Search Results - (( parameter adaptation based algorithm ) OR ( pre evaluation method algorithm ))
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1
Design of QFT-based self-tuning deadbeat controller
Published 2013“…By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called self tuning QFT-based deadbeat controller could be achieved. …”
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2
Design of QFT-based self-tuning deadbeat controller
Published 2013“…By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called self tuning QFT-based deadbeat controller could be achieved. …”
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3
Identifying and detecting unlawful behavior in video images using genetic algorithm / Shahirah Mohamed Hatim
Published 2016“…GA is used as the method of unlawful behavior detection. Previous research on GA components impact evaluation has identified selection parameter as high potential of increasing GA performance for unlawful behavior detection. …”
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4
Instance matching framework for heterogeneous semantic web content over linked data environment
Published 2021“…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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5
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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6
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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7
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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8
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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9
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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10
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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11
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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12
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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13
Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…To alleviate this parameter tuning problem, an adaptive mechanism can be introduced in EPO. …”
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14
Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant
Published 2014“…The Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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15
Novel Robot Manipulator Adaptive Artificial Control: Design a Novel SISO Adaptive Fuzzy Sliding Algorithm Inverse Dynamic Like Method.
Published 2011“…The main objective in this research is analyses and design of the adaptive robust controller based on artificial intelligence and nonlinear control. …”
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16
Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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17
A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Unlike most existing meta-heuristic algorithms, and by virtue of being parameter-free, TLBO does not have any specific parameter controls. …”
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18
Design of intelligent control system and its application on fabricated conveyor belt grain dryer
Published 2011“…These EAs overcome a common problem encountered in derivative-based learning methods, which is the necessity for the teaching signal when applying the ANIFIS as a controller.To demonstrate the effectiveness of the proposed controller, several non-linear plant models were used to evaluate its performance in terms of control accuracy, generalization ability, and robustness against external disturbances and parameter variations in the controlled system. …”
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19
Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
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