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1
Optimization Of Bar Linkage By Using Genetic Algorithms
Published 2005“…Penalty-based transformation method is used in this thesis to change the constrained problems into unconstrained ones. …”
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Monograph -
2
An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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Thesis -
3
Optimization of fast fourier transform based on twiddle factor using genetic algorithm on raspberry pi
Published 2019“…Over the years the Genetic Algorithms (GA) proved to be one of the best methods for optimization. …”
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Thesis -
4
Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform
Published 2014“…Later, an algorithm combining both Genetic Algorithm and Discrete Cosine Transform was proposed, which shows the step-by-step sequence of both methods. …”
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Final Year Project -
5
Voltage constrained optimal power flow based using genetic algorithm
Published 2015“…Active power generator, generator-buses voltages, transformer tap and injection capacitor are used as control parameters. Effectiveness of the proposed method was tested on IEEE 30 bus system and it has been compared to other optimization of power fl ow using other methods, for example the Evolutionary Programming (EP), Differential Evolution (DE) and Particle Swarm Optimization (PSO) methods. …”
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Article -
6
Local Stereo Matching Algorithm Using Small-Color Census Spared Adaptive Support Weight
Published 2011“…This work is still on process, to test the algorithm; it will use the Middlebury benchmark. According to analysis of each step of the algorithms, the proposed SCCADSW can achieve good performance among stereo methods that rely on local optimization…”
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Conference or Workshop Item -
7
Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…Clustering, an unsupervised method of grouping sets of data, is used as a solution technique in various fields to divide and restructure data to become more significant and transform them into more useful information. …”
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Article -
8
Enhancement of Single and Composite Images Based on Contourlet Transform Approach
Published 2009“…The objective evaluation steps show that the new method of enhancement not only superior to the commonly used transformation method (e.g. wavelet transform) but also to various spatial models (e.g. …”
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Thesis -
9
Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
Published 2012“…The proposed model coefficients determination in conjunction with various methods of optimal model order determination were then applied on MRI data using both Transient Error Reconstruction Algorithm (TERA) and modified Transient Error Reconstruction Algorithm to obtain images with improved resolution. …”
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Monograph -
10
Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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Conference or Workshop Item -
11
Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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Proceeding Paper -
12
Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm
Published 2020“…The PSSs design problem is transformed into an optimization problem which an eigenvalue-based objective function is developed and both the GA, PSO and the proposed FFA optimization methods are applied to search for the optimal control parameters of the PSSs that are connected to the multimachine in the power system. …”
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Article -
13
Using genetic algorithms as image watermarking performance optimizer / Zuhaili Zahid
Published 2008“…Thus, this project will introduce a genetic-algorithms-based technique to overcome the rounding error problem. …”
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Thesis -
14
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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Conference or Workshop Item -
15
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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Conference or Workshop Item -
16
Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
Published 2023“…The environment design for mobile robots' path planning based on industry environment shows excellent combinations with the GA method that generate the optimal path for the mobile robot with a semi-dynamic obstacle.…”
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Thesis -
17
Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The main contention of this thesis is to investigate the development of new optimization technique based on Differential Evolution algorithm (DE), applied for radar signal denoising application. …”
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Thesis -
20
Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Since there are many methods involved in each task of the multilayered ensemble, genetic algorithm is added to optimize the overall framework in order to select the optimal combinations of methods in each layer that can produce satisfactory results. …”
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