Search Results - (( java application svm algorithm ) OR ( parameter motion learning algorithm ))
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Recognition of human motion from qualitative normalised templates
Published 2007“…Classification of the human motion is done by comparing the QNTs to the parameters learned from numerical motion tracking. …”
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Adapting robot kinematics for human-arm motion recognition
Published 2007“…Finally, classification of the human-arm motion is achieved by comparing the QNTs to the parameters learnt with particle filter based motion tracking algorithm. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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Hybrid learning control schemes with input shaping of a flexible manipulator system.
Published 2006“…A collocated proportional-derivative (PD) controller utilizing hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate iterative learning control with acceleration feedback and genetic algorithms (GAs) for optimization of the learning parameters and a feedforward controller based on input shaping techniques for control of vibration (flexible motion) of the system. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
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Vision based automatic steering control using a PID controller
Published 2006“…Initially, a collocated proportional-derivative (PD) controller utilizing hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate iterative learning control with genetic algorithm (GA) to optimize the learning parameters and a feedforward controller based on input shaping techniques for control of vibration (flexible motion) of the system. …”
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Performance of hybrid learning control with input shaping for input tracking and vibration suppression of a flexible manipulator
Published 2006“…Initially, A Collocated Proportional-Derivative (PD) Controller Utilizing Hub-Angle And Hub-Velocity Feedback Is Developed For Control Of Rigid-Body Motion Of The System. This Is Then Extended To Incorporate Iterative Learning Control With Genetic Algorithm (GA) To Optimize The Learning Parameters And A Feedforward Controller Based On Input Shaping Techniques For Control Of Vibration (Flexible Motion) Of The System. …”
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A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem
Published 2018“…In this paper, we propose a new hybrid Q-learning sine-cosine- based strategy, called the Q-learning sine-cosine algorithm (QLSCA). …”
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Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
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Working Paper -
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Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar
Published 2016“…Several methods have been developed in both spatial and frequency domains to deblur Gaussian and motion blurred images by using iterative methods to estimate the blur parameters. …”
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Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
Published 2009“…By using EMRAN (Extended Minimal Resource Allocation Algorithm) to train the Radial Basis Funciton (RBF)Network, the PID controller can learn, adapt and change its parameters based on the condition of the controlled-objectin real-time. …”
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Proceeding Paper -
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Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia
Published 2023“…Agricultural robots; Ammonia; Forecasting; Lakes; Learning algorithms; Machine learning; Motion estimation; Multilayer neural networks; Rivers; Sensitivity analysis; Water quality; Agricultural activities; Health condition; Movement control; Multi layer perceptron; Reconnaissance surveys; Three parameters; Water quality indexes; World Health Organization; Quality control; COVID-19; lake water; river water; spatiotemporal analysis; surface water; water quality; World Health Organization; Malaysia; Penang; Putrajaya; Putrajaya Lake; West Malaysia…”
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Utilizing P-Type ILA in tuning Hybrid PID Controller for Double Link Flexible Robotic Manipulator
Published 2018“…In the controllers’ development, this research focuses on adaptive controller. 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 -
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Utilizing P-Type ILA in tuning Hybrid PID Controller for Double Link Flexible Robotic Manipulator
Published 2018“…In the controllers' development, this research focuses on adaptive controller. 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 -
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Controlling the non-parametric modeling of Double Link Flexible Robotic Manipulator using Hybrid PID tuned by PType ILA
Published 2018“…In the controllers’ development, this research focuses on selftuning controller. P-Type iterative learning algorithm (ILA) control theme was enforced to adapt the controller parameters to fulfill the required performances once there is changes to the system. …”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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