Chemometrics and Intelligent Laboratory Systems

Chemometrics and Intelligent Laboratory Systems
期刊缩写:
CHEMOMETR INTELL LAB
影响因子:
3.7
ISSN:
print: 0169-7439
研究领域:
工程技术-分析化学
创刊年份:
1986年
h-index:
109
自引率:
7.70%
Gold OA文章占比:
19.85%
原创研究文献占比:
98.31%
SCI收录类型:
Science Citation Index Expanded (SCIE) || Scopus (CiteScore)
期刊介绍英文:
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.
CiteScore:
CiteScoreSJRSNIPCiteScore排名
7.50.6671.184
学科
排名
百分位
大类:Chemistry
小类:Spectroscopy
13 / 76
83%
大类:Chemistry
小类:Analytical Chemistry
33 / 156
79%
大类:Computer Science
小类:Computer Science Applications
178 / 817
78%
大类:Computer Science
小类:Software
99 / 407
75%
大类:Chemical Engineering
小类:Process Chemistry and Technology
23 / 73
69%
发文信息
中科院SCI期刊分区
大类 小类 TOP期刊 综述期刊
2区 化学
3区 自动化与控制系统 AUTOMATION & CONTROL SYSTEMS
3区 分析化学 CHEMISTRY, ANALYTICAL
3区 计算机:人工智能 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
3区 仪器仪表 INSTRUMENTS & INSTRUMENTATION
3区 数学跨学科应用 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
3区 统计学与概率论 STATISTICS & PROBABILITY
WOS期刊分区
学科分类
Q2AUTOMATION & CONTROL SYSTEMS
Q2CHEMISTRY, ANALYTICAL
Q2COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Q1INSTRUMENTS & INSTRUMENTATION
Q1MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Q1STATISTICS & PROBABILITY
历年影响因子
2015年2.2170
2016年2.3030
2017年2.7010
2018年2.7860
2019年2.8950
2020年3.4910
2021年4.1750
2022年3.9000
2023年3.7000
历年发表
2012年170
2013年150
2014年198
2015年246
2016年230
2017年207
2018年186
2019年167
2020年222
2021年196
2022年169
投稿信息
出版周期:
Bimonthly
出版语言:
English
出版国家(地区):
NETHERLANDS
接受率:
21%
初审时长:
5 weeks
审稿时长:
50 days
发表时长:
2 weeks
论文处理费:
$3680
出版商:
Elsevier
编辑部地址:
ELSEVIER SCIENCE BV, PO BOX 211, AMSTERDAM, NETHERLANDS, 1000 AE

Chemometrics and Intelligent Laboratory Systems - 最新文献

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Prediction of potential antitumor components in Ganoderma lucidum: A combined approach using machine learning and molecular docking

Pub Date : 2024-11-08 DOI: 10.1016/j.chemolab.2024.105271 Qi Yang , Lihao Yao , Fang Jia , Guiyuan Pang , Meiyu Huang , Chengxiang Liu , Hua Luo , Lili Fan

Spectra data calibration based on deep residual modeling of independent component regression

Pub Date : 2024-11-05 DOI: 10.1016/j.chemolab.2024.105270 Junhua Zheng , Zeyu Yang , Zhiqiang Ge
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