Xiaoman Wu, Jun Liu and Yulian Peng
Without damaging and consuming natural resources, green computing technology can meet the needs of society for a long time. This paper discusses how to realize the sustainable…
Abstract
Purpose
Without damaging and consuming natural resources, green computing technology can meet the needs of society for a long time. This paper discusses how to realize the sustainable development of social economy through the innovation of green computing technology.
Design/methodology/approach
For the green computing technology and sustainable social and economic development problems, it builds back propagation (BP) neural network model and analyzes the topological structure of the network model as well as the impact of the training errors allowed by the network on its performance.
Findings
By optimizing the number of input nodes, the number of hidden nodes and the target value, the genetic algorithm (GA) can get the optimal neural network model. The simulation experiment proves that the proposed model is effective.
Originality/value
It can not only reduce the possibility of falling into local optimum, but also optimize the initial weights and thresholds of BP neural network and further improve the stability and test effect of BP neural network model.
Details
Keywords
Qiuhong Chen, Ning Geng and Kan Zhu
The purpose of this paper is to reveal the distributional characteristics and evolutional patterns in source periodicals, topics, authors, funding, and institutes of research…
Abstract
Purpose
The purpose of this paper is to reveal the distributional characteristics and evolutional patterns in source periodicals, topics, authors, funding, and institutes of research papers in Chinese Agricultural Economics so as to understand the current situations and developmental tendency of Chinese agricultural economics research over the past decade.
Design/methodology/approach
Using the citation analysis method, this paper analyzed the distributional characteristics and evolution of source periodicals, fields, authors and topics of 2,203 highly cited journal papers from the database of China National Knowledge Infrastructure (CNKI) and 189 cited journal papers from database of Social Sciences Citation Index (SSCI) in agricultural economics first-authored by Chinese scholars from 2006 to 2015.
Findings
First, over the past decade, agricultural economics research in China has seen a rapid development. Specially, 103 scholars and 42 institutes have played key roles in the development, and 12 Chinese periodicals and 3 international journals have been the most influential outlets. Second, the coverage of the topics in Chinese agricultural economics research is broad and has expanded over the past decade. The rural land issue has been the most popular topic, while the issues regarding rural institutional arrangements and industrialization in rural areas have been explored extensively. However, issues in other fields, such as agricultural markets and trade, rural labor, food safety, etc. have to be further studied. Third, the improvements of economic theory and quantitative analytic techniques, the supports from research funding, and an increase in the collaboration between Chinese scholars and those from other countries have made great contribution to the rapid development of Chinese agricultural economics research over the past decade.
Originality/value
This paper is an original work that identifies the most influential journal papers including highly cited journal papers from CNKI and cited journal papers from SSCI, using citation frequency and standard Essential Science Indicators method. This is a contribution relative to the methods used by previous studies, which did not account for frequency of citation of a paper. Moreover, this study is based on data from two databases, CNKI and SSCI, suggesting that the coverage of sample papers is broader compared to those of previous studies.