Hui Li
Hui Li
Distinguished Young Professor of Nankai University. Former Professor of Zhejiang Normal University
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Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches
J Sun, H Li, QH Huang, KY He
Knowledge-Based Systems 57, 41-56, 2014
Imbalanced enterprise credit evaluation with DTE-SBD: Decision tree ensemble based on SMOTE and bagging with differentiated sampling rates
J Sun, J Lang, H Fujita, H Li
Information Sciences 425, 76-91, 2018
Data mining method for listed companies’ financial distress prediction
J Sun, H Li
Knowledge-Based Systems 21 (1), 1-5, 2008
Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting
J Sun, H Li, H Fujita, B Fu, W Ai
Information Fusion 54, 128-144, 2020
Ranking-order case-based reasoning for financial distress prediction
H Li, J Sun
Knowledge-Based Systems 21 (8), 868-878, 2008
Predicting business failure using classification and regression tree: An empirical comparison with popular classical statistical methods and top classification mining methods
H Li, J Sun, J Wu
Expert Systems with Applications 37 (8), 5895-5904, 2010
Financial distress prediction using support vector machines: Ensemble vs individual
J Sun, H Li
Applied Soft Computing, 2012
Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble
J Sun, H Fujita, P Chen, H Li
Knowledge-Based Systems 120, 4-14, 2017
AdaBoost ensemble for financial distress prediction: An empirical comparison with data from Chinese listed companies
J Sun, M Jia, H Li
Expert systems with applications 38 (8), 9305-9312, 2011
Listed companies’ financial distress prediction based on weighted majority voting combination of multiple classifiers
J Sun, H Li
Expert Systems with Applications 35 (3), 818-827, 2008
Financial distress early warning based on group decision making
J Sun, H Li
Computers & operations research 36 (3), 885-906, 2009
Predicting business failure using multiple case-based reasoning combined with support vector machine
H Li, J Sun
Expert Systems with Applications 36 (6), 10085-10096, 2009
Forecasting business failure: The use of nearest-neighbour support vectors and correcting imbalanced samples–Evidence from the Chinese hotel industry
H Li, J Sun
Tourism Management 33 (3), 622-634, 2012
Daily tourism volume forecasting for tourist attractions
JW Bi, Y Liu, H Li
Annals of Tourism Research 83, 102923, 2020
Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction
H Li, H Adeli, J Sun, JG Han
Computers & Operations Research 38 (2), 409-419, 2011
The induced continuous ordered weighted geometric operators and their application in group decision making
J Wu, JC Li, H Li, WQ Duan
Computers & Industrial Engineering 56 (4), 1545-1552, 2009
Gaussian case-based reasoning for business failure prediction with empirical data in China
H Li, J Sun
Information Sciences 179 (1-2), 89-108, 2009
Financial distress prediction based on OR-CBR in the principle of k-nearest neighbors
H Li, J Sun, BL Sun
Expert Systems with Applications 36 (1), 643-659, 2009
To buy or not to buy? The effect of time scarcity and travel experience on tourists' impulse buying
C Li, Y Wang, X Lv, H Li
Annals of Tourism Research 86, 103083, 2021
Majority voting combination of multiple case-based reasoning for financial distress prediction
H Li, J Sun
Expert Systems with Applications 36 (3), 4363-4373, 2009
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