An Efficient Hybrid Swarm Intelligence-gradient Optimization Method for Complex Time Green’s Functions of Multilayer Media
نویسندگان
چکیده
A new hybrid technique for optimization of a multivariable function is proposed. This method is applied to the problem of complex time Green’s function of multilayer media. This technique combines Particle Swarm search algorithm with the gradient based quasi-Newton method. Superiority of the method is demonstrated by comparing its results with other optimization techniques.
منابع مشابه
Finding the Optimal Path to Restoration Loads of Power Distribution Network by Hybrid GA-BCO Algorithms Under Fault and Fuzzy Objective Functions with Load Variations
In this paper proposes a fuzzy multi-objective hybrid Genetic and Bee colony optimization algorithm(GA-BCO) to find the optimal restoration of loads of power distribution network under fault.Restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. To improve the efficiency of restoration and facilitate theactivity...
متن کاملStock Price Prediction using Machine Learning and Swarm Intelligence
Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...
متن کاملOn the hybrid conjugate gradient method for solving fuzzy optimization problem
In this paper we consider a constrained optimization problem where the objectives are fuzzy functions (fuzzy-valued functions). Fuzzy constrained Optimization (FO) problem plays an important role in many fields, including mathematics, engineering, statistics and so on. In the other side, in the real situations, it is important to know how may obtain its numerical solution of a given interesting...
متن کاملA Hybrid Time Series Clustering Method Based on Fuzzy C-Means Algorithm: An Agreement Based Clustering Approach
In recent years, the advancement of information gathering technologies such as GPS and GSM networks have led to huge complex datasets such as time series and trajectories. As a result it is essential to use appropriate methods to analyze the produced large raw datasets. Extracting useful information from large data sets has always been one of the most important challenges in different sciences,...
متن کاملFeature Selection Using Evolutionary Functional Link Neural Network for Classification
Received Sep 17, 2017 Revised Nov 18, 2017 Accepted Nov 23, 2017 Computational time is high for Multilayer perceptron (MLP) trained with back propagation learning algorithm (BP) also the complexity of the network increases with the number of layers and number of nodes in layers. In contrast to MLP, functional link artificial neural network (FLANN) has less architectural complexity, easier to tr...
متن کامل