當(dāng)前位置: 首頁 SCI期刊 SCIE期刊 計(jì)算機(jī)科學(xué) 中科院3區(qū) JCRQ2 期刊介紹(非官網(wǎng))
    International Journal Of Machine Learning And Cybernetics

    International Journal Of Machine Learning And CyberneticsSCIE

    國際簡稱:INT J MACH LEARN CYB  參考譯名:國際機(jī)器學(xué)習(xí)與控制論雜志

    • 中科院分區(qū)

      3區(qū)

    • CiteScore分區(qū)

      Q1

    • JCR分區(qū)

      Q2

    基本信息:
    ISSN:1868-8071
    E-ISSN:1868-808X
    是否OA:未開放
    是否預(yù)警:否
    TOP期刊:否
    出版信息:
    出版地區(qū):GERMANY
    出版商:Springer Berlin Heidelberg
    出版語言:English
    出版周期:12 issues per year
    出版年份:2010
    研究方向:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
    評(píng)價(jià)信息:
    影響因子:3.1
    H-index:30
    CiteScore指數(shù):7.9
    SJR指數(shù):0.988
    SNIP指數(shù):1.217
    發(fā)文數(shù)據(jù):
    Gold OA文章占比:3.75%
    研究類文章占比:99.66%
    年發(fā)文量:295
    自引率:0.1071...
    開源占比:0.037
    出版撤稿占比:0
    出版國人文章占比:0.56
    OA被引用占比:0.0215...
    英文簡介 期刊介紹 CiteScore數(shù)據(jù) 中科院SCI分區(qū) JCR分區(qū) 發(fā)文數(shù)據(jù) 常見問題

    英文簡介International Journal Of Machine Learning And Cybernetics期刊介紹

    Cybernetics is concerned with describing complex interactions and interrelationships between systems which are omnipresent in our daily life. Machine Learning discovers fundamental functional relationships between variables and ensembles of variables in systems. The merging of the disciplines of Machine Learning and Cybernetics is aimed at the discovery of various forms of interaction between systems through diverse mechanisms of learning from data.

    The International Journal of Machine Learning and Cybernetics (IJMLC) focuses on the key research problems emerging at the junction of machine learning and cybernetics and serves as a broad forum for rapid dissemination of the latest advancements in the area. The emphasis of IJMLC is on the hybrid development of machine learning and cybernetics schemes inspired by different contributing disciplines such as engineering, mathematics, cognitive sciences, and applications. New ideas, design alternatives, implementations and case studies pertaining to all the aspects of machine learning and cybernetics fall within the scope of the IJMLC.

    Key research areas to be covered by the journal include:

    Machine Learning for modeling interactions between systems

    Pattern Recognition technology to support discovery of system-environment interaction

    Control of system-environment interactions

    Biochemical interaction in biological and biologically-inspired systems

    Learning for improvement of communication schemes between systems

    期刊簡介International Journal Of Machine Learning And Cybernetics期刊介紹

    《International Journal Of Machine Learning And Cybernetics》自2010出版以來,是一本計(jì)算機(jī)科學(xué)優(yōu)秀雜志。致力于發(fā)表原創(chuàng)科學(xué)研究結(jié)果,并為計(jì)算機(jī)科學(xué)各個(gè)領(lǐng)域的原創(chuàng)研究提供一個(gè)展示平臺(tái),以促進(jìn)計(jì)算機(jī)科學(xué)領(lǐng)域的的進(jìn)步。該刊鼓勵(lì)先進(jìn)的、清晰的闡述,從廣泛的視角提供當(dāng)前感興趣的研究主題的新見解,或?qū)彶槎嗄陙砟硞€(gè)重要領(lǐng)域的所有重要發(fā)展。該期刊特色在于及時(shí)報(bào)道計(jì)算機(jī)科學(xué)領(lǐng)域的最新進(jìn)展和新發(fā)現(xiàn)新突破等。該刊近一年未被列入預(yù)警期刊名單,目前已被權(quán)威數(shù)據(jù)庫SCIE收錄,得到了廣泛的認(rèn)可。

    該期刊投稿重要關(guān)注點(diǎn):

    Cite Score數(shù)據(jù)(2024年最新版)International Journal Of Machine Learning And Cybernetics Cite Score數(shù)據(jù)

    • CiteScore:7.9
    • SJR:0.988
    • SNIP:1.217
    學(xué)科類別 分區(qū) 排名 百分位
    大類:Computer Science 小類:Computer Vision and Pattern Recognition Q1 21 / 106

    80%

    大類:Computer Science 小類:Software Q1 85 / 407

    79%

    大類:Computer Science 小類:Artificial Intelligence Q1 84 / 350

    76%

    CiteScore 是由Elsevier(愛思唯爾)推出的另一種評(píng)價(jià)期刊影響力的文獻(xiàn)計(jì)量指標(biāo)。反映出一家期刊近期發(fā)表論文的年篇均引用次數(shù)。CiteScore以Scopus數(shù)據(jù)庫中收集的引文為基礎(chǔ),針對(duì)的是前四年發(fā)表的論文的引文。CiteScore的意義在于,它可以為學(xué)術(shù)界提供一種新的、更全面、更客觀地評(píng)價(jià)期刊影響力的方法,而不僅僅是通過影響因子(IF)這一單一指標(biāo)來評(píng)價(jià)。

    歷年Cite Score趨勢(shì)圖

    中科院SCI分區(qū)International Journal Of Machine Learning And Cybernetics 中科院分區(qū)

