Adaptive brain emotional decayed learning for online prediction of geomagnetic activity indices
نویسندگان
چکیده
In this paper we propose adaptive brain-inspired emotional decayed learning to predict Kp, AE and Dst indices that characterize the chaotic activity of the earth's magnetosphere by their extreme lows and highs. In mammalian brain, the limbic system processes emotional stimulus and consists of two main components: Amygdala and Orbitofrontal Cortex (OFC). Here, we propose a learning algorithm for the neural basis computational model of Amygdala–OFC in a supervised manner and consider a decay rate in Amygdala learning rule. This added decay rate has in fact a neurobiological basis and yields to better learning and adaptive decision making as illustrated here. In the experimental studies, various comparisons are made between the proposed method named ADBEL, Multilayer Perceptron (MLP), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Locally Linear Neuro-Fuzzy (LLNF). The main features of the presented predictor are the higher accuracy at all points especially at critical points, lower computational complexity and adaptive training. Hence, the presented model can be utilized in adaptive online prediction problems. & 2013 Elsevier B.V. All rights reserved.
منابع مشابه
A Brain Emotional Learning-based Prediction Model A Brain Emotional Learning-based Prediction Model For the Prediction of Geomagnetic Storms
This paper introduces a new type of brain emotional learning inspired models (BELIMs). The suggested model is utilized as a suitable model for predicting geomagnetic storms. The model is known as BELPM which is an acronym for Brain Emotional Learning-based Prediction Model. The structure of the suggested model consists of four main parts and mimics the corresponding regions of the neural struct...
متن کاملPredicting Geomagnetic Activity Index by Brain Emotional Learning
The Emotional Learning Algorithm has been introduced to show the effect of emotions as well known stimuli in the quick and almost satisficing decision making in human. The remarkable properties of emotional learning, low computational complexity and fast training, and its simplicity in multi objective problems has made it a powerful methodology in real time control and decision systems, where t...
متن کاملA New Computational Intelligence Model for Long-Term Prediction of Solar and Geomagnetic Activity
This paper briefly describes how the neural structure of fear conditioning has inspired to develop a computational intelligence model that is referred to as the brain emotional learning-inspired model (BELIM). The model is applied to predict long step ahead of solar activity and geomagnetic storms.
متن کاملOnline Voltage Stability Monitoring and Prediction by Using Support Vector Machine Considering Overcurrent Protection for Transmission Lines
In this paper, a novel method is proposed to monitor the power system voltage stability using Support Vector Machine (SVM) by implementing real-time data received from the Wide Area Measurement System (WAMS). In this study, the effects of the protection schemes on the voltage magnitude of the buses are considered while they have not been investigated in previous researches. Considering overcurr...
متن کاملIntelligent Auto pilot Design for a Nonlinear Model of an Autonomous Helicopter by Adaptive Emotional Approach
There is a growing interest in the modeling and control of model helicopters using nonlinear dynamic models and nonlinear control. Application of a new intelligent control approach called Brain Emotional Learning Based Intelligent Controller (BELBIC) to design autopilot for an autonomous helicopter is addressed in this paper. This controller is applied to a nonlinear model of a helicopter. This...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Neurocomputing
دوره 126 شماره
صفحات -
تاریخ انتشار 2014