首页    期刊浏览 2024年11月15日 星期五
登录注册

文章基本信息

  • 标题:Predictive Analysis for Journal Abstracts using Polynomial Neural Networks Algorithm
  • 本地全文:下载
  • 作者:Adebola K. Ojo
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2017
  • 卷号:14
  • 期号:4
  • 出版社:IJCSI Press
  • 摘要:Academic journals are an important outlet for dissemination of academic research. In this study, Neural Networks model was used in the prediction of abstracts from The Institute of Electrical and Electronics Engineers (IEEE) Transactions on Computers. Simulation of results was done using the Polynomial Neural Networks algorithm. This algorithm, which is based on Group Method of Data Handling (GMDH) method, utilizes a class of polynomials such as linear, quadratic and modified quadratic. The prediction was done for a period of twenty-four months using a predictive model of three layers and two coefficients. The performance measures used in this study were mean square errors, mean absolute error and root mean square error.
  • 关键词:Polynomial Neural Networks; IEEE; GMDH; mean square errors; mean absolute error; Root mean square error
国家哲学社会科学文献中心版权所有