Search Results - (( basic optimization method algorithm ) OR ( problem implementation _ algorithm ))
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…Researchers have in the past few decades resorted to several methods that are inspired from complex optimization problems. …”
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Ant colony optimization for solving economic dispatch of power system: article / Muhammad Shukri Che Hashim
Published 2009“…ACO algorithm used in this study was implemented by using MATLAB 7.6.0 (R2008a). …”
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Article -
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Ant colony optimization for solving economic dispatch of power system / Muhammad Shukri Che Hashim
Published 2009“…ACO algorithm used in this study was implemented by using MATLAB 7.6.0 (R2008a). …”
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Towards large scale unconstrained optimization
Published 2007“…The main difficulty in dealing with large scale problems is the fact that effective algorithms for small scale problems do not necessarily translate into efficient algorithms when applied to solve large scale problems. …”
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Inaugural Lecture -
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…These problems are known as discrete-valued optimal control problems. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…Many real-world production scheduling problems involve the simultaneous optimization of multiple conflicting objectives that are challenging to solve without the aid of powerful optimization techniques. …”
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Implementation of Symmetric Rank-One Methods for Unconstrained Optimization
Published 2010“…A review of di®erent minimization methods that can be used to solve unconstrained optimization problems is also given. …”
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Optimal resource allocation for NOMA wireless networks
Published 2022“…The suggested algorithm’s most notable feature is that it converges to the global optimal solution. …”
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Article -
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Performance optimization method in OFDM based on majorization and minimization technique
Published 2019“…This signal is affected by large Wiener Process PHN and estimated by TQM algorithm. MATLAB simulation results reveal that TQM implementation has outperform to approximate PHN in OFDM systems with high number of subcarriers (Nc).…”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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Thesis -
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Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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Particle swarm optimization (PSO) for CNC route problem
Published 2002“…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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Undergraduates Project Papers -
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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Data Analysis using Particle Swarm Optimization Algorithm
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Final Year Project / Dissertation / Thesis -
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Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators
Published 2023“…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”
Conference paper -
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Improved Multi-Verse Optimizer In Text Document Clustering For Topic Extraction
Published 2021“…Second, three multi-verse optimizer algorithm (MVOs), namely, basic MVO, modified MVO, hybrid MVO is proposed to solve the TDC problem; these algorithms are incremental improvements of the preceding versions. …”
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