ItemConference Paper

Hybrid Bidirectional GRU Approach for Crop Yield Prediction and Climate Change Impact Assessment in Agriculture

Title
Hybrid Bidirectional GRU Approach for Crop Yield Prediction and Climate Change Impact Assessment in Agriculture
Creator
Monika, M.; Kumar, Arun; Kelwade, Kamlesh; John, Tegil J; Krishna Prasad, S.; Nerlekar, Tanaya
Description
The impacts of climate change induced by humans will be felt most acutely by the agriculture sector due to its extreme dependence on weather. To ensure a steady supply of food, it is necessary to study and anticipate the effects of climate change on agricultural output. The impact of climate change on agricultural yield predictions is examined in this study using a novel methodology. In the proposed model, preprocessing, feature extraction, and training are the main processes. Data pretreatment guarantees quality by cleaning and normalising the data, while the PCC is utilised for feature selection. The model utilises AM and BiGRU for usage with large datasets. Using word vectors, the word embedding layer improves contextual awareness. Experiment findings show that the model is accurate to within 98.31% and can withstand a wide range of climate conditions. Current state-of-the-art methods are vastly outperformed by it, with performance measures like as R2 = 0.921%, MAE = 0.127%, and RMSE = 0.158%. These findings show that agricultural strategists and lawmakers can use AM-BiGRU to assess the effects of climate change and build a more resilient food system. 2025 IEEE.
Source
Proceedings of 8th International Conference on Computing Methodologies and Communication, ICCMC 2025;pp.1458-1463
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
Analysis of Variance (ANOVA); Crop Yield (CY); Pearson Correlation Coefficient (PCC); Pesticides Tonnes (PT); Rain Fall (RF)
Coverage
Monika M., Cambridge Institute of Technology, Department of Mca, Karnataka, Bangalore, India; Kumar A., Medicaps University, Department of Computer Science and Engineering, Madhya Pradesh, Indore, India; Kelwade K., Anjuman College of Engineering and Technology, Department of Computer Science and Engineering, Maharashtra, Nagpur, India; John T.J., Christ University, Department of Computer Science, Karnataka, Bangalore, India; Krishna Prasad S., Nitte (Deemed to Be University), Nmam Institute of Technology, Nitte, Department of Mechanical Engineering, Udupi, India; Nerlekar T., Dr. D. Y. Patil Institute of Technology, Department of Civil Engineering, Pimpri, Maharashtra, Pune, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833151211-8;
Format
online
Language
English
Type
Conference paper

Citation

Monika, M.; Kumar, Arun; Kelwade, Kamlesh; John, Tegil J; Krishna Prasad, S.; Nerlekar, Tanaya, “Hybrid Bidirectional GRU Approach for Crop Yield Prediction and Climate Change Impact Assessment in Agriculture,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25943.

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