    中科院 2023年12月升級(jí)版 綜述期刊:否 Top期刊:否
    大類學(xué)科 分區(qū) 小類學(xué)科 分區(qū)
    計(jì)算機(jī)科學(xué) 3區(qū) COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計(jì)算機(jī):人工智能 3區(qū)

    中科院分區(qū)表 是以客觀數(shù)據(jù)為基礎(chǔ),運(yùn)用科學(xué)計(jì)量學(xué)方法對(duì)國際、國內(nèi)學(xué)術(shù)期刊依據(jù)影響力進(jìn)行等級(jí)劃分的期刊評(píng)價(jià)標(biāo)準(zhǔn)。它為我國科研、教育機(jī)構(gòu)的管理人員、科研工作者提供了一份評(píng)價(jià)國際學(xué)術(shù)期刊影響力的參考數(shù)據(jù),得到了全國各地高校、科研機(jī)構(gòu)的廣泛認(rèn)可。

    中科院分區(qū)表 將所有期刊按照一定指標(biāo)劃分為1區(qū)、2區(qū)、3區(qū)、4區(qū)四個(gè)層次,類似于“優(yōu)、良、及格”等。最開始,這個(gè)分區(qū)只是為了方便圖書管理及圖書情報(bào)領(lǐng)域的研究和期刊評(píng)估。之后中科院分區(qū)逐步發(fā)展成為了一種評(píng)價(jià)學(xué)術(shù)期刊質(zhì)量的重要工具。

    歷年中科院分區(qū)趨勢(shì)圖

    JCR分區(qū)International Journal Of Machine Learning And Cybernetics JCR分區(qū)

    2023-2024 年最新版
    按JIF指標(biāo)學(xué)科分區(qū) 收錄子集 分區(qū) 排名 百分位
    學(xué)科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE SCIE Q2 86 / 197

    56.6%

    按JCI指標(biāo)學(xué)科分區(qū) 收錄子集 分區(qū) 排名 百分位
    學(xué)科:COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE SCIE Q2 84 / 198

    57.83%

    JCR分區(qū)的優(yōu)勢(shì)在于它可以幫助讀者對(duì)學(xué)術(shù)文獻(xiàn)質(zhì)量進(jìn)行評(píng)估。不同學(xué)科的文章引用量可能存在較大的差異,此時(shí)單獨(dú)依靠影響因子(IF)評(píng)價(jià)期刊的質(zhì)量可能是存在一定問題的。因此,JCR將期刊按照學(xué)科門類和影響因子分為不同的分區(qū),這樣讀者可以根據(jù)自己的研究領(lǐng)域和需求選擇合適的期刊。

    歷年影響因子趨勢(shì)圖

    發(fā)文數(shù)據(jù)

    2023-2024 年國家/地區(qū)發(fā)文量統(tǒng)計(jì)
    • 國家/地區(qū)數(shù)量
    • CHINA MAINLAND467
    • India63
    • Iran39
    • Australia27
    • USA27
    • Canada17
    • England17
    • Turkey14
    • Saudi Arabia12
    • Taiwan12

    本刊中國學(xué)者近年發(fā)表論文

    • 1、Learning relations in human-like style for few-shot fine-grained image classification

      Author: Li, Shenming; Feng, Lin; Xue, Linsong; Wang, Yifan; Wang, Dong

      Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 377-385. DOI: 10.1007/s13042-021-01473-8

    • 2、Locality-constrained weighted collaborative-competitive representation for classification

      Author: Gou, Jianping; Xiong, Xiangshuo; Wu, Hongwei; Du, Lan; Zeng, Shaoning; Yuan, Yunhao; Ou, Weihua

      Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 363-376. DOI: 10.1007/s13042-021-01461-y

    • 3、Distance metric learning with local multiple kernel embedding

      Author: Zhang, Qingshuo; Tsang, Eric C. C.; He, Qiang; Hu, Meng

      Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 1, pp. 79-92. DOI: 10.1007/s13042-021-01487-2

    • 4、Micro-extended belief rule-based system with activation factor and parameter optimization for industrial cost prediction

      Author: Wang, Suhui; Ye, Fei-Fei; Yang, Long-Hao; Liu, Jun; Wang, Hui; Martinez, Luis

      Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 1, pp. 63-78. DOI: 10.1007/s13042-021-01485-4

    • 5、Small target deep convolution recognition algorithm based on improved YOLOv4

      Author: Li, Fudong; Gao, Dongyang; Yang, Yuequan; Zhu, Junwu

      Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 387-394. DOI: 10.1007/s13042-021-01496-1

    • 6、A hybrid-attention semantic segmentation network for remote sensing interpretation in land-use surveillance

      Author: Lv, Ning; Zhang, Zenghui; Li, Cong; Deng, Jiaxuan; Su, Tao; Chen, Chen; Zhou, Yang

      Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 395-406. DOI: 10.1007/s13042-022-01517-7

    • 7、Global attention network for collaborative saliency detection

      Author: Li, Ce; Xuan, Shuxing; Liu, Fenghua; Chang, Enbing; Wu, Hailei

      Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 2, pp. 407-417. DOI: 10.1007/s13042-022-01531-9

    • 8、An iterative recommendation model of supporting personalized learning based on schematic patterns mining from schema-enhanced contexts of problem-solving

      Author: Guo, Lankun; Jia, Zhenhua; Ma, Guozhi; Li, Jinhai

      Journal: INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS. 2023; Vol. 14, Issue 1, pp. 93-115. DOI: 10.1007/s13042-022-01525-7

    投稿常見問題

    通訊方式:TIERGARTENSTRASSE 17, HEIDELBERG, GERMANY, D-69121。

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