Journal ArticleDOI
Modular Neural Networks architecture optimization with a new nature inspired method using a fuzzy combination of Particle Swarm Optimization and Genetic Algorithms
TLDR
This paper describes a new hybrid approach for optimization combining Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) using Fuzzy Logic to integrate the results and shows the new FPSO+FGA method to be superior with respect to both the individual evolutionary methods.About:
This article is published in Information Sciences.The article was published on 2014-06-20. It has received 97 citations till now. The article focuses on the topics: Multi-swarm optimization & Metaheuristic.read more
Citations
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Journal ArticleDOI
A social learning particle swarm optimization algorithm for scalable optimization
Ran Cheng,Yaochu Jin +1 more
TL;DR: This paper introduces social learning mechanisms into particle swarm optimization (PSO) to develop a social learning PSO (SL-PSO), which performs well on low-dimensional problems and is promising for solving large-scale problems as well.
Journal ArticleDOI
A new particle swarm optimization algorithm with adaptive inertia weight based on Bayesian techniques
TL;DR: A new adaptive inertia weight adjusting approach is proposed based on Bayesian techniques in PSO, which is used to set up a sound tradeoff between the exploration and exploitation characteristics and is compared with other types of improved PSO algorithms, which also performs well.
Journal ArticleDOI
A Nonlinear Fuzzy Neural Network Modeling Approach Using an Improved Genetic Algorithm
Ridong Zhang,Jili Tao +1 more
TL;DR: A new FNN framework is first proposed by combining an AutoRegressive with exogenous input with the nonlinear Tanh function in the Takagi–Sugeno (T-S) type fuzzy consequent part to optimize the structure and parameters of the FNN simultaneously under unknown plant dynamics.
Journal ArticleDOI
A novel method to solve supplier selection problem: Hybrid algorithm of genetic algorithm and ant colony optimization
TL;DR: This is an innovative pilot research to leverage hybrid AI-based algorithm of GA and ACO to settle the supplier selection problem, which not only makes a clear methodological contribution for optimization algorithm research, but also can be served as a decision tool and provide management reference for companies.
Book ChapterDOI
A Novel PSO Based Back Propagation Learning-MLP (PSO-BP-MLP) for Classification
TL;DR: Comparison result shows that, PSO-MLP gives promising results in majority of test case problems, and an extensive experimental analysis has been performed by comparing the performance of the proposed method with MLP, GA- MLP.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Journal ArticleDOI
The particle swarm - explosion, stability, and convergence in a multidimensional complex space
M. Clerc,James Kennedy +1 more
TL;DR: This paper analyzes a particle's trajectory as it moves in discrete time, then progresses to the view of it in continuous time, leading to a generalized model of the algorithm, containing a set of coefficients to control the system's convergence tendencies.