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Development of a robust daily soil temperature estimation in semi-arid continental climate using meteorological predictors based on computational intelligent paradigms.

PloS one
Changes in soil temperature (ST) play an important role in the main mechanisms within the soil, including biological and chemical activities. For instance, they affect the microbial community composition, the speed at which soil organic matter breaks...

PEPNet: A barotropic primitive equations-based network for wind speed prediction.

Neural networks : the official journal of the International Neural Network Society
In wind speed prediction technologies, deep learning-based methods have achieved promising advantages. However, most existing methods focus on learning implicit knowledge in a data-driven manner but neglect some explicit knowledge from the physical t...

Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates (TSP) in Zabol, Iran during the dusty period of 120-days wind.

Environmental pollution (Barking, Essex : 1987)
Total suspended particulates (TSP), as a key pollutant, is a serious threat for air quality, climate, ecosystems and human health. Therefore, measurements, prediction and forecasting of TSP concentrations are necessary to mitigate their negative effe...

Innovative approach for predicting daily reference evapotranspiration using improved shallow and deep learning models in a coastal region: A comparative study.

Journal of environmental management
Accurate and reliable estimation of Reference Evapotranspiration (ETo) is crucial for water resources management, hydrological processes, and agricultural production. The FAO-56 Penman-Monteith (FAO-56PM) approach is recommended as the standard model...

Facilitating interaction between partial differential equation-based dynamics and unknown dynamics for regional wind speed prediction.

Neural networks : the official journal of the International Neural Network Society
Regional wind speed prediction is an important spatiotemporal prediction problem which is crucial for optimizing wind power utilization. Nevertheless, the complex dynamics of wind speed pose a formidable challenge to prediction tasks. The evolving dy...

Improving the operational forecasts of outdoor Universal Thermal Climate Index with post-processing.

International journal of biometeorology
The Universal Thermal Climate Index (UTCI) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units of temperature and considers physiological aspects of the human body. It takes into account the effec...

Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

Environmental monitoring and assessment
The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step be...

Enhancement of ANN-based wind power forecasting by modification of surface roughness parameterization over complex terrain.

Journal of environmental management
Wind energy plays an important role in the sustainable energy transition towards a low-carbon society. Proper assessment of wind energy resources and accurate wind energy prediction are essential prerequisites for balancing electricity supply and dem...

Utilizing support vector machines to foster sustainable development and innovation in the clean energy sector via green finance.

Journal of environmental management
As the global demand for clean energy continues to grow, the sustainable development of clean energy projects has become an important topic of research. in order to optimize the performance and sustainability of clean energy projects, this work explo...

Windy events detection in big bioacoustics datasets using a pre-trained Convolutional Neural Network.

The Science of the total environment
Passive Acoustic Monitoring (PAM), which involves using autonomous record units for studying wildlife behaviour and distribution, often requires handling big acoustic datasets collected over extended periods. While these data offer invaluable insight...