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Chemometrics And Intelligent Laboratory SystemsSCIE

國際簡稱：CHEMOMETR INTELL LAB 參考譯名：化學(xué)計量學(xué)和智能實驗室系統(tǒng)

中科院分區(qū)
2區(qū)
CiteScore分區(qū)
Q1
JCR分區(qū)
Q1

基本信息：: ISSN：0169-7439; E-ISSN：1873-3239; 是否OA：未開放; 是否預(yù)警：否; TOP期刊：是

出版信息：: 出版地區(qū)：NETHERLANDS; 出版商：Elsevier; 出版語言：English; 出版周期：Bimonthly; 出版年份：1986; 研究方向：工程技術(shù)-分析化學(xué)

評價信息：: 影響因子：3.7; H-index：109; CiteScore指數(shù)：7.5; SJR指數(shù)：0.667; SNIP指數(shù)：1.184

發(fā)文數(shù)據(jù)：: Gold OA文章占比：19.85%; 研究類文章占比：99.46%; 年發(fā)文量：186; 自引率：0.0769...; 開源占比：0.0894; 出版撤稿占比：0; 出版國人文章占比：0.28; OA被引用占比：0.0114...

投稿咨詢加急見刊

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Chemometrics And Intelligent Laboratory Systems期刊介紹

Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines.

Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data.

The journal deals with the following topics:

1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.)

2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered.

3) Development of new software that provides novel tools or truly advances the use of chemometrical methods.

4) Well characterized data sets to test performance for the new methods and software.

The journal complies with International Committee of Medical Journal Editors' Uniform requirements for manuscripts.

期刊簡介Chemometrics And Intelligent Laboratory Systems期刊介紹

《Chemometrics And Intelligent Laboratory Systems》自1986出版以來，是一本化學(xué)優(yōu)秀雜志。致力于發(fā)表原創(chuàng)科學(xué)研究結(jié)果，并為化學(xué)各個領(lǐng)域的原創(chuàng)研究提供一個展示平臺，以促進(jìn)化學(xué)領(lǐng)域的的進(jìn)步。該刊鼓勵先進(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€重要領(lǐng)域的所有重要發(fā)展。該期刊特色在于及時報道化學(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)：

預(yù)計審稿時間：約3.0個月約11.1周
國際TOP期刊
化學(xué)
AUTOMATION & CONTROL SYSTEMS
SCIE
中科院2區(qū)
非預(yù)警

Cite Score數(shù)據(jù)（2024年最新版）Chemometrics And Intelligent Laboratory Systems Cite Score數(shù)據(jù)

CiteScore：7.5
SJR：0.667
SNIP：1.184

學(xué)科類別	分區(qū)	排名	百分位
大類：Chemistry 小類：Spectroscopy	Q1	13 / 76	83%
大類：Chemistry 小類：Analytical Chemistry	Q1	33 / 156	79%
大類：Chemistry 小類：Computer Science Applications	Q1	178 / 817	78%
大類：Chemistry 小類：Software	Q1	99 / 407	75%
大類：Chemistry 小類：Process Chemistry and Technology	Q2	23 / 73	69%

CiteScore 是由Elsevier(愛思唯爾)推出的另一種評價期刊影響力的文獻(xiàn)計量指標(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、更客觀地評價期刊影響力的方法，而不僅僅是通過影響因子(IF)這一單一指標(biāo)來評價。

歷年Cite Score趨勢圖

中科院SCI分區(qū)Chemometrics And Intelligent Laboratory Systems 中科院分區(qū)

中科院 2023年12月升級版 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)
化學(xué)	2區(qū)	AUTOMATION & CONTROL SYSTEMS 自動化與控制系統(tǒng) CHEMISTRY, ANALYTICAL 分析化學(xué) COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計算機(jī)：人工智能 INSTRUMENTS & INSTRUMENTATION 儀器儀表 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS 數(shù)學(xué)跨學(xué)科應(yīng)用 STATISTICS & PROBABILITY 統(tǒng)計學(xué)與概率論	3區(qū) 3區(qū) 3區(qū) 3區(qū) 3區(qū) 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)計量學(xué)方法對國際、國內(nèi)學(xué)術(shù)期刊依據(jù)影響力進(jìn)行等級劃分的期刊評價標(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價國際學(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)四個層次，類似于“優(yōu)、良、及格”等。最開始，這個分區(qū)只是為了方便圖書管理及圖書情報領(lǐng)域的研究和期刊評估。之后中科院分區(qū)逐步發(fā)展成為了一種評價學(xué)術(shù)期刊質(zhì)量的重要工具。

