English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 52047/87178 (60%)
造訪人次 : 8689050      線上人數 : 169
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107497

    題名: Using grouping genetic algorithm to mine diverse group stock portfolio
    作者: Chen, Chun-Hao;Lu, Cheng-Yu;Hong, Tzung-Pei;Su, Ja-Hwung
    關鍵詞: grouping genetic algorithms;group stock portfolio;maximally diverse grouping problem;portfolio optimization
    日期: 2016-07-29
    上傳時間: 2016-09-20 02:10:34 (UTC+8)
    摘要: In this paper, to increase the diversity of stock portfolios, the diverse group stock portfolio mining algorithm is proposed by grouping genetic algorithm. Each chromosome is represented by grouping, stock and stock portfolio parts. The fitness function that consists of portfolio satisfaction, group balance and diversity factor is designed to evaluate quality of chromosomes. The diversity factor is used to make the numbers of stock categories in groups as similar as possible. The genetic operations are then executed on population to generate offspring to find the near optimal group stock portfolio. Finally, experiments on a real financial data were made to show the proposed approach is effective.
    關聯: 2016 IEEE World Congress on Computational Intelligence (IEEE WCCI), pp. 1-5
    顯示於類別:[資訊工程學系暨研究所] 會議論文


    檔案 描述 大小格式瀏覽次數
    program_at_a_glance.pdf議程132KbAdobe PDF17檢視/開啟



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