Enhancing the accuracy of groundwater level prediction at different scales using spatio-temporal graph convolutional model

Earth Science Informatics, Год журнала: 2025, Номер 18(2)

Опубликована: Фев. 1, 2025

Язык: Английский

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A simple and high-accuracy method for minute-level water demand forecasting in district metering areas

Journal of Hydrology, Год журнала: 2025, Номер 652, С. 132698 - 132698

Опубликована: Янв. 13, 2025

Язык: Английский

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Study on Water Resource Carrying Capacity and Crop Structure Optimization Based on Gray Relational Analysis

Plants, Год журнала: 2025, Номер 14(5), С. 685 - 685

Опубликована: Фев. 23, 2025

This study addresses challenges such as insufficient irrigation water quotas, severe groundwater over-extraction, and conflicts around crop usage within the mixed-cropping areas of Inner Mongolia Yellow River Basin. Five evaluation factors—water resource utilization efficiency, rate, degree development utilization, supply modulus, demand modulus—were selected for a gray relational analysis to assess 2023 carrying capacity. A structure optimization model was developed using machine learning, focusing on minimizing use while maximizing economic benefits. The results indicate that resources are nearing critical levels, with many regions showing low capacities supply–demand conflicts. Key issues include unreasonable planting structures excessive leading significant waste. To optimize it is recommended reduce food area by 0.0194 × 104 hm2 increase forage crops 0.0106 0.0116 hm2, respectively. adjustment would lead total reduction 0.0289 106 m3 per year, an in yield 4340.86 tons, benefit CNY 6,559,200, thus cropping towards greater rationality. findings provide valuable insights optimal allocation areas.

Язык: Английский

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Research on Photovoltaic Power Prediction Method Based on Dynamic Similar Selection and Bidirectional Gated Recurrent Unit

Advanced Theory and Simulations, Год журнала: 2025, Номер unknown

Опубликована: Март 8, 2025

Abstract Photovoltaic (PV) power generation is vital for sustainable energy development, yet its inherent randomness and volatility challenge grid stability. Accurate short‐term PV prediction essential reliable operation. This paper proposes an integrated method combining dynamic similar selection (DSS), variational mode decomposition (VMD), bidirectional gated recurrent unit (BiGRU), improved sparrow search algorithm (ISSA). First, DSS selects training data based on local meteorological similarity, reducing interference. VMD then decomposes into smooth components, mitigating volatility. The Pearson correlation coefficient used to filter highly relevant variables, enhancing input quality. BiGRU captures temporal evolution patterns, with ISSA optimizing key parameters robust forecasting. Validated historical Australian under diverse weather conditions, the proposed effectively reduces volatility, significantly improving accuracy reliability. These advancements support stable supply efficient

Язык: Английский

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Application of stochastic process modeling in the prediction of emergency response time for public emergencies

Applied Mathematics and Nonlinear Sciences, Год журнала: 2025, Номер 10(1)

Опубликована: Янв. 1, 2025

Abstract The stochastic process model, as a powerful mathematical tool, can simulate and predict phenomena over time. study adopts the Markov prediction model in incorporates gray to construct emergency response time for public emergencies. performance of model’s is evaluated by comparing its accuracy current mainstream methods. used simulating water pollution accident Huaihe River section Anhui Province. predicted that each plant during dry abundant periods was less than when pollutants reached highest concentration, indicating emergencies based on improved more adequate.

Язык: Английский

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Comparison of multiple methods for identifying water sources of mine water inrush and quantitative analysis of mixed water sources based on isotope theory

Earth Science Informatics, Год журнала: 2024, Номер 18(1)

Опубликована: Дек. 11, 2024

Язык: Английский

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