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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). …”
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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Quarter-sweep arithmetic mean algorithm for water quality model
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Conference or Workshop Item -
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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…This study explores the performance accuracies of partitioning-based algorithms and probabilistic model-based algorithm. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…The columns consist of the variables that record the reading of machine sensor tags. Validation for the model is analyzed by using validation testing data and cross validation. …”
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Final Year Project -
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All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…Most available ANC uses the secondary path modelling including filtered x least mean square (FxLMS) algorithm. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…The validation test-through correlation analysis was used to validate the model. …”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…The validation test-through correlation analysis was used to validate the model. …”
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System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
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Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
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Thesis -
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Thesis -
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Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Additionally, stratified 5-fold cross-validation was performed to evaluate the performance of proposed model. …”
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Final Year Project / Dissertation / Thesis -
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A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction
Published 2018“…The results display that the regression coefficient, root-mean-square error, mean absolute error, and mean bias error values of the suggested model are 99.86%, 1.87%, 0.91%, and 0.31%, respectively. …”
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Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction
Published 2021“…The original LSTM, VRNN, and GRU are implemented and used as benchmarking models. The results show that the optimized models outperform the original three benchmarking models in terms of mean squared error (MSE), root mean square error (RMSE), and mean absolute error (MAE). …”
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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control
Published 2019“…Correlation tests were used to validate the obtained model. Based on the proposed method, a small mean squared error value has been achieved in the validation phase. …”
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