Integrating digital technologies in agriculture for climate change adaptation and mitigation: State of the art and future perspectives

C Parra-López, SB Abdallah, G Garcia-Garcia… - … and Electronics in …, 2024 - Elsevier
Agriculture faces a major challenge in meeting the world's growing demand for food in a
sustainable manner in the face of increasing environmental pressures, in particular the …

Potential of artificial intelligence-based techniques for rainfall forecasting in Thailand: A comprehensive review

M Waqas, UW Humphries, A Wangwongchai… - Water, 2023 - mdpi.com
Rainfall forecasting is one of the most challenging factors of weather forecasting all over the
planet. Due to climate change, Thailand has experienced extreme weather events, including …

Applications of deep learning to ocean data inference and subgrid parameterization

T Bolton, L Zanna - Journal of Advances in Modeling Earth …, 2019 - Wiley Online Library
Oceanographic observations are limited by sampling rates, while ocean models are limited
by finite resolution and high viscosity and diffusion coefficients. Therefore, both data from …

The effects of climate change scenarios on Tilia ssp. in Turkey

U Canturk, Ş Kulaç - Environmental Monitoring and Assessment, 2021 - Springer
Global climate change will cause significant changes in climate parameters, especially
temperature increases and changes in precipitation regimes worldwide. Since the life of …

Landslide susceptibility prediction using particle-swarm-optimized multilayer perceptron: Comparisons with multilayer-perceptron-only, bp neural network, and …

D Li, F Huang, L Yan, Z Cao, J Chen, Z Ye - Applied Sciences, 2019 - mdpi.com
Landslides are one type of serious geological hazard which cause immense losses of local
life and property. Landslide susceptibility prediction (LSP) can be used to determine the …

[HTML][HTML] Neuro-fuzzy modeling and prediction of summer precipitation with application to different meteorological stations

AH Bukhari, M Sulaiman, S Islam, M Shoaib… - Alexandria Engineering …, 2020 - Elsevier
Research community has a growing interest in neural networks because of their practical
applications in many fields for accurate modeling and prediction of the complex behavior of …

Analyzing and modeling the spatial-temporal changes and the impact of GLOTI index on precipitation in the Marmara region of Türkiye

M Aalijahan, A Karataş, AR Lupo, B Efe… - Atmosphere, 2023 - mdpi.com
Precipitation is a particularly important part of the Earth's hydrological cycle and, therefore, is
a necessary variable for maintaining natural balance. This study investigated past, present …

Enhancing precipitation estimates through the fusion of weather radar, satellite retrievals, and surface parameters

Y Wehbe, M Temimi, RF Adler - Remote Sensing, 2020 - mdpi.com
Accurate and timely monitoring of precipitation remains a challenge, particularly in hyper-
arid regions such as the United Arab Emirates (UAE). The aim of this study is to improve the …

Dermatoscopy using multi-layer perceptron, convolution neural network, and capsule network to differentiate malignant melanoma from benign nevus

S Tiwari - … Journal of Healthcare Information Systems and …, 2021 - igi-global.com
Epiluminescence microscopy, more simply, dermatoscopy, entails a process using imaging
to examine skin lesions. Various sorts of skin ailments, for example, melanoma, may be …

Applied machine learning in social sciences: neural networks and crime prediction

RF Reier Forradellas, SL Náñez Alonso… - Social Sciences, 2020 - mdpi.com
This study proposes a crime prediction model according to communes (areas or districts in
which the city of Buenos Aires is divided). For this, the Python programming language is …