[HTML][HTML] A review of neural networks for air temperature forecasting
The accurate forecast of air temperature plays an important role in water resources
management, land–atmosphere interaction, and agriculture. However, it is difficult to …
management, land–atmosphere interaction, and agriculture. However, it is difficult to …
Deep learning-based maximum temperature forecasting assisted with meta-learning for hyperparameter optimization
Time series forecasting of meteorological variables such as daily temperature has recently
drawn considerable attention from researchers to address the limitations of traditional …
drawn considerable attention from researchers to address the limitations of traditional …
Introducing a framework for modeling of drug electrochemical removal from wastewater based on data mining algorithms, scatter interpolation method, and multi …
The contamination of waters by persistent organic pollutants, especially pharmaceutical
contaminants, is one of the concerns all over the world. To date, among the treatment …
contaminants, is one of the concerns all over the world. To date, among the treatment …
Prediction of temperature for various pressure levels using ANN and multiple linear regression techniques: A case study
In this paper, the estimation capacities of Artificial Neural Network (ANN) and Multiple Linear
Regression (MLR) are examined to forecast temperature at two pressure level 400 hPa and …
Regression (MLR) are examined to forecast temperature at two pressure level 400 hPa and …
A new framework for missing data estimation and reconstruction based on the geographical input information, data mining, and multi-criteria decision-making; theory …
A Mohaghegh, S Farzin, MV Anaraki - Groundwater for Sustainable …, 2022 - Elsevier
In the present study, a new framework is developed based on the geographical data (GD),
data mining techniques (DI), and Hesitant fuzzy-multicriteria decision-making methods (HF …
data mining techniques (DI), and Hesitant fuzzy-multicriteria decision-making methods (HF …
[HTML][HTML] Machine Learning for the Sustainable Management of Depth Prediction and Load Optimization in River Convoys: An Amazon Basin Case Study
LCP Campos Filho, NM Figueiredo, CJC Blanco… - Sustainability, 2024 - mdpi.com
The seasonal fluctuation of river depths is a critical factor in designing cargo capacity for
river convoys and logistics processes used for grain transportation in northern Brazil. Water …
river convoys and logistics processes used for grain transportation in northern Brazil. Water …
Identification of time series models using sparse Takagi–Sugeno fuzzy systems with reduced structure
K Wiktorowicz, T Krzeszowski - Neural Computing and Applications, 2022 - Springer
Simplifying fuzzy models, including those for predicting time series, is an important issue in
terms of their interpretation and implementation. This simplification can involve both the …
terms of their interpretation and implementation. This simplification can involve both the …
Introducing a Novel Double Hybrid Algorithm (DHA) and Developing Its Application for Predicting Air Temperature Under Climate Change Conditions (A Case Study of …
In the present study, a novel double hybrid algorithm (DHA) based on the least squares
support vector machine (LSSVM) and hybrid Aquila optimization-particle swarm optimization …
support vector machine (LSSVM) and hybrid Aquila optimization-particle swarm optimization …
The Importance of Agricultural and Meteorological Predictions Using Machine Learning Models
This chapter reviews the applications of machine learning (ML) models for predicting
meteorological and agricultural variables. The advantage and disadvantages of models are …
meteorological and agricultural variables. The advantage and disadvantages of models are …
[PDF][PDF] A Review of Neural Networks for Air Temperature Forecasting. Water 2021, 13, 1294
The accurate forecast of air temperature plays an important role in water resources
management, land–atmosphere interaction, and agriculture. However, it is difficult to …
management, land–atmosphere interaction, and agriculture. However, it is difficult to …