Search Results - (( course evaluation a algorithm ) OR ( parameter estimation strategy 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“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Thesis -
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…Since these parameters are affected by different operation conditions and load changings, then an accurate estimation strategy is quite necessary. …”
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Simultaneous Computation of Model Order and Parameter Estimation for Arx Model Based on Multiswarm Particle Swarm Optimization
Published 2015“…Simultaneous Model Order and Parameter Estimation (SMOPE) is a method of utilizing meta-heuristic algorithm to iteratively determine an optimal model order and parameters simultaneously for an unknown system. …”
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Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution
Published 2023“…The estimation of the shape and scale parameters of the gamma distribution is relatively straightforward using the method of moments. …”
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Automatic control of flotation process using computer vision
Published 2015“…Finally, a control strategy implementing the developed froth model and prediction system was introduced for direct optimization of metallurgical parameters. …”
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8
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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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...
Published 2022“…The estimation of the unknown parameters of the photovoltaic (PV) model is crucial for accurately verifying its real performance precisely under a wide range of climatic conditions. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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12
A multiobjective simulated Kalman filter optimization algorithm
Published 2018“…Cost function value and diversity spacing parameters are taken into consideration in the strategy. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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Using algorithmic taxonomy to evaluate lecturer workload
Published 2006“…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms
Published 2001“…The paper highlights a novel and robust method to control a robotic arm using an iterative learning technique embedded in an active force control strategy. Two main iterative learning algorithms are utilized in the study – the first is used to automatically tune the controller gains while the second to estimate the inertia matrix of the manipulator. …”
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Evaluate the performance of university course timetabling problem with different combinations of genetic algorithm
Published 2025“…University course timetabling problem (UCTP) is a scheduling problem that requires courses to be assigned to the limited time slots, classrooms, and lecturers, while adhering to a set of predefined constraints. …”
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Real-time control of automotive engine fuelled with Malaysian palm oil biodiesel
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Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong
Published 2004“…The paper highlights a novel and robust method to control a robotic arm using iterative learning technique embedded in an active force control strategy. Two iterative learning algorithms are employed in the study - the first is used to tune automatically the controller gains while the second to estimate the inertia matrix of the robotic arm. …”
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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal
Published 2006“…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal
Published 2006“…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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