Search Results - intelligence system ((((model algorithm) OR (svm algorithm))) OR (force algorithm))
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Intelligent Optimization of Force Tracking Parameters for MR Damper Modelling using Firefly Algorithm
Published 2020“…To overcome this problem, an intelligent optimization method known as firefly algorithm (FA) was used by this study to optimize the force tracking controller (FTC) parameters as to achieve the exact damping force of MR damper system. …”
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Proceeding -
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…The objective of this study is to suggest the potential classification model for talent forecasting throughout some experiments using SVM learning algorithm. …”
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Research Reports -
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Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz
Published 2019“…Therefore, Cuckoo Search Algorithm (CS) is hybrid with LS-SVM in order to optimize the RBF parameters for a better prediction performance. …”
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An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery
Published 2016“…This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton by means of an intelligent active force control (AFC) mechanism. …”
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A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed
Published 2016“…An intelligent Active Force Control (AFC) scheme is utilised to compensate disturbances that a conventional PID control algorithm alone is unable to due to the system’s highly nonlinear behaviour. …”
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Dual-tone multifrequency signal detection using support vector machines
Published 2023Subjects:Conference paper -
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Hybrid harmony search-artificial intelligence models in credit scoring
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Prediction of Optimum Cutting Conditions in Dry Turning Operations of S45C Mild Steel using AIS and PSO Intelligent Algorithm
Published 2014“…The suggested system is based on Particle Swarm Optimization (PSO) and Artificial Immune System (AIS) intelligent algorithms. …”
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Development of a robust intelligent controller for a semi-active car suspension system
Published 2022“…Semi-active suspension systems outperformed passive and active suspension systems because it contains an intelligent actuator that can give the appropriate force to dissipate unwanted vibration using intelligent and real-time controllers. …”
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An Intelligent System Approach to the Dynamic Hybrid Robot Control
Published 1996“…Firstly an algorithm was formulated that can estimate the attracting basin boundary for a stable equilibrium point of a robot's kinematic nonlinear system. …”
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Real time self-calibration algorithm of pressure sensor for robotic hand glove system
Published 2019“…The model was tested using an untrained input data set in order to verify the Proposed model’s capability for implementing a self-calibration algorithm. …”
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Applications of machine learning to friction stir welding process optimization
Published 2020“…In application of SVM algorithm the prediction accuracy found 100% for training and testing process.…”
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A preliminary lightweight random forest approach-based image classification for plant disease detection
Published 2022“…Random Forest is a special kind of ensemble learning technique and it turns out to perform very well compared to other classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN). …”
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