ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Water-Smart Food Production
Volume 9 - 2025 | doi: 10.3389/fsufs.2025.1636499
This article is part of the Research TopicOptimizing Deficit Irrigation for Sustainable Crop Production in Water-Scarce RegionsView all articles
Short-Term Soil Moisture Content Forecasting with a Hybrid Informer Model
Provisionally accepted
- University of Science and Technology Beijing, Beijing, China
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This study proposes a novel time-series forecasting approach that integrates the Informer model with the RAO-1 optimization algorithm for soil water content (SWC) prediction. The method innovatively combines Informer's long-range dependency modeling with RAO-1's efficient hyperparameter optimization to enhance forecasting accuracy. Comparative experiments were conducted using Random Forest, Support Vector Regression, Long Short-Term Memory and Transformer as baseline models on SWC datasets from the Beijing region. The RAO-1-optimized Informer consistently outperforms these baselines in both deterministic and probabilistic forecasting tasks, while also achieving superior computational efficiency. These results highlight the robustness of the proposed method and its potential to support sustainable agricultural water management through accurate SWC prediction.
Keywords: Soil moisture content, Rao-1 algorithm, Informer model, Time-series forecasting, Hyperparameter optimization, deep learning
Received: 28 May 2025; Accepted: 06 Aug 2025.
Copyright: © 2025 Wang, Yao and Huang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Long Wang, University of Science and Technology Beijing, Beijing, China
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