Computational Intelligence and Neuroscience

Applications of Computational Intelligence in Time Series


Publishing date
27 Jan 2017
Status
Published
Submission deadline
09 Sep 2016

1Pablo de Olavide University, Seville, Spain

2University of Seville, Seville, Spain

3University of Seville, Seville, Spain


Applications of Computational Intelligence in Time Series

Description

The prediction of the future has fascinated the human being since its early existence. Actually, many of these efforts can be noticed in everyday events such as energy management, telecommunications, pollution, bioinformatics, seismology, and, obviously, neuroscience. Accurate predictions are essential in economic activities as remarkable forecasting errors in certain areas may involve large loss of money.

Given this situation, the successful analysis of temporal data has been a challenging task for many researchers during the last decades and, indeed, it is difficult to figure out any scientific branch with no time-dependent variables.

Computational intelligence is known for including powerful techniques like artificial neural networks, fuzzy systems, evolutionary computation, learning theory, or probabilistic methods. Thus, this special issue is focused to the application of such techniques to time series.

The goal of this special issue is to share recent advances in time series analysis and to provide an interesting opportunity to present and discuss the latest practical advanced in real-world applications.

In this sense, original works in the field of both classification and forecasting are welcome. Results with application to neuroscience are particularly encouraged.

Potential topics include, but are not limited to:

  • Neural models in time series analysis
  • Deep learning in time series analysis
  • Soft computing in time series analysis
  • Bioinspired models in time series analysis
  • Fuzzy systems in time series analysis
  • Probabilistic methods in time series analysis
  • All of the above-mentioned techniques in the big time series data context

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 9361749
  • - Editorial

Applications of Computational Intelligence in Time Series

Francisco Martínez-Álvarez | Alicia Troncoso | ... | José C. Riquelme
  • Special Issue
  • - Volume 2017
  • - Article ID 9580815
  • - Research Article

An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment

Chien-Feng Huang | Hsu-Chih Li
  • Special Issue
  • - Volume 2017
  • - Article ID 7436948
  • - Research Article

Statistical Modeling and Prediction for Tourism Economy Using Dendritic Neural Network

Ying Yu | Yirui Wang | ... | Zheng Tang
  • Special Issue
  • - Volume 2016
  • - Article ID 9328062
  • - Research Article

Main Trend Extraction Based on Irregular Sampling Estimation and Its Application in Storage Volume of Internet Data Center

Beibei Miao | Chao Dou | Xuebo Jin
  • Special Issue
  • - Volume 2016
  • - Article ID 3045254
  • - Research Article

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

Montri Inthachot | Veera Boonjing | Sarun Intakosum
  • Special Issue
  • - Volume 2016
  • - Article ID 5329870
  • - Research Article

A Forecasting Model for Feed Grain Demand Based on Combined Dynamic Model

Tiejun Yang | Na Yang | Chunhua Zhu
  • Special Issue
  • - Volume 2016
  • - Article ID 6459873
  • - Research Article

A Long-Term Prediction Model of Beijing Haze Episodes Using Time Series Analysis

Xiaoping Yang | Zhongxia Zhang | ... | Li Yu
Computational Intelligence and Neuroscience
 Journal metrics
Acceptance rate28%
Submission to final decision79 days
Acceptance to publication37 days
CiteScore4.700
Impact Factor2.284
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