Chemometrics And Intelligent Laboratory Systems

杂志介绍

Chemometrics And Intelligent Laboratory Systems杂志介绍

《Chemometrics And Intelligent Laboratory Systems》是一本以English为主的未开放获取国际优秀期刊，中文名称化学计量学和智能实验室系统，本刊主要出版、报道化学-AUTOMATION & CONTROL SYSTEMS领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为3.7，最新CiteScore 指数为7.5。

本刊近期中国学者发表的论文主要有：

• 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

英文介绍

Chemometrics And Intelligent Laboratory Systems杂志英文介绍

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.