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Combining autoregressive integrated moving average with Long Short-Term Memory neural network and optimisation algorithms for predicting ground water level
The groundwater resources are the essential sources for irrigation and agriculture
management. Forecasting groundwater levels (GWL) for the current and future periods is an …
management. Forecasting groundwater levels (GWL) for the current and future periods is an …
An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction
Precise prediction of water quality parameters plays a significant role in making an early
alert of water pollution and making better decisions for the management of water resources …
alert of water pollution and making better decisions for the management of water resources …
Multi-model ensemble prediction of pan evaporation based on the Copula Bayesian Model Averaging approach
Pan evaporation (E p) is an efficient and practical tool for planning and managing water
resources, understanding the water balance in hydrological processes, and develo** …
resources, understanding the water balance in hydrological processes, and develo** …
Ensemble learning based multi-modal intra-hour irradiance forecasting
S Shan, C Li, Z Ding, Y Wang, K Zhang… - Energy Conversion and …, 2022 - Elsevier
Accurate intra-hour irradiance forecasting plays an important role in improving the
effectiveness of photovoltaic power management. More and more sensors, for example, total …
effectiveness of photovoltaic power management. More and more sensors, for example, total …
[HTML][HTML] A hybrid deep learning framework integrating feature selection and transfer learning for multi-step global horizontal irradiation forecasting
The randomness and volatility of solar irradiance pose a challenge to efficient solar energy
development and utilization across the world, which increases the necessity of develo** …
development and utilization across the world, which increases the necessity of develo** …
Robust kernel extreme learning machines with weighted mean of vectors and variational mode decomposition for forecasting total dissolved solids
A stable and accurate forecast of water quality parameters is crucial for planning and
managing future investment programs. A well-known water quality indicator is the total …
managing future investment programs. A well-known water quality indicator is the total …
Inclusive multiple model using hybrid artificial neural networks for predicting evaporation
Predicting evaporation is essential for managing water resources in basins. Improvement of
the prediction accuracy is essential to identify adequate inputs on evaporation. In this study …
the prediction accuracy is essential to identify adequate inputs on evaporation. In this study …
[HTML][HTML] Solar radiation estimation in different climates with meteorological variables using Bayesian model averaging and new soft computing models
Solar radiation (SR) is considered as a critical factor in determining energy management. In
this research, the potential of the Bayesian averaging model (BMA) was investigated for …
this research, the potential of the Bayesian averaging model (BMA) was investigated for …
GLUE analysis of meteorological-based crop coefficient predictions to derive the explicit equation
The crop coefficient (K c) is a scaling factor to calculate crop evapotranspiration (ET c).
Accurate prediction of K c affects planning to allocate water resources, especially in arid and …
Accurate prediction of K c affects planning to allocate water resources, especially in arid and …
GLUE uncertainty analysis of hybrid models for predicting hourly soil temperature and application wavelet coherence analysis for correlation with meteorological …
Accurate prediction of soil temperature (T s) is critical for efficient soil, water and field crop
management. In this study, hourly T s variations at 5, 10, and 30 cm soil depth were …
management. In this study, hourly T s variations at 5, 10, and 30 cm soil depth were …