Search Results - (( basic optimization based algorithm ) OR ( problem implementation _ algorithm ))
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1
A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
Published 2023“…Four types of benchmark functions are applied to test the performances of the proposed algorithm. Furthermore, the proposed algorithm is applied in the IEEE-26 bus system for tackling the economic dispatch problem. …”
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2
The design and applications of the african buffalo algorithm for general optimization problems
Published 2017“…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
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3
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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4
Stochastic process and tutorial of the African buffalo optimization
Published 2022“…This paper presents the data description of the African buffalo optimization algorithm (ABO). ABO is a recently-designed optimization algorithm that is inspired by the migrant behaviour of African buffalos in the vast African landscape. …”
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5
Stochastic process and tutorial of the African bufalo optimization
Published 2022“…This paper presents the data description of the African buffalo optimization algorithm (ABO). ABO is a recently-designed optimization algorithm that is inspired by the migrant behaviour of African buffalos in the vast African landscape. …”
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6
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The final problem is the ability of the algorithm to solve large-scale problems, which mostly are the real world problems. …”
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7
An application of barnacles mating optimizer algorithm for combined economic and emission dispatch solution
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8
Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…Particle Swarm Optimization (PSO) is a population-based metaheuristic that possesses many advantages compared to other metaheuristics in solving scheduling problems. …”
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9
Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End
Published 2012“…We implement a branch-and-contract algorithm that aims at reducing the size of the search region. …”
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10
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…Due to the high complexity of these problems, metaheuristic based global optimization techniques are usually required. …”
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11
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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12
Optimal resource allocation for NOMA wireless networks
Published 2022“…The major goal is to maximize the users’ maximum weighted sum rate. The suggested algorithm’s most notable feature is that it converges to the global optimal solution. …”
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13
Implementation of Symmetric Rank-One Methods for Unconstrained Optimization
Published 2010“…We then examine a new scaled memoryless SR1 method based on modied secant equation for solving large-scale unconstrained optimization problems. …”
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14
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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15
Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…As a result,it will first introduce the theories about the feature extraction and the basic principles on how feature points can act as locating resynchronization between watermark insertion and extraction discussed in detail.Subsequently,it will present several content-based watermark embedding and extraction methods which can be directly implemented based on the synchronization scheme.Further detailed watermarking schemes which combine feature regions extraction with counter propagation neural network-based watermarks synapses memorization are then presented.The performance of watermarking schemes based on framework of feature point shows the following advantages:a)Good imperceptibility. …”
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16
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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17
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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18
Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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19
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Several variants of PSO have been proposed for solving discrete optimization problems like TSP. Among them, the basic algorithm is the Swap Sequence based PSO (SSPSO), however, it does not perform well in providing high quality solutions. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
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