On Evaluation Model of Green Technology Innovation Capability of Pulp and Paper Enterprise Based on Support Vector Machines

2014 ◽  
Vol 886 ◽  
pp. 285-288 ◽  
Author(s):  
Zhi Fang Zhou
Keyword(s):  
Support Vector Machines ◽  
Evaluation Method ◽  
Technology Innovation ◽  
Evaluation Model ◽  
Green Technology ◽  
Pulp And Paper ◽  
Evaluation Index System ◽  
Support Vector ◽  
Innovation Capability ◽  
Vector Machines

Based on the analysis of the concept of green technology innovation capability, this paper not only structures the evaluation index system of green technology innovation capability in pulp and paper enterprises, builds the evaluation model of green technology innovation capability for pulp and paper enterprises based on Support Vector Machines with Radial Basis Function kernel, but also achieves the optimization of kernel function parameters, penalty factors and insensitive parameters based on a heuristic algorithm for tuning hyper-parameters. This model is more suitable for pulp and paper enterprises to evaluate green technology innovation capability, compared with the evaluation method of BP neural network.

Evaluation of Green Technology Innovation Capacity of Automobile Manufacture Industry

2010 ◽  
Vol 44-47 ◽  
pp. 206-212
Author(s):  
Yan Rong Wang ◽  
Qiao Ling Xu
Keyword(s):  
Technology Innovation ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Green Technology ◽  
Evaluation Index System ◽  
Ecological Environment ◽  
Matlab Toolbox ◽  
Comprehensive Evaluation Model ◽  
Innovation Capacity ◽  
Manufacture Industry

to cope with the pressure of energy and ecological environment, automobile manufacture industry must implement green technology innovation. According to the characteristics of green technology innovation, the paper puts forward evaluation index system of green technology innovation capacity , establishes comprehensive evaluation model based on improved BP neutral algorithm by Matlab toolbox, and carries out empirical analysis of data from automobile manufacture industry, finally reaches a conclusion.

scholarly journals Evaluation of SMEs’ Credit Decision Based on Support Vector Machine-Logistics Regression

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Rui Xie ◽  
Rui Liu ◽  
Xian-Bei Liu ◽  
Jia-Ming Zhu
Keyword(s):  
Decision Making ◽  
Credit Risk ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Classification Model ◽  
Support Vector ◽  
Logistics Regression ◽  
Vector Machines ◽  
Comprehensive Evaluation Model

This article uses support vector machines, logistics regression, and other methods for the comprehensive evaluation of credit decision-making of small, medium, and microenterprises and comprehensively uses software programming such as MATLAB and SPSS Modeler to solve the problem. The results, such as credit risk evaluation index system, credit risk classification model, and credit decision-making comprehensive evaluation model, are obtained. Finally, this article starts from the credit decision of small, medium, and microenterprises and provides theoretical and practical suggestions for banks to control the risks of small, medium, and microenterprises and their own development.

The Ancient Ceramics Identification Methods Based on Non-Linear Support Vector Machines

2013 ◽  
Vol 278-280 ◽  
pp. 1201-1204
Author(s):  
Ru Zhang
Keyword(s):  
Evaluation Model ◽  
Evaluation Index System ◽  
Support Vector ◽  
Intelligent Algorithm ◽  
Ancient Ceramics ◽  
Classifier Design ◽  
Vector Machines ◽  
Non Linear ◽  
Machine Analysis ◽  
White Porcelain

With the ceramics market's developing, the use of image processing and intelligent algorithm is applied to the ancient ceramics recognition and appreciation is one of the most challenging issues in the field of ancient ceramics. Article focuses on selected Ming Qing Dynasty blue and white porcelain as research samples, and explore how to extract the effective image recognition features of ancient ceramics, and to quantify the comparison, given the ancient craft of evaluation index system, and improve the identification of categories of, and appreciation evaluation model to extract special recognition feature, image preprocessing, discussion handwritten the key technology of Chinese character segmentation, feature extraction and classifier design a variety of methods, and non-linear support vector machine analysis method using multiple classifiers based, so that the sample's accuracy greatly improved.

Comprehensive Evaluation of the Technology Innovation Capability of China’s High-tech Industries Based on Fuzzy Borda Combination Method

2015 ◽  
Vol 7 (3) ◽  
pp. 215-230 ◽  
Author(s):  
Yue Hong ◽  
Dongxiao Niu ◽  
Bowen Xiao ◽  
Lingnan Wu
Keyword(s):  
Evaluation Method ◽  
Technology Innovation ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Objective Evaluation ◽  
Combination Method ◽  
High Tech ◽  
Fuzzy Evaluation ◽  
Innovation Capability ◽  
Capability Evaluation

Technology innovation capability is a main driver in improving a country’s industrial competitiveness. Development prospects and development speed are strongly dependent on industry innovation capability. Therefore, how to effectively and correctly evaluate the innovation capability of industry is of great importance. On the basis of previous research, this paper establishes an index system for evaluating the technology innovation capability of China’s high-tech industries. The index is characterized by the objective evaluation of objects with measurable indexes. The fuzzy Borda method uses precise digital methods to handle fuzzy evaluation objects; therefore, more scientific and pragmatic quantitative criteria are obtained with qualitative and quantitative evaluation results. This paper is the first attempt to apply the fuzzy Borda combination method to high-tech industry innovation capability evaluation. We establish a fuzzy Borda combination model based on four kinds of single evaluation models. By making a combination evaluation, the disadvantages of a single evaluation method are avoided. In the end, based on the fuzzy Borda combination evaluation model, the real technology innovation data of 2013 is analyzed and the innovation capability of individual industry is ranked, which will provide useful guidance for decision-making administrators.

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