雜志介紹

International Journal For Uncertainty Quantification雜志介紹

《International Journal For Uncertainty Quantification》是一本以English為主的未開放獲取國(guó)際優(yōu)秀期刊，中文名稱不確定性量化國(guó)際期刊，本刊主要出版、報(bào)道工程技術(shù)-ENGINEERING, MULTIDISCIPLINARY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1.5，最新CiteScore 指數(shù)為3.6。

英文介紹

International Journal For Uncertainty Quantification雜志英文介紹

The International Journal for Uncertainty Quantification disseminates information of permanent interest in the areas of analysis, modeling, design and control of complex systems in the presence of uncertainty. The journal seeks to emphasize methods that cross stochastic analysis, statistical modeling and scientific computing. Systems of interest are governed by differential equations possibly with multiscale features. Topics of particular interest include representation of uncertainty, propagation of uncertainty across scales, resolving the curse of dimensionality, long-time integration for stochastic PDEs, data-driven approaches for constructing stochastic models, validation, verification and uncertainty quantification for predictive computational science, and visualization of uncertainty in high-dimensional spaces. Bayesian computation and machine learning techniques are also of interest for example in the context of stochastic multiscale systems, for model selection/classification, and decision making. Reports addressing the dynamic coupling of modern experiments and modeling approaches towards predictive science are particularly encouraged. Applications of uncertainty quantification in all areas of physical and biological sciences are appropriate.