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OpenAlex Citation Counts

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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:

Prediction of gas explosion pressures: A machine learning algorithm based on KPCA and an optimized LSSVM
Kai Zhang, Ke Zhang, Rui Bao
Journal of Loss Prevention in the Process Industries (2023) Vol. 83, pp. 105082-105082
Closed Access | Times Cited: 19

Showing 19 citing articles:

An ensemble model for monthly runoff prediction using least squares support vector machine based on variational modal decomposition with dung beetle optimization algorithm and error correction strategy
Dongmei Xu, Zong Li, Wenchuan Wang
Journal of Hydrology (2023) Vol. 629, pp. 130558-130558
Closed Access | Times Cited: 36
An analysis of li-ion induced potential incidents in battery electrical energy storage system by use of computational fluid dynamics modeling and simulations: The Beijing April 2021 case study
Xingyu Shen, Qianran Hu, Qi Zhang, et al.
Engineering Failure Analysis (2023) Vol. 151, pp. 107384-107384
Closed Access | Times Cited: 16
An approach to portfolio optimization with time series forecasting algorithms and machine learning techniques
Jyotirmayee Behera, Pankaj Kumar
Applied Soft Computing (2025), pp. 112741-112741
Closed Access
Intelligent prediction of compressive strength of self-compacting concrete incorporating silica fume using hybrid IWOA-GPR model
Yang Yu, Guangyin Wang, Ghasan Fahim Huseien, et al.
Materials Today Communications (2025), pp. 112282-112282
Closed Access
Multi Expression Programming and interpretable machine learning for determining compressive strength of coral sand aggregate concrete
Kamran Ehsan, Azman Mohamed, Waleed Bin Inqiad, et al.
Materials Today Communications (2025), pp. 112370-112370
Closed Access
Data-driven compressive strength investigation and design suggestions for rubberized concrete
Chang Zhou, Yuzhou Zheng
Materials Today Communications (2025), pp. 112477-112477
Closed Access
Predicting critical flame quenching thickness using machine learning approach with ResNet and ANN
Zhongheng Nie, Wei Gao, Haipeng Jiang, et al.
Journal of Loss Prevention in the Process Industries (2024), pp. 105448-105448
Closed Access | Times Cited: 4
Case study of fire and explosion accident based on damage consequence and numerical results: Explosion medium traceability
Xiaojie Wang, Xingyu Shen, Xinming Qian, et al.
Case Studies in Thermal Engineering (2023) Vol. 49, pp. 103171-103171
Open Access | Times Cited: 10
Machine learning models to predict the residual tensile strength of glass fiber reinforced polymer bars in strong alkaline environments: A comparative study
Kai Zhang, Ke Zhang, Rui Bao
Journal of Building Engineering (2023) Vol. 73, pp. 106817-106817
Closed Access | Times Cited: 9
PCA-TANN with model-based transfer learning for predicting blast load time series on structures
Tao Qiu, Shuai Cheng, Dezhi Zhang, et al.
Process Safety and Environmental Protection (2024) Vol. 187, pp. 1161-1177
Closed Access | Times Cited: 3
Predicting possible recommendations related to causes and consequences in the HAZOP study worksheet using natural language processing and machine learning: BERT, clustering, and classification
Ali Ekramipooya, Mehrdad Boroushaki, Davood Rashtchian
Journal of Loss Prevention in the Process Industries (2024) Vol. 89, pp. 105310-105310
Closed Access | Times Cited: 2
A novel hybrid model based on two-stage data processing and machine learning for forecasting chlorophyll-a concentration in reservoirs
Wenqing Yu, Xingju Wang, Xin Jiang, et al.
Environmental Science and Pollution Research (2023) Vol. 31, Iss. 1, pp. 262-279
Closed Access | Times Cited: 4
Explosion pressure and duration prediction using machine learning: A comparative study using classical models with Adam‐optimized neural network
Ahmad Muzammil Idris, Risza Rusli, Moamen Elsayed Mohamed, et al.
The Canadian Journal of Chemical Engineering (2024)
Closed Access | Times Cited: 1
A survival prediction model based on PCA-HSIDA-LSSVM for patients with esophageal squamous cell carcinoma
Yanfeng Wang, Yuhang Xia, Dan Ling, et al.
Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine (2023) Vol. 237, Iss. 12, pp. 1409-1426
Closed Access | Times Cited: 2
PROCESS MONITORING IN HYBRID ELECTRIC VEHICLES BASED ON DYNAMIC NONLINEAR METHOD
Yonghui Wang, Deprizon Syamsunur, Ang Chun Kit, et al.
Istrazivanja i projektovanja za privredu (2024) Vol. 22, Iss. 2, pp. 492-505
Open Access
Intelligent prediction of internal corrosion rate in submarine oil and gas pipelines based on KPCA-ISSA-MKSVR combined strategy
Hongye Jiang, Peng-zheng Lei, You-lv li, et al.
Research Square (Research Square) (2024)
Closed Access
Experimental analysis and model prediction of elbow pipe's erosion in water-cooled radiator
Yongfei Wang, Xiaofei Li, Tong Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Quality control prediction of electrolytic copper using novel hybrid nonlinear analysis algorithm
Yuzhen Su, Weichuan Ye, Kai Yang, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 1
FAULT DETECTION AND SEPARATION OF HYBRID ELECTRIC VEHICLES BASED ON KERNEL ORTHOGONAL SUBSPACE ANALYSIS
Yonghui Wang, Deprizon Syamsunur, Cong Peng, et al.
Istrazivanja i projektovanja za privredu (2023) Vol. 21, Iss. 4, pp. 1192-1202
Open Access
CNN CLASSIFICATION OF SOYBEANS WITH STORAGE TIME BASED ON NEAR INFRARED SPECTROSCOPY
Yan He, Kai Kang, Yin Qiwei, et al.
Engenharia Agrícola (2023) Vol. 43, Iss. 6
Open Access
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