Hybrid Deep Learning Models for Forecasting Harmful Algal Blooms (HABs)

Sayyad Sakina Akbar , Aditya Rajendra Yadav , Amit Kumar Pandey , Dr. Santosh Kumar Singh

Chlorophyll-a, Forecasting, Deep Learning, Bloomformer, Toxic Level, GRU and LSTM

This paper designs and analyzes hybrid deep learning methods of forecasting HABs along California and Southern Oregon coastlines between the month of April and July 2025. They are three models that are operated: a CNN-GRU to predict chlorophyll-a; a multi-variable CNN-GRU to identify the risk of the HAB; and a Bloomformer-CNN-BiLSTM to predict the toxin level. These are models that involve biological and environmental information on water temperature, salinity, and chlorophyll-a levels. Findings indicate that multi-variable and transformer-enhanced models provide more reliable forecasts that can be used to make early warning and coastal management. Bloomformer-CNN-BiLSTM model is the most representative of the capacity-level and accuracy with toxin-related parameters of the system levels of Pseudo-nitzschia and domoic acid. This can establish a base on hybrid deep learning techniques in predicting HABs, informative in establishing the financial, health, and environmental dangers of algal blooms.

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"Hybrid Deep Learning Models for Forecasting Harmful Algal Blooms (HABs)", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 9, page no.b364-b370, September-2025, Available :https://ijsdr.org/papers/IJSDR2509145.pdf

Volume 10 Issue 9, September-2025

Pages : b364-b370

Paper Reg. ID: IJSDR_305017

Published Paper Id: IJSDR2509145

Downloads: 00066

Research Area: Biological Science

Country: Mumbai, Maharashtra, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2509145

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2509145

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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