Optimised deep convolutional spiking neural network for accurate long-term and short-term rainfall forecasting in climate prediction systems

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Authors

Publication Details

Journal
International Journal of Mobile Communications
Published
2025-06-27
DOI
https://doi.org/10.1504/ijmc.2026.10072144
Primary Topic
Hydrological Forecasting Using AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimised deep convolutional spiking neural network for accurate long-term and short-term rainfall forecasting in climate prediction systems

K Ananthajothi, Moorthy Agoramoorthy, M. Amanullah
International Journal of Mobile Communications
Hydrological Forecasting Using AI
article

Optimised deep convolutional spiking neural network for accurate long-term and short-term rainfall forecasting in climate prediction systems

K Ananthajothi, Moorthy Agoramoorthy, M. Amanullah
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Mobile CommunicationsVol. 1(1)
Climate action
Openalex Percentile: Top 86%
Hydrological Forecasting Using AI
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Optimised deep convolutional spiking neural network for accurate long-term and short-term rainfall forecasting in climate prediction systems — K Ananthajothi, Moorthy Agoramoorthy, et al. · International Journal of Mobile Communications (2025) | TGRS Research Map | TGRS