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8 articles for “BP (back-propagation)”
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Mechatronics Robot Navigation using Machine Learning through Prolog Programming Language
Abstract: A basic decision-making system is developed in this paper using Neural Network in Machine learningto explore a robot in concealed condition. The robot can move out of explicit labyrinths effectivelythrough modifying its bearing and speed persistently via the neural system model for machinelearning. Over the past several years, navigation tasks for mobile robots have been widely studied.There have been many attempts to introduce the usage of machine learning algorithms. Excellentperformance …
Published in Journal of Mechatronics and Automation · Vol. 8, Issue 1, 2021 · pp. 39–47 Read article
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Power Estimation for VLSI Circuits Using Neural Networks
Abstract: Neural network based VLSI power estimation is done which estimates power in VLSI circuits from its input/output and gate information, without simulation and analysis of its detail structure and the interconnections.Artificial neural network is created which helps in estimation of power. Power estimation results from the [2] [3]are used as the training vector for the network .The network is trained using Back-propagation algorithm. Asimple recurrent network is also introduced called …
Published in Journal of VLSI Design Tools and Technology · Vol. 1, Issue 1-2-3, 2011 · pp. 45–56 Read article
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Simulation of Neural Network based PID Controller for Pressure Process
Abstract: This paper provides a Neural Network PID controller based on Back Propagation (BP) algorithm applied to pressure control in a tank. The controller has many advantages like that more convenient in parameter regulating, better robust. Neural network is to adjust the parameters of PID controller based on the operational status of the system, to achieve a better performance, making the output of the output neurons corresponding to the three adjustable …
Published in Journal of Control & Instrumentation · Vol. 4, Issue 1, 2013 · pp. 23–27 Read article
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Detection of Bus Driver Fatigue Based on Robust Visual Analysis of Eye State and Blowing an Alarm
Abstract: AbstractDriver's deficiency is one of the significant purposes behind car crashes, especially for drivers of wide vehicles, (for example, transports and overwhelming trucks) in perspective of conceded driving periods and fatigue in working conditions. In this paper, we propose a dream based exhaustion recognizing confirmation structure for transport driver watching, which is clear and flexible for sending in transports and critical vehicles. The structure contains modules of head-bear unmistakable evidence, …
Published in Current Trends in Signal Processing · Vol. 8, Issue 2, 2018 · pp. 34–43 Read article
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Prediction of shear strength of reinforced concrete beams using Artificial Neural Network and evaluated by Finite Element Software
Abstract: ABSTRACTIn this paper, the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference Framework (ANFIS) are utilized to foresee the shear quality of Reinforced Concrete (RC) shafts, and the models are contrasted and American Concrete Institute (ACI) and Iranian Concrete Institute (ICI) observational codes. The ANN display, with Multi-Layer Perceptron (MLP), utilizing a Back-Propagation (BP) algorithm, is utilizedto foresee the shear quality of RC pillars. Six vital parameters are chosen …
Published in Journal of Construction Engineering, Technology & Management · Vol. 8, Issue 1, 2018 · pp. 34–42 Read article
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Nonlinear Semiconductor Device Modeling using Neural Networks
Abstract: This paper describes the nonlinear semiconductor (transistor) of small and large signal modeling using a single neural network. Multilayer perceptron (MLP) with back-propagation (BP) learning is adopted in this work to model the drain current (ID) and the transconductance (gm) of the transistor. MLP modeling performance in terms of mean square error (MSE) and complexity of the network are illustrated briefly. Artificial neural network (ANN) model outcome for nonlinear function …
Published in Journal of VLSI Design Tools and Technology · Vol. 4, Issue 3, 2014 · pp. 1–6 Read article
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Speed Estimator for Sensorless Field-Oriented Control Induction Motor Drive Using Intelligent Neural Networks
Abstract: This paper presents a novel approach to the field-oriented control (FOC) of induction motor drives. It discusses the introduction of artificial neural networks (ANNs) for decoupling control of induction motors using FOC principles. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Matlab/Simulink. Simulation result shows a good performance of speed estimator. Simulation results …
Published in Journal of Control & Instrumentation · Vol. 6, Issue 3, 2015 · pp. 42–49 Read article
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Bearing Defect Diagnosis: An Approach for Manufacturing Industries Using Wavelet Transform Based Features
Abstract: To maintain reliability in the manufacturing units, industries have concentrated their attention on the condition based maintenance. Fault detection and diagnosis are the two of three condition based maintenance mainstays. Bearing is one of the most important and essential components of the rotating machines. Hence, the researchers have shown their interest in bearing fault detection and diagnosis from the last few years. They mainly use bearing vibration as fault characteristics …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 1, 2017 · pp. 15–21 Read article