Search Results - (( _ distribution drops algorithm ) OR ( parameter adaptation ((a algorithm) OR (new algorithm)) ))
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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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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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Performance study of adaptive filtering algorithms for noise cancellation of ECG signal
Published 2023“…Removal of noises from ECG (Electrocardiogram) signal is a classical problem. Moreover, nullifying AC and DC noises using the two adaptive algorithms-the LMS and the RLS from the ECG is a new study in biomedical science. …”
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…Thus, this research proposed a new method known as Back Propagation Gradient Descent with Adaptive Gain, Adaptive Momentum and Adaptive Learning Rate (BPGD-AGAMAL) which modifies the existing Back Propagation Gradient Descent algorithm by adaptively changing the gain, momentum coefficient and learning rate. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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A comparative study for parameter selection in online auctions
Published 2009“…The bidding strategies applying self-adaptation model are expected to perform better than the deterministic dynamic adaptation because of the nature of the algorithm itself. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…In this paper, a new method is designed to effectively determine the parameters of proton exchange membrane fuel cells (PEMFCs), i.e., ?…”
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025“…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…A new algorithm of coordinate gradient descent (CGD) is developed to optimize the adaptive LASSO. …”
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UMK Etheses -
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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