An integrated harmony search algorithm-based multi-objective differential evolution of evolving spiking neural network

2016 ◽  
Vol 15 (3) ◽  
pp. 192
Author(s):  
Abdulrazak Yahya Saleh ◽  
Siti Mariyam Shamsuddin ◽  
Haza Nuzly Abdull Hamed
Keyword(s):  
Neural Network ◽  
Differential Evolution ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Spiking Neural Network ◽  
Multi Objective ◽  
Evolving Spiking Neural Network

Optimal hybrid scheme of dynamic neural network and PID controller based on harmony search algorithm to control a PWM-driven pneumatic actuator position

2017 ◽  
Vol 24 (16) ◽  
pp. 3538-3554 ◽  
Author(s):  
Mahmood Mazare ◽  
Mostafa Taghizadeh ◽  
Mohammad Ghasem Kazemi
Keyword(s):  
Neural Network ◽  
Pid Controller ◽  
Pulse Width Modulation ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Pneumatic Actuator ◽  
Hybrid Scheme ◽  
Dynamic Neural Network ◽  
Switching Valve

In this paper, the position of a pulse width modulation (PWM)-driven pneumatic actuator has been controlled using a dynamic neural network (DNN) and Proportional Integral Derivative (PID) controller. The harmony search algorithm (HSA) has been used to unravel the optimization problem. The DNN controller is optimally designed to control the position of the actuator. As to the performance of the PID controller, it can assist the DNN controller to give better results. Therefore, an optimal hybrid scheme with both DNN and PID controllers based on HSA is suggested. A pneumatic circuit containing a fast-switching valve is used to reduce the complexity of the PWM-driven servo pneumatic system along with its cost price.

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.

Multi Objective Design Optimization of Helical Gear Pair Using Adaptive Parameter Harmony Search Algorithm

2015 ◽  
Vol 813-814 ◽  
pp. 1032-1036
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Jeganathan ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Search Algorithm ◽  
Harmony Search ◽  
Helical Gear ◽  
Harmony Search Algorithm ◽  
Gear Pair ◽  
Multi Objective ◽  
Gear Design ◽  
Design Variables ◽  
Helical Gear Pair

Mechanical design engineers design products by selecting the best possible materials and geometries that satisfies the specific operational requirements of the design. It involves lot of creativity and aesthetics to make better designs. A gear design makes the designer to compromise many design variables so as to arrive the best performance of a gear set. The best possible way for multi variable, Multiobjective gear design is to try design optimization. For many complex engineering optimization problems multi objective design optimization methods are used to simplify the design problem. In this paper, multiobjective design of helical gear pair transmission with objective functions namely volume of the small and large helical gear and opposite number of overlap ratio is taken into account. The design variables considered are normal module, helix angle, gear width coefficient and teeth number of small helical gear. A recent meta-heuristic algorithm namely parameter adaptive harmony search algorithm is applied to solve this problem using the weighted sum approach. It is evident from the results that the proposed approach is performing better than other algorithms.

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