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tmy1977金蟲 (正式寫手)
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[求助]
請哪位朋友幫忙查一下下面這篇文章是否被Sci檢索?謝謝!
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1. 題名: A new descent memory gradient method and its global convergence 2. 作者: Min Sun and Qingguo Bai 3. 期刊題名: Journal of Systems Science and Complexity 4. 出版社: Springer 5. 年份: 2011年 6. 卷期和頁碼: Volume 24, Number 4, 784-794. |
金蟲 (正式寫手)
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1. タイトル: A new descent memory gradient method and its global convergence 著者名: Sun Min; Bai Qingguo ジャーナル名: JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY 巻: 24 號: 4 ページ: 784-794 DOI: 10.1007/s11424-011-8150-0 発行: AUG 2011 被引用數(shù): 0 (Web of Science から) [ 抄録を非表示] In this article, a new descent memory gradient method without restarts is proposed for solving large scale unconstrained optimization problems. The method has the following attractive properties: 1) The search direction is always a sufficiently descent direction at every iteration without the line search used; 2) The search direction always satisfies the angle property, which is independent of the convexity of the objective function. Under mild conditions, the authors prove that the proposed method has global convergence, and its convergence rate is also investigated. The numerical results show that the new descent memory method is efficient for the given test problems. |
金蟲 (正式寫手)
新蟲 (正式寫手)
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CSDL Union NCL OPAC (0) 保存為: 更多選項 A new descent memory gradient method and its global convergence 作者: Sun, M (Sun, Min)1; Bai, QG (Bai, Qingguo)2 來源出版物: JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY 卷: 24 期: 4 頁: 784-794 DOI: 10.1007/s11424-011-8150-0 出版年: AUG 2011 被引頻次: 0 (來自 Web of Science) 引用的參考文獻: 18 [ 查看 Related Records ] 引證關(guān)系圖 摘要: In this article, a new descent memory gradient method without restarts is proposed for solving large scale unconstrained optimization problems. The method has the following attractive properties: 1) The search direction is always a sufficiently descent direction at every iteration without the line search used; 2) The search direction always satisfies the angle property, which is independent of the convexity of the objective function. Under mild conditions, the authors prove that the proposed method has global convergence, and its convergence rate is also investigated. The numerical results show that the new descent memory method is efficient for the given test problems. 入藏號: WOS:000293858300014 文獻類型: Article 語種: English 作者關(guān)鍵詞: Global convergence; memory gradient method; sufficiently descent KeyWords Plus: LINE SEARCH; CONJUGATE 通訊作者地址: Sun, M (通訊作者),Zaozhuang Univ, Dept Math & Informat Sci, Zaozhuang 277160, Peoples R China 地址: 1. Zaozhuang Univ, Dept Math & Informat Sci, Zaozhuang 277160, Peoples R China 2. Qufu Normal Univ, Sch Management, Rizhao 276826, Peoples R China 電子郵件地址: sunmin_2008@yahoo.com.cn, qfnubaiqg@163.com 基金資助致謝: 基金資助機構(gòu) 授權(quán)號 National Science Foundation of China 70971076 Foundation of Shandong Provincial Education Department J10LA59 [顯示基金資助信息][隱藏基金資助信息] This research is supported by the National Science Foundation of China under Grant No. 70971076 and the Foundation of Shandong Provincial Education Department under Grant No. J10LA59. 出版商: SPRINGER HEIDELBERG, TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY Web of Science 分類: Mathematics, Interdisciplinary Applications 學(xué)科類別: Mathematics IDS 號: 806ZW ISSN: 1009-6124 |
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