Classification of Dementia Using Harmony Search Optimization Technique

2018 ◽  
Author(s):  
Bharanidharan N. ◽  
Harikumar Rajaguru
Keyword(s):  
Optimization Technique ◽  
Harmony Search ◽  
Search Optimization

scholarly journals FSD-HSO Optimization Algorithm for Closed Fringes Interferogram Demodulation

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ulises H. Rodriguez-Marmolejo ◽  
Miguel Mora-Gonzalez ◽  
Jesus Muñoz-Maciel ◽  
Tania A. Ramirez-delreal
Keyword(s):  
Relative Error ◽  
Optimization Technique ◽  
Harmony Search ◽  
Mathematical Optimization ◽  
Physical Nature ◽  
Algorithm Optimization ◽  
Interference Phenomenon ◽  
Sinusoidal Modulation ◽  
Search Optimization ◽  
Mathematical Optimization Model

Due to the physical nature of the interference phenomenon, extracting the phase of an interferogram is a known sinusoidal modulation problem. In order to solve this problem, a new hybrid mathematical optimization model for phase extraction is established. The combination of frequency guide sequential demodulation and harmony search optimization algorithms is used for demodulating closed fringes patterns in order to find the phase of interferogram applications. The proposed algorithm is tested in four sets of different synthetic interferograms, finding a range of average relative error in phase reconstructions of 0.14–0.39 rad. For reference, experimental results are compared with the genetic algorithm optimization technique, obtaining a reduction in the error up to 0.1448 rad. Finally, the proposed algorithm is compared with a very known demodulation algorithm, using a real interferogram, obtaining a relative error of 1.561 rad. Results are shown in patterns with complex fringes distribution.

scholarly journals Real-time implementation of an enhanced nonlinear PID controller based on harmony search for one-stage servomechanism system

2018 ◽  
Vol 12 (4) ◽  
pp. 4161-4179
Author(s):  
Mohamed. A. Shamseldin ◽  
Mohamed Sallam ◽  
A. M. Bassiuny ◽  
A. M. Abdel Ghany
Keyword(s):  
Real Time ◽  
Pid Controller ◽  
Controller Design ◽  
Optimization Technique ◽  
Harmony Search ◽  
Reference Test ◽  
Variable Position ◽  
Labview Software ◽  
One Stage ◽  
Search Optimization

This paper presents a real-time implementation of an enhanced nonlinear PID (NPID) controller to follow a preselected position profile of one stage servomechanism drive system. This purpose should be realized regardless the different operating points and external disorders (friction and backlash). In this study, the MATLAB Simulink used for purpose of controller design while the result from simulation will be executed in real time using LABVIEW software. There is not enough information about the servomechanism experimental setup so, the system identification techniques will be used via collecting experimental input/output data. The optimum parameters for the controllers have been obtained via harmony search optimization technique according to an effective cost function. Also, the performance of enhanced NPID controller has been investigated by comparing it with linear PID controller.  The experimental and simulation results show that the proposed NPID controller has minimum rise time and settling time through constant position reference test. Also, the NPID control is faster than the linear PID control by 40% in case of variable position reference test.

scholarly journals A modified simplex based direct search optimization algorithm for adaptive transversal FIR filters

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110254
Author(s):  
Armaghan Mohsin ◽  
Yazan Alsmadi ◽  
Ali Arshad Uppal ◽  
Sardar Muhammad Gulfam
Keyword(s):  
Optimization Algorithm ◽  
Optimization Technique ◽  
Fast Convergence ◽  
Good Convergence ◽  
Optimum Point ◽  
Search Optimization ◽  
Higher Dimensional ◽  
Gradient Based ◽  
Improved Accuracy ◽  
Quadratic Cost Function

