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:

Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection
Lean Yu, Xiao Yao, Shouyang Wang, et al.
Expert Systems with Applications (2011) Vol. 38, Iss. 12, pp. 15392-15399
Closed Access | Times Cited: 95

Showing 1-25 of 95 citing articles:

Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research
Stefan Lessmann, Bart Baesens, Hsin‐Vonn Seow, et al.
European Journal of Operational Research (2015) Vol. 247, Iss. 1, pp. 124-136
Open Access | Times Cited: 885
Information gain directed genetic algorithm wrapper feature selection for credit rating
Swati Jadhav, Hongmei He, Karl Jenkins
Applied Soft Computing (2018) Vol. 69, pp. 541-553
Open Access | Times Cited: 275
Statistical and machine learning models in credit scoring: A systematic literature survey
Xolani Dastile, Turgay Çelik, Moshe Moses Potsane
Applied Soft Computing (2020) Vol. 91, pp. 106263-106263
Closed Access | Times Cited: 274
Investigation and improvement of multi-layer perceptron neural networks for credit scoring
Zongyuan Zhao, Shuxiang Xu, Byeong Ho Kang, et al.
Expert Systems with Applications (2014) Vol. 42, Iss. 7, pp. 3508-3516
Closed Access | Times Cited: 201
Deep learning for credit scoring: Do or don’t?
Björn Rafn Gunnarsson, Seppe vanden Broucke, Bart Baesens, et al.
European Journal of Operational Research (2021) Vol. 295, Iss. 1, pp. 292-305
Open Access | Times Cited: 162
Selection of Support Vector Machines based classifiers for credit risk domain
Paulius Danėnas, Gintautas Garšva
Expert Systems with Applications (2014) Vol. 42, Iss. 6, pp. 3194-3204
Closed Access | Times Cited: 135
Design of experiments and response surface methodology to tune machine learning hyperparameters, with a random forest case-study
Gustavo A. Lujan-Moreno, Phillip Howard, Omar Rojas, et al.
Expert Systems with Applications (2018) Vol. 109, pp. 195-205
Closed Access | Times Cited: 129
An intelligent fault identification method of rolling bearings based on LSSVM optimized by improved PSO
Hongbo Xü, Guohua Chen
Mechanical Systems and Signal Processing (2012) Vol. 35, Iss. 1-2, pp. 167-175
Closed Access | Times Cited: 107
A multi-objective genetic optimization for fast, fuzzy rule-based credit classification with balanced accuracy and interpretability
Marian B. Gorzałczany, Filip Rudziński
Applied Soft Computing (2015) Vol. 40, pp. 206-220
Closed Access | Times Cited: 102
Big Data techniques to measure credit banking risk in home equity loans
Agustín Pérez, Agustin Pérez-Torregrosa, Marta Vaca
Journal of Business Research (2018) Vol. 89, pp. 448-454
Closed Access | Times Cited: 97
A novel ensemble classification model based on neural networks and a classifier optimisation technique for imbalanced credit risk evaluation
Feng Shen, Xingchao Zhao, Zhiyong Li, et al.
Physica A Statistical Mechanics and its Applications (2019) Vol. 526, pp. 121073-121073
Closed Access | Times Cited: 91
A firefly algorithm modified support vector machine for the credit risk assessment of supply chain finance
Hao Zhang, Yuxin Shi, Xueran Yang, et al.
Research in International Business and Finance (2021) Vol. 58, pp. 101482-101482
Closed Access | Times Cited: 89
Hyperparameter Tuning of Machine Learning Algorithms Using Response Surface Methodology: A Case Study of ANN, SVM, and DBN
Warut Pannakkong, Kwanluck Thiwa-anont, Kasidit Singthong, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-17
Open Access | Times Cited: 61
A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain
Gang Yao, Xiaojian Hu, Guanxiong Wang
Expert Systems with Applications (2022) Vol. 200, pp. 117002-117002
Closed Access | Times Cited: 54
Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods
Xiaoming Zhang, Lean Yu
Expert Systems with Applications (2023) Vol. 237, pp. 121484-121484
Closed Access | Times Cited: 26
A literature review on the application of evolutionary computing to credit scoring
Ana I. Marqués, Vicente García, J. Salvador Sánchez
Journal of the Operational Research Society (2012) Vol. 64, Iss. 9, pp. 1384-1399
Open Access | Times Cited: 106
Forecasting of turbine heat rate with online least squares support vector machine based on gravitational search algorithm
Weiping Zhang, Peifeng Niu, Guoqiang Li, et al.
Knowledge-Based Systems (2012) Vol. 39, pp. 34-44
Closed Access | Times Cited: 86
A Pruning Neural Network Model in Credit Classification Analysis
Yajiao Tang, Junkai Ji, Shangce Gao, et al.
Computational Intelligence and Neuroscience (2018) Vol. 2018, pp. 1-22
Open Access | Times Cited: 59
Credit Scoring: A Review on Support Vector Machines and Metaheuristic Approaches
Rui Ying Goh, Lai Soon Lee
Advances in Operations Research (2019) Vol. 2019, pp. 1-30
Open Access | Times Cited: 58
Investigating the beneficial impact of segmentation-based modelling for credit scoring
Khaoula Idbenjra, Kristof Coussement, Arno De Caigny
Decision Support Systems (2024) Vol. 179, pp. 114170-114170
Closed Access | Times Cited: 7
Prediction of bank credit worthiness through credit risk analysis: an explainable machine learning study
Victor Chang, Qianwen Xu, Shola Habib Akinloye, et al.
Annals of Operations Research (2024)
Open Access | Times Cited: 6
Balancing accuracy, complexity and interpretability in consumer credit decision making: A C-TOPSIS classification approach
Xiaoqian Zhu, Jianping Li, Dengsheng Wu, et al.
Knowledge-Based Systems (2013) Vol. 52, pp. 258-267
Closed Access | Times Cited: 59
A novel multistage deep belief network based extreme learning machine ensemble learning paradigm for credit risk assessment
Lean Yu, Zebin Yang, Ling Tang
Flexible Services and Manufacturing Journal (2015) Vol. 28, Iss. 4, pp. 576-592
Closed Access | Times Cited: 49
An improved SMO algorithm for financial credit risk assessment – Evidence from China’s banking
Qi Zhang, Jue Wang, Aiguo Lu, et al.
Neurocomputing (2017) Vol. 272, pp. 314-325
Closed Access | Times Cited: 42
Application of a rule extraction algorithm family based on the Re-RX algorithm to financial credit risk assessment from a Pareto optimal perspective
Yoichi Hayashi
Operations Research Perspectives (2016) Vol. 3, pp. 32-42
Open Access | Times Cited: 38
Page 1 - Next Page

Scroll to top