Water quality prediction using machine learning models based on grid search method

MY Shams, AM Elshewey, ESM El-Kenawy… - Multimedia Tools and …, 2024 - Springer
Water quality is very dominant for humans, animals, plants, industries, and the environment.
In the last decades, the quality of water has been impacted by contamination and pollution …

Enhancing crop recommendation systems with explainable artificial intelligence: a study on agricultural decision-making

MY Shams, SA Gamel, FM Talaat - Neural Computing and Applications, 2024 - Springer
Abstract Crop Recommendation Systems are invaluable tools for farmers, assisting them in
making informed decisions about crop selection to optimize yields. These systems leverage …

Times Series Forecasting of Monthly Rainfall using Seasonal Auto Regressive Integrated Moving Average with EXogenous Variables (SARIMAX) Model

S Mulla, CB Pande, SK Singh - Water Resources Management, 2024 - Springer
In this study, the monthly rainfall time series forecasting was investigated based on the
effectiveness of the Seasonal Auto Regressive Integrated Moving Average with EXogenous …

An optimized model based on deep learning and gated recurrent unit for COVID-19 death prediction

Z Tarek, MY Shams, SK Towfek, HK Alkahtani… - Biomimetics, 2023 - mdpi.com
The COVID-19 epidemic poses a worldwide threat that transcends provincial, philosophical,
spiritual, radical, social, and educational borders. By using a connected network, a …

Soil erosion status prediction using a novel random forest model optimized by random search method

Z Tarek, AM Elshewey, SM Shohieb, AM Elhady… - Sustainability, 2023 - mdpi.com
Soil erosion, the degradation of the earth's surface through the removal of soil particles,
occurs in three phases: dislocation, transport, and deposition. Factors such as soil type …

Temperature prediction based on STOA-SVR rolling adaptive optimization model

S Shen, Y Du, Z Xu, X Qin, J Chen - Sustainability, 2023 - mdpi.com
In this paper, a support vector regression (SVR) adaptive optimization rolling composite
model with a sooty tern optimization algorithm (STOA) has been proposed for temperature …

Analysis of Statistical and Deep Learning Techniques for Temperature Forecasting

S Ganesan Kruthika, U Rajasekaran… - Recent Advances in …, 2024 - ingentaconnect.com
In the field of meteorology, temperature forecasting is a significant task as it has been a key
factor in industrial, agricultural, renewable energy, and other sectors. High accuracy in …

A Hybrid SARIMAX Model in Conjunction with Neural Networks for the Forecasting of Life Insurance Industry Growth in Thailand

S Huadsri, S Mekruksavanich… - … on Digital Arts …, 2024 - ieeexplore.ieee.org
This article is conducted with the primary aim of comparing various forecasting models to
identify the optimal model for forecasting the growth of the life insurance industry in …

Modeling Life Insurance Business Growth in Thailand using SARIMAX and Multilayer Perceptron

W Phaphan, A Jitpattanakul, S Huadsri… - … on Computer and …, 2024 - ieeexplore.ieee.org
The principal objective of this article is to examine, compare, and develop a time series
model for forecasting the growth of the life insurance business in Thailand. The proposed …

Forecasting Temperature Trends Using SARIMAX: A Case Study in Ahmedabad City, India

V Shah, N Patel, DA Shah, D Swain, M Mohanty… - 2024 - preprints.org
Globalization and industrialization have significantly disturbed the environmental
ecosystem, leading to critical challenges such as global warming, extreme weather events …