雜志介紹

Chemometrics And Intelligent Laboratory Systems雜志介紹

《Chemometrics And Intelligent Laboratory Systems》是一本以English為主的未開(kāi)放獲取國(guó)際優(yōu)秀期刊，中文名稱化學(xué)計(jì)量學(xué)和智能實(shí)驗(yàn)室系統(tǒng)，本刊主要出版、報(bào)道化學(xué)-AUTOMATION & CONTROL SYSTEMS領(lǐng)域的研究動(dòng)態(tài)以及在該領(lǐng)域取得的各方面的經(jīng)驗(yàn)和科研成果，介紹該領(lǐng)域有關(guān)本專業(yè)的最新進(jìn)展，探討行業(yè)發(fā)展的思路和方法，以促進(jìn)學(xué)術(shù)信息交流，提高行業(yè)發(fā)展。該刊已被國(guó)際權(quán)威數(shù)據(jù)庫(kù)SCIE收錄，為該領(lǐng)域相關(guān)學(xué)科的發(fā)展起到了良好的推動(dòng)作用，也得到了本專業(yè)人員的廣泛認(rèn)可。該刊最新影響因子為3.7，最新CiteScore 指數(shù)為7.5。

本刊近期中國(guó)學(xué)者發(fā)表的論文主要有：

• Simultaneous measurement of chemical oxygen demand and turbidity in water based on broad optical spectra using backpropagation neural network

  Author: Zhou, Chao; Zhang, Jiang

• A multi-task learning approach for chemical process abnormity locations and fault classifications

  Author: Zhao, Wenlei; Li, Jince; Li, Hongguang

• 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

• 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

英文介紹

Chemometrics And Intelligent Laboratory Systems雜志英文介紹

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.