Normal Parameter Reduction in Soft Set Based on Harmony Search Algorithm

2014 ◽  
Vol 644-650 ◽  
pp. 2173-2176
Author(s):  
Zhi Kong ◽  
Guo Dong Zhang ◽  
Li Fu Wang
Keyword(s):  
Data Mining ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Soft Set ◽  
Intelligent Optimization ◽  
Parameter Reduction ◽  
Intelligent Optimization Algorithm ◽  
Normal Parameter

The normal parameter reduction in soft set is difficult to application in data mining because of great calculation quantity. In this paper, the intelligent optimization algorithm, the harmony search algorithm, is applied to solve the problem. The normal parameter reduction model is constructed and the harmony search algorithm is designed. Experience has shown that the method is feasible and fast..

Hybrid Data Mining Approach for Image Segmentation Based Classification

Biometrics ◽  
2017 ◽  
pp. 1543-1561 ◽  
Author(s):  
Mrutyunjaya Panda ◽  
Aboul Ella Hassanien ◽  
Ajith Abraham
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Image Segmentation ◽  
Search Algorithm ◽  
Rbf Neural Network ◽  
Harmony Search ◽  
Optimal Solution ◽  
Solution Space ◽  
Harmony Search Algorithm ◽  
Data Mining Technique

Evolutionary harmony search algorithm is used for its capability in finding solution space both locally and globally. In contrast, Wavelet based feature selection, for its ability to provide localized frequency information about a function of a signal, makes it a promising one for efficient classification. Research in this direction states that wavelet based neural network may be trapped to fall in a local minima whereas fuzzy harmony search based algorithm effectively addresses that problem and able to get a near optimal solution. In this, a hybrid wavelet based radial basis function (RBF) neural network (WRBF) and feature subset harmony search based fuzzy discernibility classifier (HSFD) approaches are proposed as a data mining technique for image segmentation based classification. In this paper, the authors use Lena RGB image; Magnetic resonance image (MR) and Computed Tomography (CT) Image for analysis. It is observed from the obtained simulation results that Wavelet based RBF neural network outperforms the harmony search based fuzzy discernibility classifiers.

Improved Harmony Search Algorithm with Crossover Operation

2013 ◽  
Vol 415 ◽  
pp. 353-356 ◽  
Author(s):  
Hong Gang Xia ◽  
Qing Liang Wang
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Optimization Methods ◽  
Optimization Method ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
Intelligent Optimization ◽  
New Variant ◽  
Improved Harmony Search ◽  
Improved Harmony Search Algorithm

Harmony search (HS) algorithm is a good meta-heuristic intelligent optimization method and it does depend on imitating the music improvisation process to generate a perfect state of harmony. However, intelligent optimization methods is easily trapped into local optimal, HS is no exception. In order to improve the performance of HS, a new variant of harmony search algorithm is proposed in this paper. The variant introduce a new crossover operation into HS, and design a strategy to adjust parameter pitch adjusting rate (PAR) and bandwidth (BW). Several standard benchmarks carried out to be tested. The numerical results demonstrated that the superiority of the proposed method to the HS and recently developed variants (IHS, and GHS).

An Efficient Control Implementation for Inverter Based Harmony Search Algorithm

2017 ◽  
Vol 8 (1) ◽  
pp. 279
Author(s):  
Mushtaq Najeeb ◽  
Hamdan Daniyal ◽  
Ramdan Razali ◽  
Muhamad Mansor
Keyword(s):  
Optimization Algorithm ◽  
Search Algorithm ◽  
Dynamic Performance ◽  
Harmony Search ◽  
Absolute Error ◽  
Fast Response ◽  
Pi Controller ◽  
Harmony Search Algorithm ◽  
Voltage Source ◽  
Output Performance

This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. The HS algorithm aims to handle the trial and error procedure used in finding the PI parameters and then apply the proposed control algorithm via the eZdsp TMS320F28355 board to link the inverter prototype with the Matlab Simulink. The mean absolute error (MAE) is used as an optimization problem to minimize the output voltage error for the developed controller (PI-HS) as compared to the PI controller based particale swarm optimization algorithm (PI-PSO). Based on the experimental results obtained, it is noted that the proposed controller (PI-HS) provides a good dynamic performance, robustness, constant voltage amplitude, and fast response in terms of overshoot, transient, and steady-state.

scholarly journals Improved Multiobjective Harmony Search Algorithm with Application to Placement and Sizing of Distributed Generation

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Wanxing Sheng ◽  
Ke-yan Liu ◽  
Yunhua Li ◽  
Yuan Liu ◽  
Xiaoli Meng
Keyword(s):  
Distributed Generation ◽  
Search Algorithm ◽  
Harmony Search ◽  
Engineering Application ◽  
Test System ◽  
Harmony Search Algorithm ◽  
Optimal Placement ◽  
The Novel ◽  
Nsga Ii ◽  
Intelligent Optimization Algorithm

To solve the comprehensive multiobjective optimization problem, this study proposes an improved metaheuristic searching algorithm with combination of harmony search and the fast nondominated sorting approach. This is a kind of the novel intelligent optimization algorithm for multiobjective harmony search (MOHS). The detailed description and the algorithm formulating are discussed. Taking the optimal placement and sizing issue of distributed generation (DG) in distributed power system as one example, the solving procedure of the proposed method is given. Simulation result on modified IEEE 33-bus test system and comparison with NSGA-II algorithm has proved that the proposed MOHS can get promising results for engineering application.

Hybrid Harmony Search Algorithm to Solve the Feature Selection for Data Mining Applications

2020 ◽  
pp. 19-37 ◽  
Author(s):  
Laith Mohammad Abualigah ◽  
Mofleh Al‐diabat ◽  
Mohammad Al Shinwan ◽  
Khaldoon Dhou ◽  
Bisan Alsalibi ◽  
...  
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Selection For

A New Variant Harmony Search Algorithm with Random Mutation Strategy

2014 ◽  
Vol 1065-1069 ◽  
pp. 3425-3428
Author(s):  
Xiu Hong Zhao
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Optimization Methods ◽  
Optimization Method ◽  
Harmony Search Algorithm ◽  
Random Mutation ◽  
Local Optima ◽  
Intelligent Optimization ◽  
New Variant ◽  
Mutation Strategy

Harmony search (HS) algorithm is a good meta-heuristic intelligent optimization method, which has been paid much attention recently. However, intelligent optimization methods are easily trapped into local optima, HS is no exception. In order to improve the performance of HS, a new variant of harmony search algorithm with random mutation strategy (HSRM) is proposed in this paper. The HSRM uses a random mutation strategy to replace the pitch adjusting operation, and dynamically adjust the key parameter pitch adjusting rate (PAR). Experiment results demonstrated that the proposed method is superior to the HS and recently developed variants (IHS, and GHS) and other meta-heuristic algorithm.

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