Search Results - (( parameter implementation learning algorithm ) OR ( parameter estimation system algorithm ))
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1
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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2
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…In this work, two AP selection algorithms are proposed which are Max Kernel and Kernel Logistic Discriminant that implement the knowledge of kernel density estimate and logistic regression machine learning classification. …”
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3
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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4
Active force control with iterative learning control algorithm for a vehicle suspension
Published 2013“…The AFC with ILC (AFCIL) suspension system was experimented both through simulation and practical experimentation considering various ILC learning parameters, differenti operating conditions and a number of external disturbances to test and verify the system robustness. …”
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5
Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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6
Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich
Published 2019“…At the same time, the system throughput was increased. The proposed algorithms reduced the handover number, packet delay and packet loss by 48%, 89% and 85% respectively, whereas the system throughput increased by 13% compared to reference algorithms.…”
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7
Development of gender and race recognition system using speech and recognition by using frequency spectrum
Published 2009“…In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. …”
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Learning Object -
8
Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line
Published 2020“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region
Published 2025“…This study employs various machine learning and deep learning algorithms, specifically Random Forest (RF), Artificial Neural Network (ANN), and Deep Learning Neural Network (DLNN), to estimate landslide susceptibility in Chamoli district, Uttarakhand, India?…”
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11
Utilizing P-Type ILA in tuning Hybrid PID Controller for Double Link Flexible Robotic Manipulator
Published 2018“…PType iterative learning algorithm (ILA) control scheme is implemented to adapt the controller parameters to meet the desired performances when there are changes to the system. …”
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Proceeding -
12
Utilizing P-Type ILA in tuning Hybrid PID Controller for Double Link Flexible Robotic Manipulator
Published 2018“…PType iterative learning algorithm (ILA) control scheme is implemented to adapt the controller parameters to meet the desired performances when there are changes to the system. …”
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13
Estimation in spot welding parameters using genetic algorithm
Published 2007“…By using Genetic algorithm (GA) the spot welding parameters can be estimated.…”
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14
A new metaphor-less algorithms for the photovoltaic cell parameter estimation
Published 2023“…Multiobjective optimization; Parameter estimation; Photoelectrochemical cells; Photovoltaic cells; Solar power generation; Cell parameter; Estimated parameter; Local minimums; Optimization algorithms; Pre-mature convergences; Solar cell parameters; Solar photovoltaic system; Solar PVs; Solar cells…”
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15
An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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16
Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…Therefore, it is crucial to assess the parameter of chaotic systems. To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. …”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…Both the model order and the parameters of the system are estimated simultaneously to attain the best mathematical model of a system. …”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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19
An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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20
Prioritisation assessment and robust predictive model for a comprehensive medical equipment maintenance using machine learning techniques / Aizat Hilmi Zamzam
Published 2022“…The development of predictive models for objectives 1 and 2 of this study involves the application of seven supervised machine learning algorithms. The effectiveness of these models is assessed through eleven performance evaluation parameters. …”
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