scholarly journals Corporate Social Responsibility Based on Radial Basis Function Neural Network Evaluation Model of Low-Carbon Circular Economy Coupled Development

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zenghua Gong ◽  
Kaiyi Guo ◽  
Xiaoguang He
Keyword(s):  
Neural Network ◽  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Radial Basis Function ◽  
Basis Function ◽  
Circular Economy ◽  
Evaluation Model ◽  
Low Carbon ◽  
Radial Basis ◽  
Corporate Social

Under the background that the development of low-carbon circular economy is the objective requirement for the in-depth implementation of scientific development and the inevitable choice for promoting the sustainable development of economy and society, it is not only the requirement of corporate social responsibility but also the path to realize corporate social responsibility. Enterprises should become the representative and model of social responsibility practice in the development of low-carbon circular economy, in order to promote the fulfilment and development of corporate social responsibility in the whole society. Therefore, it is of great theoretical and practical significance to study the realization of corporate social responsibility in the context of low-carbon circular economy. This paper introduces the connotation of low-carbon circular economy and corporate social responsibility, analyses the reality and theoretical basis of realizing corporate social responsibility in low-carbon circular economy, analyses the interactive relationship between the development of low-carbon circular economy and the realization of corporate social responsibility, and puts forward the construction of enterprise low-carbon operation mechanism. This paper uses the research of corporate social responsibility based on radial basis function neural network to build a low-carbon circular economy. The evaluation model of environment economy coupling development is verified by an example, which provides useful guidance for the evaluation and development of corporate social responsibility.

scholarly journals A Novel Evaluation Model for Urban Smart Growth Based on Principal Component Regression and Radial Basis Function Neural Network

2019 ◽  
Vol 11 (21) ◽  
pp. 6125
Author(s):  
Lianyan Li ◽  
Xiaobin Ren
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Basis Function ◽  
Rbf Neural Network ◽  
Evaluation Model ◽  
Smart Growth ◽  
Principal Component Regression ◽  
Principal Component ◽  
Self Organizing Map ◽  
Radial Basis

Smart growth is widely adopted by urban planners as an innovative approach, which can guide a city to develop into an environmentally friendly modern city. Therefore, determining the degree of smart growth is quite significant. In this paper, sustainable degree (SD) is proposed to evaluate the level of urban smart growth, which is established by principal component regression (PCR) and the radial basis function (RBF) neural network. In the case study of Yumen and Otago, the SD values of Yumen and Otago are 0.04482 and 0.04591, respectively, and both plans are moderately successful. Yumen should give more attention to environmental development while Otago should concentrate on economic development. In order to make a reliable future plan, a self-organizing map (SOM) is conducted to classify all indicators and the RBF neural network-trained indicators are separate under different classifications to output new plans. Finally, the reliability of the plan is confirmed by cellular automata (CA). Through simulation of the trend of urban development, it is found that the development speed of Yumen and Otago would increase slowly in the long term. This paper provides a powerful reference for cities pursuing smart growth.

Application of Radial Basis Function Neural Network to Support Concept Evaluation

2012 ◽  
Vol 472-475 ◽  
pp. 1926-1931
Author(s):  
Qing Wei Yang ◽  
Nai Chao Wang ◽  
Ma Lin
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Basis Function ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Rbf Neural Network ◽  
Evaluation Model ◽  
Concept Evaluation ◽  
Radial Basis ◽  
Design Characteristics

In order to solve the problem that how to evaluate the complex system support concept, an evaluation method based on Radial Basis Function (RBF) neural network model was presented. Through researching the support system overall design characteristics and elements of support, on this basis, evaluation parameters of support concept were abstracted. Support concept evaluation model based on RBF was established and a mature and stable RBF neural network was trained to calculate the comprehensive evaluation value for support concept. Finally, the further demonstration and verification of the method are given through specific case application and compared with the result for evaluation results of data envelopment analysis (DEA) model.

scholarly journals CORPORATE SOCIAL RESPONSIBILITY AND CONSUMERS’ WASTE SORTING HABITS

2017 ◽  
Vol 5 ◽  
pp. 51-56
Author(s):  
Solveiga Blumberga ◽  
Ance Saulīte
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Circular Economy ◽  
Low Carbon ◽  
The European Union ◽  
Low Carbon Economy ◽  
Large Size ◽  
Sorting Process ◽  
Common Effort ◽  
Corporate Social

The transition to circular economy shifts attention to re-use, repair, restoration and recycling of materials and products. What was previously considered to be waste can be turned into resources. The transition to a circular economy where the value of products, materials and resources is maintained for as long as possible and where as little waste is generated as possible is a significant contribution to the common effort in the European Union to create a sustainable low-carbon economy in which resources are used efficiently. Such an approach allows to transform the EU economy and generate new advantages for it (European Commission, 2015). Our individual action and provided support may help peers notice an opportunity and a solution for the future. The aims of the study are: To investigate the evaluation of the significance of the consumers’ corporate social responsibility and waste-sorting habits and to provide recommendations for improved access to the separate waste collection service. The research questions for achieving the objectives of the study were the following: How do consumers evaluate corporate social responsibility of companies in general? What are the waste-sorting habits of consumers? Are there statistically significant differences in the waste-sorting habits between various consumer generations? The authors prepared a unique consumer survey in which economically active inhabitants of the capital of Latvia, aged 15 to 71 years, participated. The results of our survey showed that the respondents rated the corporate social responsibility of companies as essential and emphasized that it was important for the large-size enterprises to operate ethically. The waste-sorting process itself creates disbelief among the respondents and also suspicion that all sorted waste is lumped together and removed to disposal sites.

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