Search Results - (( developing network training algorithm ) OR ( java implementation based algorithm ))
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1
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…The computational tool, Matlab was proposed for classification with Levenberg-Marquardt training algorithm, which provided faster rate of convergence for feed forward network. …”
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Thesis -
2
RSA Encryption & Decryption using JAVA
Published 2006“…Today, with online marketing, banking, healthcare and other services, even the average householder is aware of encryption. The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
3
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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4
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…The main challenges of implementing ANPR algorithm on mobile phone are how to produce a higher coding efficiency, lower computational complexity, and higher scalability. …”
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Book -
5
Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks
Published 2022“…Following the best selection of neural network algorithm, BR algorithm is further trained using 50-70% training with 10-28 hidden neurons. …”
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Monograph -
6
Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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7
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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8
Café Web Based System Using Priority Scheduling Approach
Published 2017“…The priority scheduling algorithm is based on Control Processing Unit scheduling algorithm where it has a priority to execute tasks. …”
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Conference or Workshop Item -
9
Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection
Published 2024“…There are multiple techniques in training the network, one of which is training with metaheuristic algorithms. …”
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Article -
10
PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…ANN can be categorized into three main types: single layer, recurrent network and multilayer feed-forward network. In multilayer feed-forward ANN, the actual performance is highly dependent on the selection of architecture and training parameters. …”
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Thesis -
11
E-Handrawn Calculator
Published 2008“…The purpose of this project is to demonstrate an application of back-propagation network (comparison of training their algorithms and transfer function) in order to developing e-Hand-Drawn Calculator. …”
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Final Year Project -
12
Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…On the whole, BR algorithm with 60% training and 30 hidden nodes were successfully developed for BOD analysis, meanwhile, 70% training for COD analysis with the regression values of 0.9978 and 0.9976 respectively. …”
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Monograph -
13
Logic Programming In Radial Basis Function Neural Networks
Published 2013“…The analysis revealed that performance of particle swarm optimization algorithm and Prey predator algorithm are better to use in training the networks. …”
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Thesis -
14
Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…Bat algorithm is an optimizer tool and developed using of echolocation characteristics of bats, while the neural network is learning methods that approach the human brain using artificial neurons. …”
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Article -
15
Pairwise testing tools based on hill climbing algorithm (PTCA)
Published 2014“…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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Undergraduates Project Papers -
16
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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Article -
17
Java based expert system for selection of natural fibre composite materials
Published 2013“…In this paper, we develop a technology for the materials selection system using Java based expert system. The weighted-range method (WRM) was implemented to identify the range value and to scrutinise the candidate materials. …”
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Article -
18
Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…Bat algorithm is an optimizer tool and developed using of echolocation characteristics of bats, while the neural network is learning methods that approach the human brain using artificial neurons. …”
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Thesis -
19
Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets
Published 2014“…The ANN training data were obtained from Open-ended Coaxial Probe (OCP) microwave measurements and the quasi-static admittance model, the ANN was trained with four different training algorithms: Levenberg Marquardt (LM) algorithm, Gradient Descent with Momentum (GDM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA) algorithm. …”
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Article -
20
Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…ANN is a computer-based simulation of the living nervous system which works quite differently from conventional programming. The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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