N
Ning Chen
Researcher at Instituto Superior de Engenharia do Porto
Publications - 37
Citations - 593
Ning Chen is an academic researcher from Instituto Superior de Engenharia do Porto. The author has contributed to research in topics: Bankruptcy prediction & Learning vector quantization. The author has an hindex of 11, co-authored 34 publications receiving 497 citations. Previous affiliations of Ning Chen include Polytechnic Institute of Porto.
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Financial credit risk assessment: a recent review
TL;DR: The traditional statistical models and state-of-the-art intelligent methods for financial distress forecasting are summarized, with the emphasis on the most recent achievements as the promising trend in this area.
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Clustering and visualization of bankruptcy trajectory using self-organizing map
TL;DR: This study uses self-organizing map (SOM) to analyze and visualize the financial situation of companies over several years through a two-step clustering process and demonstrates the promising functionality of SOM for bankruptcy trajectory clustering and visualization.
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A genetic algorithm-based approach to cost-sensitive bankruptcy prediction
TL;DR: This paper presents an evolutionary approach for optimizing simultaneously the complexity and the weights of learning vector quantization network under the symmetric cost preference and shows significant reduction of features without the degradation of prediction capability.
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Enhanced default risk models with SVM
TL;DR: Experimental results in the setting of a heterogeneous data set of French companies demonstrated that the proposed default risk model showed better predictability performance than the baseline SVM and multi-task learning with SVM.
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During-incident process assessment in emergency management: Concept and strategy
TL;DR: In this article, the authors analyzed the influencing factors of during-incident process assessment and proposed a conceptual model of assessment, which quantitatively characterize the evolution of incidents and corresponding responses, and hence contribute to appropriate decisions in practical applications.