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37 articles for “back-propagation algorithm”
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Calcareous Soil as a Promising Adsorbent to Remove Fluoride from Aqueous Solution: Equilibrium, Kinetic and Thermodynamic Study
Abstract: Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 In this work, the feasibility of employing calcareous soil to remove fluoride ions from its aqueous solutions was investigated under batch mode. The influence of solution pH, sorbent dose, initial fluoride concentration, contact time, stirring rate and temperature on the removal process were investigated. The equilibrium adsorption data were analyzed using Langmuir, Freundlich and Temkin isotherm models. The kinetics of fluoride …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 3, Issue 3, 2012 · pp. 1–21 Read article
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Face Recognition Using Neural Networking Algorithms
Abstract: Face recognition system has become quite popular nowadays. It has gained a good attention in recent few years. Face recognition is practically everywhere, in security system for criminal activities, places like airports and international borders, it is needed for identification of people. In the paper, we discussed about three Neural Networking Algorithms used for FR such as Gabor Filter, Principle Component Analysis with Back Propagation Neural Network and Wavelet Transform …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 23–27 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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Audio-Only Speaker Identification using Principal Component Analysis based Back-Propagation Learning Neural Network in Noisy Environment
Abstract: This paper introduces text dependent speaker identification system on Principal Component Analysis based Back-Propagation learning neural network which deals with detecting a particular speaker from a known populations under noisy environment. For audio pre-processing, ends point detection, silence parts removal, frame segmentation and windowing techniques have been used and wiener filter has been applied to remove the background noise from the audio speech utterances. To reduce the dimension of the …
Published in Current Trends in Signal Processing · Vol. 3, Issue 3, 2013 · pp. 1–10 Read article
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Iris Recognition System Using Principal Component Analysis based Back-Propagation Learning Neural Networks
Abstract: This paper deals with the iris recognition system using Back-Propagation learning neural network algorithm where Principal Component Analysis technique has been used to reduce the dimension of the iris feature vector. Automated iris localization and segmentation methods have applied to effectively isolate the iris region from pupil and sclera. Circular Hogue transform has used to detect the iris/sclera boundary and pupil/iris boundary. To remove the upper and lower eyelids effects …
Published in Current Trends in Information Technology · Vol. 3, Issue 3, 2013 · pp. 5–11 Read article
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Analysis Of Gradient Descent In Back Propagation Neural Network For Maximum And Efficient Utilization
Abstract: The back-propagation is a successfully established algorithm for multi-layered perceptron neural networks, which is usuallywith successfully for tiny network architectures or small tasks. In this paper we have highlighted the important libraries for thepurpose of implementation of neural networks. After that we have given the process of feed forward in neural network and howwe optimize this process by updating the weights by going backward towards the previous layers. The Author …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 1, 2022 · pp. 21–30 Read article
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A Novel Strategy for Weight Initialization in Sigmoidal Feed-forward Artificial Neural Networks
Abstract: In this paper, a novel method of weight initialization is proposed. The proposed method of weight initialization distributes the initial weights and thresholds in such a manner that they lie in different regions of the activation function used at the hidden layer. The proposed method is compared with six other popular weight initialization methods on ten function approximation problems using the RPROP (Resilient Back-propagation) and Levenberg-Marquardt algorithms for training. Two …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 62–75 Read article
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Finding Color Blindness Using Ishihara Algorithm
Abstract: This paper is aimed to develop a back propagation artificial neural network (ANN) model that could distinguish crop plants from weeds. Although only the color indices associated with image pixels were used as inputs, it was assumed that the ANN model could develop the ability to use other information, such as shapes, implicit in these data. The 756x504 pixel images were taken in the field and were then cropped to …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 2, Issue 1, 2015 · pp. 1–14 Read article
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Managing the Resources of LTE Networks using Multi-orthogonal Access based on Deep Learning