In this paper, a novel modified optimization algorithm is presented, which combines Nelder-Mead (NM) method with a gradient-based approach. The well-known Nelder Mead optimization technique is widely used but it suffers from convergence issues in higher dimensional complex problems. Unlike the NM, in this proposed technique we have focused on two issues of the NM approach, one is shape of the simplex which is reshaped at each iteration according to the objective function, so we used a fixed shape of the simplex and we regenerate the simplex at each iteration and the second issue is related to reflection and expansion steps of the NM technique in each iteration, NM used fixed value of [Formula: see text], that is, [Formula: see text]  = 1 for reflection and [Formula: see text]  = 2 for expansion and replace the worst point of the simplex with that new point in each iteration. In this way NM search the optimum point. In proposed algorithm the optimum value of the parameter [Formula: see text] is computed and then centroid of new simplex is originated at this optimum point and regenerate the simplex with this centroid in each iteration that optimum value of [Formula: see text] will ensure the fast convergence of the proposed technique. The proposed algorithm has been applied to the real time implementation of the transversal adaptive filter. The application used to demonstrate the performance of the proposed technique is a well-known convex optimization problem having quadratic cost function, and results show that the proposed technique shows fast convergence than the Nelder-Mead method for lower dimension problems and the proposed technique has also good convergence for higher dimensions, that is, for higher filter taps problem. The proposed technique has also been compared with stochastic techniques like LMS and NLMS (benchmark) techniques. The proposed technique shows good results against LMS. The comparison shows that the modified algorithm guarantees quite acceptable convergence with improved accuracy for higher dimensional identification problems.

scholarly journals An enhanced krill herd optimization technique used for classification problem

2021 ◽  
Vol 30 (2) ◽  
pp. 354-364
Author(s):  
Firas Al-Mashhadani ◽  
Ibrahim Al-Jadir ◽  
Qusay Alsaffar
Keyword(s):  
Machine Learning ◽  
Simulated Annealing ◽  
Optimization Technique ◽  
Optimization Method ◽  
Classification Problem ◽  
Test Results ◽  
Internal Evaluation ◽  
Evaluation Measures ◽  
Search Optimization ◽  
Krill Herd

In this paper, this method is intended to improve the optimization of the classification problem in machine learning. The EKH as a global search optimization method, it allocates the best representation of the solution (krill individual) whereas it uses the simulated annealing (SA) to modify the generated krill individuals (each individual represents a set of bits). The test results showed that the KH outperformed other methods using the external and internal evaluation measures.

scholarly journals Power Loss Calculation in 11-Level Cascaded H-Bridge Inverter using Harmony Search Optimized Switching Scheme

2019 ◽  
Vol 8 (6) ◽  
pp. 5200-5205
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
System Analysis ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Harmony Search ◽  
Multilevel Inverter ◽  
Total Power ◽  
Multi Objective Optimization ◽  
Multi Objective

Power loss is the most significant parameter in power system analysis and its adequate calculation directly effects the economic and technical evaluation. This paper aims to propose a multi-objective optimization algorithm which optimizes dc source magnitudes and switching angles to yield minimum THD in cascaded multilevel inverters. The optimization algorithm uses metaheuristic approach, namely Harmony Search algorithm. The effectiveness of the multi-objective algorithm has been tested with 11-level Cascaded H-Bridge Inverter with optimized DC voltage sources using MATLAB/Simulink. As the main objective of this research paper is to analyze total power loss, calculations of power loss are simplified using approximation of curves from datasheet values and experimental measurements. The simulation results, obtained using multi-objective optimization method, have been compared with basic SPWM, optimal minimization of THD, and it is confirmed that the multilevel inverter fired using multi- objective optimization technique has reduced power loss and minimum THD for a wide operating range of multilevel inverter.

scholarly journals Improving the delivered power quality from WECS to the grid based on PMSG control model

2020 ◽  
Vol 10 (6) ◽  
pp. 6349
Author(s):  
Shimaa A. Hussien ◽  
M. A. Deab ◽  
N. S. Hosny
Keyword(s):  
Wind Energy ◽  
Power Electronics ◽  
Power Quality ◽  
Software Package ◽  
Optimization Technique ◽  
Harmony Search ◽  
Synchronous Generator ◽  
Power Circuit ◽  
Energy Applications ◽  
Grid Side

Renewable energy has become one of the most energy resources nowadays, especially, wind energy. It is important to implement more analysis and develop new control algorithms due to the rapid changes in the wind generators size and the power electronics development in wind energy applications. This paper proposes a grid-connected wind energy conversion system (WECS) control scheme using permanent magnet synchronous generator (PMSG). The model works to improve the delivered power quality and maximize its value. The system contained one controller on the grid side converter (GSC) and two simulation packages used to simulate this model, which were PSIM software package for simulating power circuit and power electronics converters, and MATLAB software package for simulating the controller on Simulink. It employed a meta-heuristic technique to fulfil this target effectively. Mine-blast algorithm (MBA) and harmony search optimization technique (HSO) were applied to the proposed method to get the best controller coefficient to ensure maximum power to the grid and minimize the overshoot and the steady state error for the different control signals. The comparison between the results of the MBA and the HSO showed that the MBA gave better results with the proposed system.

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