Complexity

Complex Methods Applied to Data Analysis, Processing, and Visualization


Publishing date
01 May 2019
Status
Published
Submission deadline
28 Dec 2018

1University of Alicante, Alicante, Spain

2University of Westminster, London, UK

3Griffith University, Brisbane, Australia


Complex Methods Applied to Data Analysis, Processing, and Visualization

Description

The amount of data available every day is not only enormous but growing at an exponential rate. Over the last ten years there has been an increasing interest in using complex methods to analyse and visualize massive data generated from very different sources and with many different features: social networks, surveillance systems, smart cities, medical diagnosis, business, cyberphysical systems, or media digital data. This special issue is designed to serve researchers and developers to publish original, innovative, and state-of-the-art machine complex methods algorithms and architectures to analyse and visualize large amounts of data and solve a range of problems.

We are particularly interested in candidates who have conducted research in the theoretical or practical aspects of data processing: algorithms using complex methods (including chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory), statistical learning methods applied to one or more domains: software engineering, media digital data, bioinformatics, health care, imaging and video, social networks, natural language processing, and others.

Potential topics include but are not limited to the following:

  • Chaos steganography algorithm for multimedia data mining
  • Neural networks in visual surveillance
  • Artificial neural network model for education data learning
  • Location big data mining with cellular automata
  • Intelligent web mining technique using genetic algorithms
  • Multimedia data (signal, 2D/3D image, and video) analysis in medicine, science, and engineering using complex methods algorithms
  • An optimization of semantic image analysis using genetic algorithm approach: human activity recognition, face/facial expression recognition, scene understanding, object detection and tracking, and saliency detection
  • Intelligent text mining model using deep neural network
  • Sentiment analysis and opinion mining using convolutional neural network

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 9316123
  • - Editorial

Complex Methods Applied to Data Analysis, Processing, and Visualisation

Jose Garcia-Rodriguez | Anastasia Angelopoulou | ... | Andrew Lewis
  • Special Issue
  • - Volume 2019
  • - Article ID 6271017
  • - Research Article

Hybrid Unsupervised Exploratory Plots: A Case Study of Analysing Foreign Direct Investment

Álvaro Herrero | Alfredo Jiménez | Secil Bayraktar
  • Special Issue
  • - Volume 2019
  • - Article ID 1306039
  • - Review Article

A Systematic Review of Deep Learning Approaches to Educational Data Mining

Antonio Hernández-Blanco | Boris Herrera-Flores | ... | Borja Navarro-Colorado
  • Special Issue
  • - Volume 2019
  • - Article ID 4057849
  • - Research Article

MI-Based Robust Waveform Design in Radar and Jammer Games

Bin Wang | Xu Chen | ... | Xin Song
  • Special Issue
  • - Volume 2019
  • - Article ID 5245373
  • - Research Article

Activity Feature Solving Based on TF-IDF for Activity Recognition in Smart Homes

Jinghuan Guo | Yong Mu | ... | Jingxuan Gu
  • Special Issue
  • - Volume 2019
  • - Article ID 1403829
  • - Research Article

Improved Permutation Entropy for Measuring Complexity of Time Series under Noisy Condition

Zhe Chen | Yaan Li | ... | Jing Yu
  • Special Issue
  • - Volume 2019
  • - Article ID 5937274
  • - Research Article

Two-Phase Incremental Kernel PCA for Learning Massive or Online Datasets

Feng Zhao | Islem Rekik | ... | Dinggang Shen
  • Special Issue
  • - Volume 2019
  • - Article ID 6876173
  • - Research Article

A Novel Semi-Supervised Learning Method Based on Fast Search and Density Peaks

Fei Gao | Teng Huang | ... | Huiyu Zhou
  • Special Issue
  • - Volume 2019
  • - Article ID 2095063
  • - Research Article

LMC and SDL Complexity Measures: A Tool to Explore Time Series

José Roberto C. Piqueira | Sérgio Henrique Vannucchi Leme de Mattos
Complexity
Publishing Collaboration
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 Journal metrics
Acceptance rate43%
Submission to final decision64 days
Acceptance to publication35 days
CiteScore3.200
Impact Factor2.462
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