<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The evaluation of the scientific research projects is an important procedure before the scientific research projects are approved. The BP neural network and linear neural network are adopted to evaluate the scientific research projects in this paper. The evaluation index system with 12 indexes is set up. The basic principle of the neural network is analyzed and then the BP neural network and linear neural network models are constructed and the output error function of the neural networks is introduced. The Matlab software is applied to set the parameters and calculate the neural networks. By computing a real-world example, the evaluation results of the scientific research projects are obtained and the results of the BP neural network, linear neural network and linear regression forecasting are compared. The analysis shows that the BP neural network has higher efficiency than the linear neural network and linear regression forecasting in the evaluation of the scientific research projects problem. The method proposed in this paper is an effective method to evaluate the scientific research projects.</p></abstract>

The evaluation of the scientific research projects is an important procedure before the scientific research projects are approved. The BP neural network and linear neural network are adopted to evaluate the scientific research projects in this paper. The evaluation index system with 12 indexes is set up. The basic principle of the neural network is analyzed and then the BP neural network and linear neural network models are constructed and the output error function of the neural networks is introduced. The Matlab software is applied to set the parameters and calculate the neural networks. By computing a real-world example, the evaluation results of the scientific research projects are obtained and the results of the BP neural network, linear neural network and linear regression forecasting are compared. The analysis shows that the BP neural network has higher efficiency than the linear neural network and linear regression forecasting in the evaluation of the scientific research projects problem. The method proposed in this paper is an effective method to evaluate the scientific research projects.

An Effective Method to Evaluate the Scientific Research Projects

Science and Technology Division, Beijing Jiaotong University, 100044 Beijing, China

School of Economics and Management, Beijing Jiaotong University, 100044 Beijing, China

School of Traffic and Transportation, Beijing Jiaotong University, 100044 Beijing, China

Foundations of Computing and Decision Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"An Effective Method to Evaluate the Scientific Research Projects"}

The evaluation of the scientific research projects is an important procedure before the scientific research projects are approved. The BP neural network and...

An Effective Method to Evaluate the Scientific Research Projects

Online veröffentlicht: 09. Sept. 2014

Seitenbereich: 175 - 188

DOI: https://doi.org/10.2478/fcds-2014-0010

Schlüsselwörter
effective method, evaluation, scientific research projects, index system, neural network

© by Xiaohui Hou

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

An Effective Method to Evaluate the Scientific Research Projects

Online veröffentlicht: 09. Sept. 2014

Seitenbereich: 175 - 188

DOI: https://doi.org/10.2478/fcds-2014-0010

Schlüsselwörtereffective method, evaluation, scientific research projects, index system, neural network

© by Xiaohui Hou

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
effective method, evaluation, scientific research projects, index system, neural network