Search Results - (( parameter adaptation based algorithm ) OR ( pattern optimization method algorithm ))
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique
Published 2022“…The work in this thesis is expected to be the best approach in formulating an adaptive fuzzy technique based on brute force and regression algorithms for optimization and prediction of EMS in BEV application.…”
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Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction
Published 2025“…Adaptive gradient-based algorithms, including ADAM, NADAM, ADADELTA, ADAGRAD, and ADAMAX, exhibited superior performance. …”
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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks
Published 2017“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization
Published 2025“…The study introduces a hybrid model that integrates TCN with Artificial Fish Swarm Algorithm (AFSA), a bio-inspired optimization technique designed to fine-tune TCN parameters. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Fuzzy Logic Based Self-Adaptive Handover Algorithm for MobileWiMAX.
Published 2013“…The proposed FuzSAHO algorithm will first self-adapt the handover parameters based on a set of multiple criteria, which includes the RSSI and MS velocity. …”
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Novel parameter extraction for single, double, and three diodes photovoltaic models based on robust adaptive arithmetic optimization algorithm and adaptive damping method of Berndt-Hall-Hall-Hausman
Published 2022“…In this work, we present a robust adaptive Arithmetic Optimization Algorithm based on the adaptive damping Berndt-hall-hall-Hausman (RaAOAAdBHHH) approach to efficacity determine the parameters of the single, double, and three diode PV model. …”
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Self-adaptive Population Size Strategy Based on Flower Pollination Algorithm for T-Way Test Suite Generation
Published 2019“…Addressing this issue, this paper proposes self-adaptive population size strategy based on Flower Pollination Algorithm, called saFPA for t-way test suite generation. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…The proposed design framework provides readers with the main steps required to integrate any proposed meta-algorithm into parameter and/or strategy adaptation schemes.…”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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Application of pattern search method to economic load dispatch with valve point loading / Siti Aisah Md. Sari
Published 2010“…This study presents the application of Pattern Search (PS) method in Economic Dispatch (ED) problem; ED is used to optimize the fuel cost of electric energy while at the same time allocate the demand between available generation unit. …”
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On the problem formulation for parameter extraction of the photovoltaic model: novel integration of hybrid evolutionary algorithm and Levenberg Marquardt based on adaptive damping parameter formula
Published 2022“…This paper presents an approach to determine the nine parameters of the three diode (TD) PV model based on the integration of the guaranteed convergence arithmetic optimization algorithm and Levenberg-Marquardt with adaptive damping nonlinear parameter method named as GCAOAAdLM. …”
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Sheet C1 Pattern Number Recognition Using Artificial Immune System Optimization
Published 2022“…In order to recognize the numerical patterns on sheet C1, we, therefore, require a method that uses the Artificial Immune System (AIS), specifically the CSA (Clonal Selection Algorithm) algorithm, which is one of the AIS system's algorithms for optimization. …”
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Analysis of LMS and NLMS noise cancellations of speech signal using Matlab Simulink / Roziahtushahila Hashim
Published 2014“…The LMS adaptive filter has several parameters which can affect their performance. …”
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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification
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Optimizing Central Pattern Generators (CPG) Controller For One Legged Hopping Robot By Using Genetic Algorithm (GA)
Published 2018“…Therefore,a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters. …”
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DESIGN OF ADAPTIVE BACKSTEPPING WITH GRAVITATIONAL SEARCH ALGORITHM FOR NONLINEAR SYSTEM
Published 2014“…Gravitational search algorithm (GSA) is integrated with the designed controller in order to automatically tune its control parameters and adaptation gain since the tracking performance of the controller relies on these parameters. …”
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