Analyzing variation of inflow from the Syr Darya to the Aral Sea: A Bayesian-neural-network-based factorial analysis method-Reference-Cited by-同舟云学术

Analyzing variation of inflow from the Syr Darya to the Aral Sea: A Bayesian-neural-network-based factorial analysis method

Published:2020-08 Issue: Volume:587 Page:124976
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Jia Q.M.,Li Y.P.,Li Y.F.,Huang G.H.^ORCID

Funder

Chinese Academy of Sciences

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference68 articles.

1. The history and future of the biological resources of the Caspian and the Aral Seas;Aladin;J. Oceanol. Limnol.,2018

2. Optimization of wireless power transfer using artificial neural network: a review;Ali;Microwave Opt. Technol. Lett.,2019

3. Power system voltage stability assessment using a hybrid approach combining dragonfly optimization algorithm and support vector regression;Amroune;Arab. J. Sci. Eng.,2018

4. Structural health monitoring of a cable-stayed bridge with Bayesian neural networks;Arangio;Struct. Infrastruct. Eng.,2015

5. Insights into preferential flow snowpack runoff using random forest;Avanzi;Water Resour. Res.,2019

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analyzing variation of water inflow to inland lakes under climate change: Integrating deep learning and time series data mining;Environmental Research;2024-10

2. Modeling Upscaled Mass Discharge From Complex DNAPL Source Zones Using a Bayesian Neural Network: Prediction Accuracy, Uncertainty Quantification and Source Zone Feature Importance;Water Resources Research;2024-06-26

3. A factorial-analysis-based Bayesian neural network method for quantifying China's CO2 emissions under dual-carbon target;Science of The Total Environment;2024-04

4. Carbon trading price forecasting in digitalization social change era using an explainable machine learning approach: The case of China as emerging country evidence;Technological Forecasting and Social Change;2024-03

5. Development of a random-forest-copula-factorial analysis (RFCFA) method for predicting propagation between meteorological and hydrological drought;National Science Open;2024-01-01