Information Sciences（ISCI ）的VOLUME 591论文列表

卷期号： Volume 591

发布时间： April 2022

卷期年份： 2022

卷期官网： https://www.sciencedirect.com/journal/information-sciences/vol/591/suppl/C

Editorial Board

Shadowed-set-based three-way clustering methods: An investigation of new optimization-based principles

ASMCNN: An efficient brain extraction using active shape model and convolutional neural networks

Optimization problems subject to addition-Łukasiewicz-product fuzzy relational inequalities with applications in urban sewage treatment systems

Grained matrix and complementary matrix: Novel methods for computing information descriptions in covering approximation spaces

Ship-unloading scheduling optimization with differential evolution

On exploring data lakes by finding compact, isolated clusters

Dynamic graph computing: A method of finding companion vehicles from traffic streaming data

Semi-supervised multi-view graph convolutional networks with application to webpage classification

Bayesian optimization based dynamic ensemble for time series forecasting

An integrated surrogate model constructing method: Annealing combinable Gaussian process

MWFP-outlier: Maximal weighted frequent-pattern-based approach for detecting outliers from uncertain weighted data streams

Adaptively sharing multi-levels of distributed representations in multi-task learning

Semantic guide for semi-supervised few-shot multi-label node classification

An orthogonal classifier for improving the adversarial robustness of neural networks

Matrix representation of the conditional entropy for incremental feature selection on multi-source data

Knowledge extraction and retention based continual learning by using convolutional autoencoder-based learning classifier system

Hybrid attention network based on progressive embedding scale-context for crowd counting

MEACCP: A membrane evolutionary algorithm for capacitated clustering problem

Auto-CASH: A meta-learning embedding approach for autonomous classification algorithm selection

Actor-critic continuous state reinforcement learning for wind-turbine control robust optimization

Data-feature-driven nonlinear process monitoring based on joint deep learning models with dual-scale

Hypergraph regularized semi-supervised support vector machine

Withdrawal notice to: “Granular computing based machine learning in the era of big data” [Inf. Sci. 591 (2022) 422–423]

WITHDRAWN: Granular computing based machine learning in the era of big data