of Technology (NIT), Tiruchirappalli; India. He received National Geo Science award from Honorable President of India for his significant contribution in the installation of Indian Arctic mooring. His area of expertise includes design, development, installation and maintenance of offshore autonomous data acquisition/collection platforms especially in instrumentation and communication part of the system. He has also participated in various cruises on board research vessels for the installation of Indian data buoy and tsunami buoy systems. He is a Member of IEEE and served as treasurer during 2016–2018 in IEEE Oceanic Engineering Society (OES) Indian chapter. Email: [email protected]