Search Results - (( simulation optimization extraction algorithm ) OR ( java application during algorithm ))
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1
Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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2
Optimized clustering with modified K-means algorithm
Published 2021“…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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3
Bees algorithm for Forest transportation planning optimization in Malaysia
Published 2021“…Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. …”
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Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin
Published 2010“…This paper presents the application of Genetic Algorithm and Ant Colony Optimization (ACO) Algorithm for robot path planning (RPP) in global static environment. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Simulation results reveal the proposed algorithm’s ability to produce real and well-distributed Pareto optimum fronts for all considered multi-objective optimization cases. …”
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PARTICLE SWARM OPTIMIZATION MAXIMUM POWER POINT TRACKING FOR PARTIALLY SHADED SOLAR PV
Published 2023“…This study proposes a particle swarm optimization (PSO) algorithm based on MPPT for the PGS to operate under PSC. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…The Matlab-Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. …”
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PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm
Published 2024“…This paper introduces a Solar PV Smart Fault Diagnosis and Classification (SFDC) model that harnesses the Random Forest (RF) algorithm in conjunction with Cross-Validation (CV) and an optimized feature extraction (FE) set. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2013“…The Matlab-Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. …”
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…In addition, to prove the superiority of the proposed hybrid forecasting method the simulation results obtained using ANN and ANFIS models optimized by other well-known optimization methods have been compared with that of proposed method. © 2019 IEEE.…”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…Next, four recently introduced optimization algorithms are employed as feature selector, namely as 1) angle modulated simulated Kalman filter (AMSKF), 2) binary simulated Kalman filter (BSKF), 3) local optimum distance evaluated simulated Kalman filter (LocalDESKF), and 4) global optimum distance evaluated simulated Kalman filter (GlobalDESKF). …”
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13
A genetic algorithm optimized RNN-LSTM model for remaining useful life prediction of turbofan engine
Published 2021“…Both feature extraction and prediction algorithm have played crucial roles on the performance of RUL prediction models. …”
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Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin
Published 2018“…The process continues repeatedly to track maximum power depending on the swarmsize of the MPPT algorithm. In order to validate this technique simulation was conducted using MATLAB SIMULINK software in order to observe and identify the output power extracted from the PV panel. …”
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15
Towards Enhancing the Performance of Grid-Tied VSWT via Adopting Sine Cosine Algorithm-Based Optimal Control Scheme
Published 2021“…The effectiveness of the proposed SCA-PI is verified in the MATLAB/Simulink environment, and the results are compared to those obtained using a grey wolf optimizer and particle swarm algorithm-based optimal PI controller. …”
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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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Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The algorithms are developed using MATLABTM software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytemsTM, and the spectra of the fault data are analyzed using fast Fourier transform which facilitates extraction of distinct features of each type of fault. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The algorithms are developed using MATLAB software. A range of faults are simulated on EHV modeled transmission line using SimPowerSytems, and the spectra of the fault data are analyzed using fast Fourier transform to extract features of each type of fault. …”
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19
Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network
Published 2023“…Hence, this thesis will utilize Non-Systematic Weighted Random 2 Satisfiability incorporating with Binary Artificial Bee Colony algorithm in Discrete Hopfield Neural Network. The Binary Artificial Bee Colony will be utilized to optimize the logical structure according to the ratio of negative literals by capitalizing the features of the exploration mechanism of the algorithm. …”
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network
Published 2022“…The first proposed algorithm aims to optimize the EE by controlling the on/off status of RRH via a deep Q network (DQN) and subsequently solving a power optimization problem. …”
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Final Year Project / Dissertation / Thesis
