[HTML][HTML] Drought prediction: a comprehensive review of different drought prediction models and adopted technologies

N Nandgude, TP Singh, S Nandgude, M Tiwari - Sustainability, 2023 - mdpi.com
Precipitation deficit conditions and temperature anomalies are responsible for the
occurrence of various types of natural disasters that cause tremendous loss of human life …

[HTML][HTML] Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review

S Salcedo-Sanz, J Pérez-Aracil, G Ascenso… - Theoretical and Applied …, 2024 - Springer
Atmospheric extreme events cause severe damage to human societies and ecosystems.
The frequency and intensity of extremes and other associated events are continuously …

Prediction of the standardized precipitation index based on the long short-term memory and empirical mode decomposition-extreme learning machine models: The …

Ö Coşkun, H Citakoglu - Physics and Chemistry of the Earth, Parts A/B/C, 2023 - Elsevier
This research predicted the meteorological drought of Sakarya province in northwest Türkiye
using long short-term memory (LSTM). This deep learning algorithm has gained popularity …

[HTML][HTML] Prioritizing sub-watersheds for soil erosion using geospatial techniques based on morphometric and hypsometric analysis: a case study of the Indian Wyra …

PR Shekar, A Mathew, HG Abdo, H Almohamad… - Applied Water …, 2023 - Springer
The hydrological availability and scarcity of water can be affected by geomorphological
processes occurring within a watershed. Hence, it is crucial to perform a quantitative …

Combination of data-driven models and best subset regression for predicting the standardized precipitation index (SPI) at the Upper Godavari Basin in India

CB Pande, R Costache, SS Sammen, R Noor… - Theoretical and Applied …, 2023 - Springer
Standardized precipitation index prediction and monitoring are essential to mitigating the
effect of drought actions on precision farming, environments, climate-smart agriculture, and …

[HTML][HTML] Machine learning models development for accurate multi-months ahead drought forecasting: Case study of the Great Lakes, North America

MM Hameed, SFM Razali, WHMW Mohtar… - Plos one, 2023 - journals.plos.org
The Great Lakes are critical freshwater sources, supporting millions of people, agriculture,
and ecosystems. However, climate change has worsened droughts, leading to significant …

Examining evolutionary scale modeling‐derived different‐dimensional embeddings in the antimicrobial peptide classification through a KNIME workflow

KL Martínez‐Mauricio, CR García‐Jacas… - Protein …, 2024 - Wiley Online Library
Molecular features play an important role in different bio‐chem‐informatics tasks, such as
the Quantitative Structure–Activity Relationships (QSAR) modeling. Several pre‐trained …

Modeling of meteorological, agricultural, and hydrological droughts in semi-arid environments with various machine learning and discrete wavelet transform

M Achite, OM Katipoglu, S Şenocak… - Theoretical and Applied …, 2023 - Springer
Recent meteorological, hydrological, and agricultural droughts in the Mediterranean regions
have raised concerns about the impact of climate change. In this study, the meteorological …

Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India

CB Pande, NL Kushwaha, OA Alawi, SS Sammen… - Environmental …, 2024 - Elsevier
This research was established to accurately forecast daily scale air quality index (AQI) which
is an essential environmental index for decision-making. Researchers have projected …

Short-term drought Index forecasting for hot and semi-humid climate Regions: A novel empirical Fourier decomposition-based ensemble Deep-Random vector …

M Jamei, M Ali, SM Bateni, C Jun, M Karbasi… - … and Electronics in …, 2024 - Elsevier
The development of advanced technologies based on computer aid models in the domain of
crops and agriculture productively is a modern advancement. Machine learning (ML) based …