Development Evaluation Model of the low-carbon Economy Based on Fuzzy Support Vector Machines

2013 ◽  
Vol 4 (5) ◽  
pp. 9-15
Author(s):  
Min Li
Keyword(s):  
Support Vector Machines ◽  
Evaluation Model ◽  
Support Vector ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Vector Machines ◽  
Fuzzy Support Vector Machines ◽  
Development Evaluation ◽  
Carbon Economy

scholarly journals Classification of the Priority of Auditing XBRL Instance Documents with Fuzzy Support Vector Machines Algorithm

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Guang-Yih Sheu
Keyword(s):  
Support Vector Machines ◽  
Financial Distress ◽  
Fuzzy Variable ◽  
Financial Ratios ◽  
Misclassification Rate ◽  
Benford’S Law ◽  
Support Vector ◽  
Vector Machines ◽  
Benford's Law ◽  
Fuzzy Support Vector Machines

Concluding the conformity of XBRL (eXtensible Business Reporting Language) instance documents law to the Benford's law yields apparently different results before and after a company's financial distress. These results bring an idea of finding fraudulent documents from the inspection of financial ratios since the unacceptable conformity implies a large likelihood of a fraudulent document. Fuzzy support vector machines models are developed to implement such an idea. The dependent variable is a fuzzy variable quantifying the conformity of an XBRL instance document to the Benford's law; whereas, independent variables are financial ratios. Nevertheless, insufficient data are available to define any membership function for describing the fuzziness in independent and dependent variables, but the interval factor method is introduced to express that fuzziness. Using the resulting fuzzy support vector machines model, it is suggested that the price-to-book ratio versus equity ratio may be used to classify the priority of auditing XBRL instance documents. The misclassification rate is less than 30 \%. In conclusion, a new and promising application of fuzzy support vector machines algorithm has been found in this study.

Research on the Low-Carbon Benefit Evaluation System of the Logistics Enterprise Based on the FAHP Method

2011 ◽  
Vol 66-68 ◽  
pp. 631-636
Author(s):  
Ye Zhou ◽  
Zhi Song Ye ◽  
Yun Zhu Wang
Keyword(s):  
Emission Reduction ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Economic Benefits ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Logistics Enterprise ◽  
Carbon Economy

The low-carbon economy becomes a hot issue in every country after Copenhagen’s meeting, and Logistics enterprise is an important economic entity to achieve a low carbon economy, so how to effectively evaluate the effect of logistics enterprises and low-carbon benefits of emission reduction become a problem that really needed to solve. Therefore, it evaluated the effects of low-carbon benefits of logistics respectively from the economic benefits, logistics operational efficiency and CO2 emission reduction by AHP. Based on it, logistics enterprise evaluation model of low-carbon benefits was built in the way of fuzzy comprehensive evaluation, and finally verified the effectiveness of the evaluation system with a case.

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