Search Results - (( developing function using algorithm ) OR ( learning implementation some algorithm ))
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1
Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN. …”
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Thesis -
2
PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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Thesis -
3
SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR
Published 2005“…On the other hand, Neural Network has become tremendously popular in the control application due to its ability in adaptive learning and approximating function. By implementing Nyquist Stability Criterion's tuning algorithm with Neural Network, this will definitely enhance the process of tuning the PID controller. …”
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Final Year Project -
4
Development of gender and race recognition system using speech and recognition by using frequency spectrum
Published 2009“…In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. …”
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Learning Object -
5
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…A Wilcoxon Signed-Rank Test was performed to measure the pair-wise statistical performances of the algorithms and from the results, NPO recorded a better statistical performance compared to the other benchmarking algorithms. …”
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Thesis -
6
A novel neuroscience-inspired architecture: for computer vision applications
Published 2016“…Our finding is that there are neuroscience theories that are not utilized in deep learning. Therefore, in this work, a novel model utilizing some of those theories is developed. …”
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Proceeding Paper -
7
Development of an Isolated Digit Speech Recognition Based on Multilayer Perceptron Model
Published 2004“…A Multilayer perceptron (MLP) is a popular NN model used in ASR field. In this study, a MLP with back propagation learning algorithm is implemented to perform the isolated digit speech recognition task for Malay language. …”
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Thesis -
8
Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani
Published 2023“…In the human gait model, three Machine Learning algorithms were used: Gaussian Process Regression, Support Vector Machine, and Decision Tree. …”
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Thesis -
9
An optimized ensemble for predicting reservoir rock properties in petroleum industry
Published 2013“…In the present thesis, we proposed a new method named optimized ensembleto improve the prediction of these reservoirs parameters from well log data with the aid of available core data. Ensemble is a learning algorithm that combines some experts instead of considering a single best expert for the predictions.The thesis proposed anoptimizing method leading to small structure of assemble GA. …”
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Thesis -
10
Multi-Backpropagation network
Published 2002“…In most cases, Neural Network considered large amount of data, as it will be teach to learn or memorize the data as the knowledge. The learning mechanism for Neural Network is its learning algorithm. …”
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Conference or Workshop Item -
11
Three-term backpropagation algorithm for classification problem
Published 2006“…This algorithm utilizes two term parameters which are Learning Rate, α and Momentum Factor,β. …”
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Thesis -
12
Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview
Published 2019“…In this paper, we discuss some important topics such as the general view of reinforcement learning, methods, and algorithms of reinforcement learning and challenges which reinforcement learning is facing. …”
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Conference or Workshop Item -
13
Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview
Published 2019“…In this paper, we discuss some important topics such as the general view of reinforcement learning, methods, and algorithms of reinforcement learning and challenges which reinforcement learning is facing. …”
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Conference or Workshop Item -
14
Motion learning using spatio-temporal neural network
Published 2020“…In this study, learning is implemented on a reward basis without the need for learning targets.The algorithm has shown good potential in learning motion trajectory particularly in noisy and dynamic settings. …”
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Article -
15
Feature selection in intrusion detection, state of the art: A review
Published 2016“…By removing these irrelevant and redundant features accuracy of the learning algorithms can be increased. In this paper implementation of different feature selection techniques have been reviewed. …”
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Article -
16
Detection of surface defects of aluminium extrudants using artificial intelligence
Published 2024“…Although nowadays some manufacturing industries have implemented algorithms to automate the detection of defects, those algorithms face challenges on dealing with noises and lighting changes. …”
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Final Year Project / Dissertation / Thesis -
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Rapid software framework for the implementation of machine learning classification models
Published 2021“…However, to implement a complete machine learning model involves some technical hurdles such as the steep learning curve, the abundance of the programming skills, the complexities of hyper-parameters, and the lack of user friendly platform to be used for the implementation. …”
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Article -
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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Article -
19
Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…In Chapter 2, we propose a new algorithm based on incremental Radial Basis Function Network (RBFN) to accelerate the learning in stream data. …”
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Thesis -
20
A case study on quality of sleep and health using Bayesian networks
Published 2012“…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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