A simple Mathematical Fuzzy Model of Brain Emotional Learning to Predict Kp Geomagnetic Index
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2014, Vol 2, Issue 2
Abstract
In this paper, we propose fuzzy mathematical model of brain limbic system (LS) which is responsible for emotional stimuli. Here the proposed model is utilized to predict the chaotic activity of the earth’s magnetosphere. Numerical results show that the correlation of the results obtained from the proposed fuzzy model is higher than non-fuzzy models. Hence, the proposed model can be applied in real time chaotic time series prediction.
Authors and Affiliations
Ehsan Lotfi *| Department of Computer Engineering, Torbat-e-Jam Branch, Islamic Azad University, Torbat-e-Jam, Iran, A. Keshavarz| Department of Psychology, Torbat-e-Jam Branch, Islamic Azad University, Torbat-e-Jam, Iran
Keywords
Related Articles
- EP ID EP749
- DOI -
- Views 545
- Downloads 41
Improving Intrusion Detection using Genetic Linear Discriminant Analysis
The objective of this research is to propose an efficient soft computing approach with high detection rates and low false alarms while maintaining low cost and shorter detection time for intrusion detection. Our results...
New Approach in E-mail Based Text Steganography
In this study combination of lossless compression techniques and Vigenere cipher was used in text steganography that makes use of email addresses to be the keys to reconstruct the secret message which has been embedded i...
An Efficient Approach for Ground Echoes Suppression Based on Textural Features and SVM
The use of the Support Vector Machine (SVM) technique for the clutter identification in the context of meteorological data is presented. The clutter is due to ground echoes and anomalous propagation. The SVM is combined...
Intrusion Detection Forecasting Using Time Series for Improving Cyber Defence
The strength of time series modeling is generally not used in almost all current intrusion detection and prevention systems. By having time series models, system administrators will be able to better plan resource alloca...
Structure-Texture Decomposition of RGB-D Images
In this paper, we study the problem of separating texture from structure in RGB-D images. Our structure preserving image smoothing operator is based on the region covariance smoothing (RCS) method in [16] that we present...