歷年中科院分區(qū)趨勢圖

JCR分區(qū)Chemometrics And Intelligent Laboratory Systems 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：AUTOMATION & CONTROL SYSTEMS	SCIE	Q2	26 / 84	69.6%
學(xué)科：CHEMISTRY, ANALYTICAL	SCIE	Q2	28 / 106	74.1%
學(xué)科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q2	66 / 197	66.8%
學(xué)科：INSTRUMENTS & INSTRUMENTATION	SCIE	Q1	17 / 76	78.3%
學(xué)科：MATHEMATICS, INTERDISCIPLINARY APPLICATIONS	SCIE	Q1	13 / 135	90.7%
學(xué)科：STATISTICS & PROBABILITY	SCIE	Q1	10 / 168	94.3%

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：AUTOMATION & CONTROL SYSTEMS	SCIE	Q1	15 / 84	82.74%
學(xué)科：CHEMISTRY, ANALYTICAL	SCIE	Q1	18 / 106	83.49%
學(xué)科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q1	45 / 198	77.53%
學(xué)科：INSTRUMENTS & INSTRUMENTATION	SCIE	Q1	11 / 76	86.18%
學(xué)科：MATHEMATICS, INTERDISCIPLINARY APPLICATIONS	SCIE	Q1	23 / 135	83.33%
學(xué)科：STATISTICS & PROBABILITY	SCIE	Q1	14 / 168	91.96%

JCR分區(qū)的優(yōu)勢在于它可以幫助讀者對學(xué)術(shù)文獻(xiàn)質(zhì)量進(jìn)行評估。不同學(xué)科的文章引用量可能存在較大的差異，此時單獨(dú)依靠影響因子(IF)評價期刊的質(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。

歷年影響因子趨勢圖

發(fā)文數(shù)據(jù)

2023-2024 年國家/地區(qū)發(fā)文量統(tǒng)計

國家/地區(qū)數(shù)量
CHINA MAINLAND205
Spain54
USA49
Iran36
France30
Italy26
Canada25
Brazil21
England18
India18

本刊中國學(xué)者近年發(fā)表論文

1、Simultaneous measurement of chemical oxygen demand and turbidity in water based on broad optical spectra using backpropagation neural network
Author: Zhou, Chao; Zhang, Jiang

Journal: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. 2023; Vol. 237, Issue , pp. -. DOI: 10.1016/j.chemolab.2023.104830
2、A multi-task learning approach for chemical process abnormity locations and fault classifications
Author: Zhao, Wenlei; Li, Jince; Li, Hongguang

Journal: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. 2023; Vol. 233, Issue , pp. -. DOI: 10.1016/j.chemolab.2022.104719
3、ConInceDeep: A novel deep learning method for component identification of mixture based on Raman spectroscopy
Author: Zhao, Ziyan; Liu, Zhenfang; Ji, Mingqiang; Zhao, Xin; Zhu, Qibing; Huang, Min

Journal: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. 2023; Vol. 234, Issue , pp. -. DOI: 10.1016/j.chemolab.2023.104757
4、GAMB-GNN: Graph Neural Networks learning from gene structure relations and Markov Blanket ranking for cancer classification in microarray data
Author: Zhang, Shoujia; Xie, Weidong; Li, Wei; Wang, Linjie; Feng, Chaolu

Journal: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. 2023; Vol. 232, Issue , pp. -. DOI: 10.1016/j.chemolab.2022.104713
5、Simple dilated convolutional neural network for quantitative modeling based on near infrared spectroscopy techniques
Author: Gan, Feng; Luo, Jianfei

Journal: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. 2023; Vol. 232, Issue , pp. -. DOI: 10.1016/j.chemolab.2022.104710
6、Design the arbitrary order calculus operator by a simulated hyperbolic function for analytical applications
Author: Yao, Zhixiang; Yao, Ju; Su, Hui

Journal: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. 2023; Vol. 234, Issue , pp. -. DOI: 10.1016/j.chemolab.2023.104754
7、Application of iterative distance correlation and PLS for wavelength interval selection in near infrared spectroscopy
Author: Huang, Xin; Xia, Li

Journal: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. 2023; Vol. 234, Issue , pp. -. DOI: 10.1016/j.chemolab.2023.104756
8、Nonlocal, local and global preserving stacked autoencoder based fault detection method for nonlinear process monitoring
Author: Yang, Jingchao; Wang, Li

Journal: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. 2023; Vol. 235, Issue , pp. -. DOI: 10.1016/j.chemolab.2023.104758