[HTML][HTML] Advanced machine learning model for better prediction accuracy of soil temperature at different depths
Soil temperature has a vital importance in biological, physical and chemical processes of
terrestrial ecosystem and its modeling at different depths is very important for land …
terrestrial ecosystem and its modeling at different depths is very important for land …
Improving monthly rainfall forecast in a watershed by combining neural networks and autoregressive models
A Pérez-Alarcón, D Garcia-Cortes… - Environmental …, 2022 - Springer
The main aim of the rain forecast is to determine rain occurrence conditions in a specific
location. This is considered of vital importance to assess the availability of water resources …
location. This is considered of vital importance to assess the availability of water resources …
[HTML][HTML] A review of machine learning approaches to soil temperature estimation
M Taheri, HK Schreiner, A Mohammadian, H Shirkhani… - Sustainability, 2023 - mdpi.com
Soil temperature is an essential factor for agricultural, meteorological, and hydrological
applications. Direct measurement, despite its high accuracy, is impractical on a large spatial …
applications. Direct measurement, despite its high accuracy, is impractical on a large spatial …
A two-layer water demand prediction system in urban areas based on micro-services and LSTM neural networks
In recent years, scarce water resources became one of the main problems that endanger
human species existence and the advancement of any nation. In this research, smart water …
human species existence and the advancement of any nation. In this research, smart water …
Predicting wastewater treatment plant quality parameters using a novel hybrid linear-nonlinear methodology
Biochemical oxygen demand (BOD), chemical oxygen demand (COD), total dissolved solids
(TDS) and total suspended solids (TSS) are the most commonly regulated wastewater …
(TDS) and total suspended solids (TSS) are the most commonly regulated wastewater …
[HTML][HTML] Genetic-algorithm-optimized sequential model for water temperature prediction
Advances in establishing real-time river water quality monitoring networks combined with
novel artificial intelligence techniques for more accurate forecasting is at the forefront of …
novel artificial intelligence techniques for more accurate forecasting is at the forefront of …
Development of an extreme gradient boosting model integrated with evolutionary algorithms for hourly water level prediction
The establishment of reliable water level prediction models is vital for urban flood control
and planning. In this paper, we develop hybrid models (GA-XGBoost and DE-XGBoost) that …
and planning. In this paper, we develop hybrid models (GA-XGBoost and DE-XGBoost) that …
A reliable linear stochastic daily soil temperature forecast model
Forecasting soil temperature profile is recognized as vital information for irrigation demand
forecast in a modern/efficient agricultural water management framework in arid regions. A …
forecast in a modern/efficient agricultural water management framework in arid regions. A …
Metaheuristic optimization algorithms hybridized with artificial intelligence model for soil temperature prediction: Novel model
An enhanced hybrid artificial intelligence model was developed for soil temperature (ST)
prediction. Among several soil characteristics, soil temperature is one of the essential …
prediction. Among several soil characteristics, soil temperature is one of the essential …
Analysis of the influence of international benchmark oil price on China's real exchange rate forecasting
The exchange rate forecasting plays an important role in the economic and financial fields.
Oil price fluctuations have a great impact on the country's economic activity. Based on the …
Oil price fluctuations have a great impact on the country's economic activity. Based on the …