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The Modified Differential Evolution and the RBF (MDE-RBF) Neural Network for Time Series Prediction
We develop a modified differential evolution algorithm that produces radial basis function neural network controllers for chaotic systems. This method requires few controlling variables. We examineExpand
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A hybrid learning algorithm for evolving Flexible Beta Basis Function Neural Tree Model
Abstract In this paper, a tree-based encoding method is introduced to represent the Beta basis function neural network. The proposed model called Flexible Beta Basis Function Neural Tree (FBBFNT) canExpand
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Hierarchical multi-dimensional differential evolution for the design of beta basis function neural network
This paper proposes a hierarchical multi-dimensional differential evolution (HMDDE) algorithm, which is an automatic computational frame work for the optimization of beta basis function neuralExpand
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Automatic Selection for the Beta Basis Function Neural Networks
In this paper, we propose a differential evolution algorithm based design for the beta basis function neural network. The differential Evolution algorithm has been used in many practical cases andExpand
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Human Expertise in Mobile Robot Navigation
Numerous applications, such as material handling, manufacturing, security, and automated transportation systems, use mobile robots. Autonomous navigation remains one of the primary challenges of theExpand
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Moving average multi directional local features for speaker recognition
A new speech feature extraction technique called moving average multi directional local features (MA-MDLF) is presented in this paper. This method is based on linear regression (LR) and movingExpand
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Opposition-based particle swarm optimization for the design of beta basis function neural network
Many methods for solving optimization problems, whether direct or indirect, rely upon gradient information and therefore may converge to a local optimum. Global optimization methods like EvolutionaryExpand
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Evolving Flexible Beta Operator Neural Trees (FBONT) for Time Series Forecasting
In this paper, a new time-series forecasting model based on the Flexible Beta Operator Neural Tree (FBONT) is introduced. The FBONT model which has a tree-structural representation is considered as aExpand
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Opposition-based differential evolution for beta basis function neural network
Many methods for solving optimization problems, whether direct or indirect, rely upon gradient information and therefore may converge to a local optimum. Global optimization methods like EvolutionaryExpand
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Designing Beta Basis Function Neural Network for optimization using Artificial Bee Colony (ABC)
This paper presents an application of swarm intelligence technique namely Artificial Bee Colony (ABC) to design the design of the Beta Basis Function Neural Networks (BBFNN). The focus of thisExpand
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