Search Results - (( developing training control algorithm ) OR ( java implication based algorithm ))
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1
Slew Control of Prolate Spinners Using Single Magnetorquer
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Nonlinear modeling and control of a spark ignition engine idle speed / Hazem Mohamed
Published 1998“…Tlie control teclmique used is the fuzzy control. The fuzzy controller is formulated as a radial basis function network trained by the orthogqnalleast squares algorithm to estimate the controller parameters. …”
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3
Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…Due to that, many algorithms employ different training algorithms to guide the network for providing an accurate result with less training and testing error. …”
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4
Brain Machine Interface Controlled Robot Chair
Published 2010“…The BMI controls the joystick of the robot chair using a shared control algorithm. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Using streaming data algorithm for intrusion detection on the vehicular controller area network
Published 2022“…In this paper, the adapted streaming data Isolation Forest (iForestASD) algorithm has been applied to CAN intrusion detection. …”
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Proceeding Paper -
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Speed control of separately excited dc motor using artificial intelligent approach
Published 2013“…A neural network controller with learning technique based on back propagation algorithm is developed. …”
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Development of an Adaptive Algorithm for Solving the Inverse Kinematics Problem for Serial Robot Manipulators
Published 2005“…Experimental results have shown better response for the first configuration network in terms of precision and iteration. The developed approach possesses several distinct advantages; these advantages can be listed as follows :(First) system model does not have to be known at the time of the controller design, (Second) any change in the physical setup of the system such as the addition of a new tool would only involve training and will not require any major system software modifications, and (Third) this scheme would work well in a typical industrial set-up where the controller of a robot could be taught the handful of paths depending on the task assigned to that robot. …”
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10
Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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Enhanced conjugate gradient methods for training MLP-networks
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Conference or Workshop Item -
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Direct neuro-AVC modelling and control strategy for vibration suppression of a flexible plate structure
Published 2003“…A multi layer perceptron (MLP) neuro-controller is designed to characterise the ideal controller characteristic using an online adaptation and training mechanism. …”
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Conference or Workshop Item -
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Flexible Approach for Region of Interest Creation for Shape-Based Matching in Vision System
Published 2009“…The algorithm consists of two phases, the training phase and the recognition phase. …”
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Conference or Workshop Item -
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A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm
Published 2016“…In this paper, as an alternative to previous methods, we propose a new flower pollination algorithm with remarkable balance between consistency and exploration for NN training to build a model for the forecasting of petroleum consumption by the Organization of the Petroleum Exporting Countries (OPEC). …”
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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES
Published 2019“…The implementation of the algorithm consists of three stages which are pre-processing, network training and accuracy evaluation. …”
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Final Year Project -
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud
Published 2022“…However, according to a recent study, ANN algorithms require a huge amount of training data while BPFFNN algorithms only have an average success rate of 70% in recognizing all the characters. …”
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Student Project -
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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control
Published 2019“…Considering both convergence rate and result accuracy simultaneously, the chaotic modified SFS algorithm performs significantly better than other training algorithms. …”
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR
Published 2005“…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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Final Year Project -
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Neural network controller design for position control system improvement
Published 2013“…Neural network controller is implemented using backpropagation training algorithm. …”
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