首页> 外文期刊>International Journal of Innovative Computing Information and Control >AN IMPROVED FORECASTING MODEL BASED ON THE WEIGHTED FUZZY RELATIONSHIP MATRIX COMBINED WITH A PSO ADAPTATION FOR ENROLLMENTS
【24h】

AN IMPROVED FORECASTING MODEL BASED ON THE WEIGHTED FUZZY RELATIONSHIP MATRIX COMBINED WITH A PSO ADAPTATION FOR ENROLLMENTS

机译:基于加权模糊关系矩阵结合PSO自适应的改进预测模型

获取原文
获取原文并翻译 | 示例
           

摘要

Most fuzzy forecasting approaches are based on modeling fuzzy relations according to the past data. In this paper, an improved forecasting model which combines weighted fuzzy relationship matrices and particle swarm optimization is presented for enrollments. First, the weighted fuzzy relationship matrices are more effective to capture fuzzy relations on time series data than fuzzy logical relationship rules. Second, the particle swarm optimization for the optimized lengths of intervals is developed to adjust interval lengths by searching the space of the universe of discourse. To verify the effectiveness of the proposed model, the empirical data for the enrollments of the University of Alabama are illustrated, and the experimental results show that the proposed model outperforms those of previous forecasting models for both the training and testing phases with various orders and different interval lengths. These results are very encouraging for future work on the development of fuzzy time series and particle swarm optimization in forecasting real-world applications.
机译:大多数模糊预测方法都是基于根据过去的数据对模糊关系进行建模。本文提出了一种改进的预测模型,该模型结合了加权模糊关系矩阵和粒子群优化算法用于招生。首先,加权模糊关系矩阵比模糊逻辑关系规则更有效地捕获时间序列数据上的模糊关系。其次,针对搜索区间的最佳长度发展了粒子群优化算法,以通过搜索话语空间来调整区间长度。为了验证该模型的有效性,对阿拉巴马大学的入学经验数据进行了说明,实验结果表明,该模型在训练阶段和测试阶段(无论阶次和不同)均优于先前的预测模型。间隔长度。这些结果对于未来在预测实际应用中开发模糊时间序列和粒子群优化方面的工作非常令人鼓舞。

著录项

  • 来源
  • 作者单位

    Department of Computer Science and Information Engineering National Taiwan University of Science and Technology No. 43, Sec. 4, Keelung Rd., Taipei 106, Taiwan;

    Department of Computer Science and Information Engineering National Taiwan University of Science and Technology No. 43, Sec. 4, Keelung Rd., Taipei 106, Taiwan;

    Department of Electronic Engineering Technology and Science Institute of Northern Taiwan No. 2, Xueyuan Rd., Peitou, Taipei 112, Taiwan;

    Department of Electronic Engineering National United University No. 1, Lien-Kung, Miao-Li 360, Taiwan;

    Department of Electronic Engineering National United University No. 1, Lien-Kung, Miao-Li 360, Taiwan;

    Department of Electronic Engineering National United University No. 1, Lien-Kung, Miao-Li 360, Taiwan;

    Department of Information Management St. Mary's Medicine Nursing and Management College No. 100, Sec. 2, San-shing Rd., Da-yin Village, Yilan County 266, Taiwan;

    Center of Excellence in Information Assurance King Saud University Kingdom of Saudi Arabia;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    fuzzy time series; particle swarm optimization; fuzzy logical relationship; fuzzy relationship matrix;

    机译:模糊时间序列;粒子群优化;模糊逻辑关系;模糊关系矩阵;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号