Climate Change Impact on Geographical Region and Healthcare Analysis Using Deep Learning Algorithms DOI

G. Srikanth,

Ch. V. Raghavendran,

M. Prabhu

и другие.

Remote Sensing in Earth Systems Sciences, Год журнала: 2024, Номер unknown

Опубликована: Дек. 30, 2024

Язык: Английский

Improving Short-term Daily Streamflow Forecasting Using an Autoencoder Based CNN-LSTM Model DOI
Umar Muhammad Mustapha Kumshe,

Z.M. Abdulhamid,

Baba Ahmad Mala

и другие.

Water Resources Management, Год журнала: 2024, Номер 38(15), С. 5973 - 5989

Опубликована: Авг. 13, 2024

Язык: Английский

Процитировано

6
Effective carbon footprint assessment strategy in fly ash geopolymer concrete based on adaptive boosting learning techniques DOI
Y.S. Wudil, Amin Al‐Fakih, Mohammed A. Al‐Osta

и другие.

Environmental Research, Год журнала: 2024, Номер unknown, С. 120570 - 120570

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

3
Diel temperature patterns unveiled: High-frequency monitoring and deep learning in Lake Kasumigaura DOI Creative Commons
Senlin Zhu, Ryuichiro Shinohara, Shin‐ichiro S. Matsuzaki

и другие.

Ecological Indicators, Год журнала: 2024, Номер 169, С. 112958 - 112958

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

3
What drives the distinct evolution of the Aral Sea and Lake Balkhash? Insights from a novel CD-RF-FA method DOI Creative Commons
Shuang Liu, Aihua Long, Geping Luo

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 56, С. 102014 - 102014

Опубликована: Окт. 16, 2024

Язык: Английский

Процитировано

0
Marine Life Analysis Based on Ocean Water Level Rise and Climate Change Using Underwater Imaging Techniques DOI
Ádám Máté,

T. S. Arulananth,

T. Sathiya

и другие.

Remote Sensing in Earth Systems Sciences, Год журнала: 2024, Номер 7(4), С. 657 - 669

Опубликована: Окт. 22, 2024

Язык: Английский

Процитировано

0
Combining Physical Hydrological Model with Explainable Machine Learning Methods to Enhance Water Balance Assessment in Glacial River Basins DOI Open Access
Ruibiao Yang, Jinglu Wu, Guojing Gan

и другие.

Water, Год журнала: 2024, Номер 16(24), С. 3699 - 3699

Опубликована: Дек. 22, 2024

The implementation of accurate water balance assessment in glacier basins is essential for the management and sustainable development resources basins. In this study, a hybrid modeling framework was constructed to enhance runoff prediction An improved physical hydrological model (SEGSWAT+) combined with machine learning (ML) capture relationship between residuals components through Shapley additive explanations (SHAP) method. Based on enhancement fitting results existing model, are decomposed used correct process component values, thus improving accuracy results. We evaluated performance correction method using various ML methods. analyzed two consecutive periods from 1959 2022 glacial sub-basins three tributaries Upper Ili River Basin central Asia. show that based extreme gradient boosting (XGBoost) an average NSE value 0.93 has best performance, bias evapotranspiration soil content change reduced by 3.2–5%, proving effectiveness correction. This study advances interpretation models hydrologic areas complex hydrodynamic characteristics.

Язык: Английский

Процитировано

0
Climate Change Impact on Geographical Region and Healthcare Analysis Using Deep Learning Algorithms DOI

G. Srikanth,

Ch. V. Raghavendran,

M. Prabhu

и другие.

Remote Sensing in Earth Systems Sciences, Год журнала: 2024, Номер unknown

Опубликована: Дек. 30, 2024

Язык: Английский

Процитировано

0