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An enforced support vector machine model for construction contractor default prediction · Study

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ArticleAn enforced support vector machine model for construction contractor default prediction

H. Ping Tserng2011

Article2011

An enforced support vector machine model for construction contractor default prediction

H. Ping Tserng · Gwo‐Fong Lin · L. Ken Tsai · Po‐Cheng Chen

73 citations·0/0 files stored·Automation in Construction

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Financial Distress and Bankruptcy Prediction Forecasting Techniques and Applications Imbalanced Data Classification Techniques

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1966Financial Ratios As Predictors of Failure 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models 2004Assessing the Probability of Bankruptcy 1998Is the Risk of Bankruptcy a Systematic Risk?2005Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters 1990A neural network model for bankruptcy prediction

Cited by

2020Enhancing the Knowledge of Construction Business Failure: A Social Network Analysis Approach 2017Estimation of Costs and Durations of Construction of Urban Roads Using ANN and SVM 2020Detecting corporate misconduct through random forest in China’s construction industry 2014PREDICTION OF DEFAULT PROBABILITY FOR CONSTRUCTION FIRMS USING THE LOGIT MODEL 2019Business Failure Prediction of Construction Contractors Using a LSTM RNN with Accounting, Construction Market, and Macroeconomic Variables

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Details

Year2011

Typearticle

Published2011-06-27

VenueAutomation in Construction

ISSN-L0926-5805

Languageen

Citations73

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1016/j.autcon.2011.05.007

openalex_workW2049477141

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2017A support vector machine method for bid/no bid decision making

2016Critical factors for insolvency prediction: towards a theoretical model for the construction industry

2015Evaluating Contractor Financial Status Using a Hybrid Fuzzy Instance Based Classifier: Case Study in the Construction Industry