Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Improving forecasting accuracy of medium and long-term runoff using artificial neural network based on EEMD decomposition
Wenchuan Wang, Kwok‐wing Chau, Lin Qiu, et al.
Environmental Research (2015) Vol. 139, pp. 46-54
Closed Access | Times Cited: 221

Showing 1-25 of 221 citing articles:

Driven by Data or Derived Through Physics? A Review of Hybrid Physics Guided Machine Learning Techniques With Cyber-Physical System (CPS) Focus
Rahul Rai, Chandan K. Sahu
IEEE Access (2020) Vol. 8, pp. 71050-71073
Open Access | Times Cited: 216
Monthly runoff time series prediction by variational mode decomposition and support vector machine based on quantum-behaved particle swarm optimization
Zhong-kai Feng, Wen-jing Niu, Zhengyang Tang, et al.
Journal of Hydrology (2020) Vol. 583, pp. 124627-124627
Closed Access | Times Cited: 210
An adaptive middle and long-term runoff forecast model using EEMD-ANN hybrid approach
Qiaofeng Tan, Xiaohui Lei, Wang Xu, et al.
Journal of Hydrology (2018) Vol. 567, pp. 767-780
Closed Access | Times Cited: 209
Spatiotemporal Modeling for Nonlinear Distributed Thermal Processes Based on KL Decomposition, MLP and LSTM Network
Yajun Fan, Kangkang Xu, Hui Wu, et al.
IEEE Access (2020) Vol. 8, pp. 25111-25121
Open Access | Times Cited: 168
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Rana Muhammad Adnan, Reham R. Mostafa, Özgür Kişi, et al.
Knowledge-Based Systems (2021) Vol. 230, pp. 107379-107379
Closed Access | Times Cited: 165
Precipitation projection using a CMIP5 GCM ensemble model: a regional investigation of Syria
Rajab Homsi, Mohammed Sanusi Shiru, Shamsuddin Shahid, et al.
Engineering Applications of Computational Fluid Mechanics (2019) Vol. 14, Iss. 1, pp. 90-106
Open Access | Times Cited: 150
Hourly stepwise forecasting for solar irradiance using integrated hybrid models CNN-LSTM-MLP combined with error correction and VMD
Jun Liu, Xiaoqiao Huang, Qiong Li, et al.
Energy Conversion and Management (2023) Vol. 280, pp. 116804-116804
Closed Access | Times Cited: 75
An enhanced monthly runoff time series prediction using extreme learning machine optimized by salp swarm algorithm based on time varying filtering based empirical mode decomposition
Wenchuan Wang, Qi Cheng, Kwok‐wing Chau, et al.
Journal of Hydrology (2023) Vol. 620, pp. 129460-129460
Closed Access | Times Cited: 42
Evaluating the Performance of Several Data Preprocessing Methods Based on GRU in Forecasting Monthly Runoff Time Series
Wenchuan Wang, Yu-jin Du, Kwok‐wing Chau, et al.
Water Resources Management (2024) Vol. 38, Iss. 9, pp. 3135-3152
Open Access | Times Cited: 16
Multi-step ahead wind speed forecasting using an improved wavelet neural network combining variational mode decomposition and phase space reconstruction
Deyun Wang, Hongyuan Luo, Olivier Grunder, et al.
Renewable Energy (2017) Vol. 113, pp. 1345-1358
Closed Access | Times Cited: 166
Operation rule derivation of hydropower reservoir by k-means clustering method and extreme learning machine based on particle swarm optimization
Zhong-kai Feng, Wen-jing Niu, Rui Zhang, et al.
Journal of Hydrology (2019) Vol. 576, pp. 229-238
Closed Access | Times Cited: 140
Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach
Ramendra Prasad, Ravinesh C. Deo, Yan Li, et al.
CATENA (2019) Vol. 177, pp. 149-166
Closed Access | Times Cited: 136
Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems
Xiaohu Wen, Qi Feng, Ravinesh C. Deo, et al.
Journal of Hydrology (2019) Vol. 570, pp. 167-184
Closed Access | Times Cited: 129
Random forest regression evaluation model of regional flood disaster resilience based on the whale optimization algorithm
Dong Liu, Zhongrui Fan, Qiang Fu, et al.
Journal of Cleaner Production (2019) Vol. 250, pp. 119468-119468
Closed Access | Times Cited: 127
Prediction of multi-inputs bubble column reactor using a novel hybrid model of computational fluid dynamics and machine learning
Amir Mosavi, Shahaboddin Shamshirband, Ely Salwana, et al.
Engineering Applications of Computational Fluid Mechanics (2019) Vol. 13, Iss. 1, pp. 482-492
Open Access | Times Cited: 114
Forecasting reservoir monthly runoff via ensemble empirical mode decomposition and extreme learning machine optimized by an improved gravitational search algorithm
Wen-jing Niu, Zhong-kai Feng, Ming Zeng, et al.
Applied Soft Computing (2019) Vol. 82, pp. 105589-105589
Closed Access | Times Cited: 113
Flood prediction based on weather parameters using deep learning
Suresh Sankaranarayanan, Malavika Prabhakar, Sreesta Satish, et al.
Journal of Water and Climate Change (2019) Vol. 11, Iss. 4, pp. 1766-1783
Closed Access | Times Cited: 113
A new approach for simulating and forecasting the rainfall-runoff process within the next two months
Mohamad Javad Alizadeh, Mohammad Reza Kavianpour, Özgür Kişi, et al.
Journal of Hydrology (2017) Vol. 548, pp. 588-597
Closed Access | Times Cited: 107
Forecasting Daily Runoff by Extreme Learning Machine Based on Quantum-Behaved Particle Swarm Optimization
Wen-jing Niu, Zhong-kai Feng, Chuntian Cheng, et al.
Journal of Hydrologic Engineering (2018) Vol. 23, Iss. 3
Closed Access | Times Cited: 98
Streamflow estimation by support vector machine coupled with different methods of time series decomposition in the upper reaches of Yangtze River, China
Shuang Zhu, Jianzhong Zhou, Lei Ye, et al.
Environmental Earth Sciences (2016) Vol. 75, Iss. 6
Closed Access | Times Cited: 95
Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting
Soukayna Mouatadid, Jan Adamowski, Mukesh Tiwari, et al.
Agricultural Water Management (2019) Vol. 219, pp. 72-85
Closed Access | Times Cited: 95
A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition
Xike Zhang, Qiuwen Zhang, Gui Zhang, et al.
International Journal of Environmental Research and Public Health (2018) Vol. 15, Iss. 5, pp. 1032-1032
Open Access | Times Cited: 93
Short-term traffic volume prediction using GA-BP based on wavelet denoising and phase space reconstruction
Yanni Peng, Wanli Xiang
Physica A Statistical Mechanics and its Applications (2019) Vol. 549, pp. 123913-123913
Closed Access | Times Cited: 93
Annual Streamflow Time Series Prediction Using Extreme Learning Machine Based on Gravitational Search Algorithm and Variational Mode Decomposition
Wen-jing Niu, Zhong-kai Feng, Yu‐Bin Chen, et al.
Journal of Hydrologic Engineering (2020) Vol. 25, Iss. 5
Closed Access | Times Cited: 90
Data Pre-Analysis and Ensemble of Various Artificial Neural Networks for Monthly Streamflow Forecasting
Jianzhong Zhou, Peng Tian, Chu Zhang, et al.
Water (2018) Vol. 10, Iss. 5, pp. 628-628
Open Access | Times Cited: 86
Page 1 - Next Page

Scroll to top