Real-world credit scoring: a comparative study of statistical and artificial intelligent methods

Zhao, Ying; Habib, Tabassum; Chi, Guotai; Uddin, Mohammad Shamsu

doi:10.1504/ijkedm.2019.097357

Cited by 3 publications

(1 citation statement)

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“…The evaluation of model performance is different, because different performance measures are adopted for dif-ferent data sets with different properties in different situations. Therefore, on six real-world intelligent data sets, combined with ten representative performance standards, this study adopts six famous intelligent evaluation classification methods for comprehensive evaluation [11]. In order to study related things, a comprehensive intelligent scoring model is established, which considers various additional variable groups, which increase the accuracy of the model.…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Scoring and Style of Calligraphy Post Based on Machine Vision

Zhou

2022

Journal of Sensors

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Machine vision is a noncontact measurement method. In some jobs that are not suitable for artificial work environment or artificial vision, machine vision is usually used to replace artificial vision to meet the traditional requirements. Therefore, this paper quotes machine vision into the intelligent scoring and style research of calligraphy post. Firstly, it briefly introduces the related concepts and steps of calligraphy post and briefly explains the style of calligraphy post. Then for the third part of the machine vision localization research algorithm, the correlation function algorithm was proposed in the research field to explain and analyze. Finally, by comparing other research methods of machine vision, it shows that machine vision is more conducive to the study of calligraphy style intelligent scoring, through the experimental study of people on the calligraphy style and calligraphy style of people on the intelligent score. At the end, it is proposed that machine vision can greatly promote the study of intelligent scoring and style of calligraphy and also reflect the accuracy and usability of intelligent scoring for calligraphy style. On-contact test of machine vision refers to not touching the tested object, so as to obtain the test result. It is a three-dimensional testing technology. Among them, the test system of machine vision is relatively simple. It is easy to move and easy to collect data, and the cost of this noncontact test is low. It has more accurate testing technology. A plurality of test quantities can be simultaneously tested by image laser detection of the test quantity without touching the object.

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Section: Introductionmentioning

confidence: 99%

Research on Intelligent Scoring and Style of Calligraphy Post Based on Machine Vision

Zhou

2022

Journal of Sensors

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Machine Learning in Credit Risk Modeling: Empirical Application of Neural Network Approaches

Uddin

2021

The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success

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Rapid growth of MXene-based membranes for sustainable environmental pollution remediation

et al. 2023

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Real-world credit scoring: a comparative study of statistical and artificial intelligent methods

Cited by 3 publications

References 0 publications

Research on Intelligent Scoring and Style of Calligraphy Post Based on Machine Vision

Research on Intelligent Scoring and Style of Calligraphy Post Based on Machine Vision

Machine Learning in Credit Risk Modeling: Empirical Application of Neural Network Approaches

Rapid growth of MXene-based membranes for sustainable environmental pollution remediation

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