Search Results - (( parameter optimization system algorithm ) OR ( learning classification parallel algorithm ))
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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The forecasting of poverty using the ensemble learning classification methods
Published 2023“…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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A Study On The Application Of Gravitational Search Algorithm In Optimizing Stereo Matching Algorithm’s Parameters For Star Fruit Inspection System
Published 2018“…This paper reports the result obtained by implementing Gravitational Search Algorithm for tuning Stereo Matching Algorithm’s parameters for the application star fruit inspection system. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Combining deep and handcrafted image features for MRI brain scan classification
Published 2019“…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm
Published 2016“…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…Compared to another well-established optimizer, such as particle swarm optimization (PSO), the SKF algorithm is a relatively new optimizer and most importantly, the SKF algorithm has not been applied to parameter tuning of PID controller. …”
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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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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. …”
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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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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…However, to fully utilize the algorithm, the parameter of the algorithm need to be set properly. …”
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A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…This paper presents a new hybrid identification algorithm called the Average Multi-Verse Optimizer and Sine Cosine Algorithm for identifying the continuous-time Hammerstein system. …”
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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm
Published 2018“…An optimized design of a fuzzy logic system can be regarded as setting of different parameters of the system automatically. …”
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Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions
Published 2024Subjects:Conference Paper
