Special Issue Information Special Issue Call for Paper Other Special Issues on this journal Closed Special Issues
Data Stream Mining and Soft Computing Applications

Data Stream Mining and Soft Computing Applications

Journal
Impact Score 9.24

OFFICIAL WEBSITE

Special Issue Information

Submission Deadline: 31-01-2017
Journal Impact Score: 9.24
Journal Name: Applied Soft Computing
Publisher: Applied Soft Computing

Special Issue Call for Papers

In current industrial systems, the necessity of data stream mining and learning from data streams is increasingly becoming more prevalent and urgent, due to speed, volume and on-line nature of the data generated by such systems. While conventional batch and off-line training approaches provide a possible solution, such approaches are often too time and memory intensive, and cannot process the data at the high enough rate that is often desired. This is true even when batch and off-line approaches are applied to sliding windows or onto streaming samples gathered from reservoir computing techniques.

An important aspect in data stream mining is that the data analysis system, the learner, has no control over the order of samples that arrive over time --- they simply arrive in the same order they are acquired and recorded. Also, the learning algorithms usually have to be fast enough in order to cope with real-time and on-line demands. This usually requires a single-pass learning procedure, restricting the algorithm to update models and statistical information in a sample-wise manner, without using any prior data. In literature, this is also termed as incremental or sequential learning and plays a key role in data stream mining frameworks and environments. Practical real-world applications of evolving models include – and are not limited to - on-line quality control of production items, supervision and failure analysis of dynamically changing machine states, decision support systems in medicine, engine control, prediction and quantification in very dynamic production processes, welding processes, user profiling in various applications, forecasting, and internet, among many others.

This special issue intends to draw a picture of the recent advances in data stream mining techniques including all incremental machine learning concepts and evolving soft computing modeling strategies for addressing these important problems discussed above. Finally, all emerging and grand-challenge problems, topics such as interpretability aspects in evolving models, and mimicking intelligent brain – even if at a limited scale - are of particular interest to this special issue. Computational aspects such as real-time capability of the learning methods play central roles within all these issues.

Topics

Original contributions are solicited from, but are not limited, the following topics of interest:

Advanced Aspects for Improved Stability, Performance and Usability (but not necessarily restr. to):
New Algorithms, Concepts in Data Stream Mining with Soft Computing Techniques (for supervised regression, classification and unsupervised learning)
New Algorithms, Concepts in Mining with Machine Learning Concepts(for supervised regression, classification and unsupervised learning)
Concepts to address drifts and shifts in Data Streams
On-line single-pass active learning from Data Streams
Semi-supervised learning from Data Streams
Dynamic dimension reduction and feature selection in Streams
Reliability in model predictions and parameters
Stability, process-safety and computational related aspects
Concepts to address linguistic interpretability
Concepts to address visual interpretability (model development over time)
Online tuning via human-machine interaction
Complexity reduction and interpretability issues in evolving models
Incremental and evolving methods for multi-label classification problems
On-line ensembling and fusioning methods for improved model output robustness
Concepts to address dynamic splitting of model components on the fly
Real-World Applications of evolving soft computing techniques such as (but not necessarily restricted to):
Data stream modelling and identification
Online fault detection and decision support systems
Online media stream classification
Process control and condition monitoring
Modeling in high throughput production systems
Web applications
Adaptive chemometric models in dynamic chemical processes
Online time series analysis and stock market forecasting
Robotics, Intelligent Transport and Advanced Manufacturing
Adaptive Evolving Controller Design
User Activities Recognition
Cloud Computing
Multiple Sensor Networks
Big Data

Closed Special Issues

Publisher
Journal Details
Closing date
G2R Score
Predictive Intelligence: Humans Meet Artificial Intelligence

Predictive Intelligence: Humans Meet Artificial Intelligence

Applied Soft Computing
Closing date: 31-05-2021 G2R Score: 9.24
Virtual  Recent Advances in Discrete Swarm Intelligence Algorithms for Solving Engineering Problems

Virtual Recent Advances in Discrete Swarm Intelligence Algorithms for Solving Engineering Problems

Applied Soft Computing
Closing date: 31-12-2020 G2R Score: 9.24
Expert Decision Making for Data Analytics with Applications

Expert Decision Making for Data Analytics with Applications

Applied Soft Computing
Closing date: 31-12-2020 G2R Score: 9.24
Soft Computing for Intelligent Edge Computing

Soft Computing for Intelligent Edge Computing

Applied Soft Computing
Closing date: 15-12-2020 G2R Score: 9.24
Intelligent solutions for efficient logistics and sustainable transportation

Intelligent solutions for efficient logistics and sustainable transportation

Applied Soft Computing
Closing date: 15-11-2020 G2R Score: 9.24
New Techniques in Adversarial Machine Learning

New Techniques in Adversarial Machine Learning

Applied Soft Computing
Closing date: 20-10-2020 G2R Score: 9.24
Randomization-Based Deep and Shallow Learning Algorithms

Randomization-Based Deep and Shallow Learning Algorithms

Applied Soft Computing
Closing date: 30-09-2020 G2R Score: 9.24
Applying Machine Learning for Combating Fake News and Internet/Media Content Manipulation

Applying Machine Learning for Combating Fake News and Internet/Media Content Manipulation

Applied Soft Computing
Closing date: 25-09-2020 G2R Score: 9.24
Special Issue on Expert Decision Making for Data Analytics with Applications

Special Issue on Expert Decision Making for Data Analytics with Applications

Applied Soft Computing
Closing date: 31-07-2020 G2R Score: 9.24
Expert Decision Making for Data Analytics with Applications

Expert Decision Making for Data Analytics with Applications

Applied Soft Computing
Closing date: 31-07-2020 G2R Score: 9.24
Soft Computing for Recommender Systems and Sentiment Analysis

Soft Computing for Recommender Systems and Sentiment Analysis

Applied Soft Computing
Closing date: 30-06-2020 G2R Score: 9.24
Application of Computational Intelligence models in Transformative Computing technologies

Application of Computational Intelligence models in Transformative Computing technologies

Applied Soft Computing
Closing date: 16-01-2020 G2R Score: 9.24
Data-driven Decision Making - Theory, Methods, and Applications

Data-driven Decision Making - Theory, Methods, and Applications

Applied Soft Computing
Closing date: 15-08-2019 G2R Score: 9.24
Bio-Inspired Optimization Techniques for BioMedical Data Analysis: Methods and Applications

Bio-Inspired Optimization Techniques for BioMedical Data Analysis: Methods and Applications

Applied Soft Computing
Closing date: 01-11-2018 G2R Score: 9.24
Applying Machine Learning Systems for IoT Services in Industrial Informatics

Applying Machine Learning Systems for IoT Services in Industrial Informatics

Applied Soft Computing
Closing date: 20-11-2017 G2R Score: 9.24
Evolutionary Computer Vision, Image Processing and Pattern Recognition

Evolutionary Computer Vision, Image Processing and Pattern Recognition

Applied Soft Computing
Closing date: 30-04-2017 G2R Score: 9.24
Data Stream Mining and Soft Computing Applications

Data Stream Mining and Soft Computing Applications

Applied Soft Computing
Closing date: 31-01-2017 G2R Score: 9.24
Intelligent Decision Support Systems based on Soft Computing

Intelligent Decision Support Systems based on Soft Computing

Applied Soft Computing
Closing date: 25-01-2017 G2R Score: 9.24
Fuzzy Systems for Biomedical Science in Healthcare

Fuzzy Systems for Biomedical Science in Healthcare

Applied Soft Computing
Closing date: 01-01-1970 G2R Score: 9.24