Abstract: AbstractOne of the topics discussed in telecommunications systems is joint subcarrier and power allocation in the uplink of an NOMA system that we study. Due to this reason a novel radio resource management framework is presented based on code-domain and a deep learning algorithm for uplink and downlink transmissions, such that the neural network is trained by Bayesian regularization back propagation and the mean squared error )MSE) are the training …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 7, Issue 2, 2020 · pp. 19–26 Read article
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Comparative Analysis of Artificial Intelligence-based MPPT Algorithms for Wind Energy System
Abstract: By extracting maximum possible power from a wind generator system, the efficiency of the system can be increased. Radial basis function (RBF), feed forward back propagation (FFBP) and adaptive neuro-fuzzy inference system (ANFIS) are recognized as the universal estimators. This paper presents a single network based maximum power point tracking (MPPT) of a wind turbine system using these algorithms. The single network based maximum power extraction method is simple and …
Published in Journal of Power Electronics and Power Systems · Vol. 10, Issue 3, 2020 · pp. 7–18 Read article
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Optical Character Recognition Using Back Propagation Neural Network
Abstract: This paper represents an Artificial Neural Network (ANN)-based approach for the recognition of English characters using feed-forward neural network. Noise has been considered as one of the major issues that degrades the performance of character recognition system. Our feed forward network has one input, one hidden, and one output layer. The entire recognition system is divided into two sections, namely training and recognition section. Both the sections include image acquisition, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 11–18 Read article
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Performance Evaluation of PCA Based Back Propagation over PCA Based Euclidian Distance for Video Images
Abstract: Key frame selection aims at reducing amount of data and retrieve information desired from a video. Video summarization aims at reducing the amount of data in order to retrieve information from a video. In this paper, we present an innovative approach for key frame selection; and a face detection and recognition from video sequence. For face detection from video, first we select the key frames and then detect multiple faces …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 1, 2016 · pp. 24–31 Read article
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Leak Location Detection in Underground Pipeline Using Transient Pollutant Propagation Concentration Signature Analysis with Theory of Hypernumbers
Abstract: The paper introduces a new analytical method of detecting leakage locations in underground pipe systems. For the first time, the phenomenon of pollutant backflush through leaks in liquid transport systems is used for algorithmic leak location identification. The paper compares the proposed concept with known monitoring methods. The theoretical analysis of the method's capability to increase leak localization distance and detect the location of tiny holes in pipelines is provided. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 13–22 Read article
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Perceptual Features Based Continuous Speech Recognition in Additive Noise Environment Using Various Modelling Techniques
Abstract: The main objective of this paper is to discuss the effectiveness of Mel frequency perceptual features and the noise reduction technique in evaluating the performance of multi speaker independent continuous speech recognition system in additive noise environment by using various modelling techniques. The proposed perceptual features are captured and trained using clustering technique, GMM, continuous density HMM and back propagation neural networks. Speech recognition system is evaluated on clean and …
Published in Current Trends in Signal Processing · Vol. 2, Issue 1-3, 2012 · pp. 67–81 Read article
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An Approach of Multi-modal Biometric Iris and Speech based Person Recognition System with Decision Fusion Technique
Abstract: This paper presents a unique approach of multi-modal iris and speech feature based person recognition system. Iris images and speech signals are taken from CASIA iris database and NOIZEUS speech database respectively. Iris features are extracted after applying iris images noise removing and image pre-processing techniques. On the other hand, speech signal noise removing, start-end points detection algorithm, silence parts removal, windowing and feature extraction techniques are applied to extract …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 2, Issue 2, 2015 · pp. 5–10 Read article
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Optimized Receivers for Underwater Visible Light Communication
Abstract: For uses like ocean exploration, environmental monitoring, and underwater data transfer, wireless communication under water is crucial. Conventional acoustic and radio frequency communication methods suffer from low bandwidth, high latency, and severe signal attenuation in underwater environments. With its high data rate and low propagation delay, Visible Light Communication (VLC) provides a promising alternative. In this work, an underwater VLC system is implemented using Light Emitting Diodes (LEDs) with intensity …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
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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