Search Results - (( developing effective training algorithm ) OR ( java visualization based algorithm ))
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1
A performance analysis of association rule mining algorithms
Published 2016“…The results of the CPU profiler of Java VisualVM showed that Binary-Based algorithm performs better than Eclat algorithm in-terms of both execution times and memory usage. …”
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2
Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin
Published 2019“…D3.js is used as a technology to visualize the result in interactive form or dynamic visualization which is a JavaScript library and Python is a language to program the system. …”
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3
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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4
Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
Published 2019“…This web based approach will be using Java programming language and Mongo DB (NoSQL database) to improve the retrieval performance by 80%, precision of the search result of the bibliographic data by omitting non-significance papers and visualizing a clearer network diagram using centrality measure for better decision making. …”
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5
Design Of Robot Motion Planning Algorithm For Wall Following Robot
Published 2006“…Navigation algorithms are tested in a variety of differently shaped environments to encourage the development of robust solutions, and reduce the possibility of solutions based on memorization of a fixed set of movements. …”
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Dynamic force-directed graph with weighted nodes for scholar network visualization
Published 2022“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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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
Graphical user interface for bounded-addition fuzzy splicing systems and their variants / Mathuri Selvarajoo ... [et al.]
Published 2023“…In this research, a graphical user interface is developed to generate all the splicing languages generated by bounded-addition fuzzy splicing systems and their variants. An algorithm is developed using JAVA and Visual Studio Code software in order to replace the time-consuming manual computation of the languages generated by bounded-addition fuzzy DNA splicing systems and their variants.…”
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9
Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection
Published 2024“…Metaheuristic algorithms that aim to develop more effective hybrid algorithms by combining the good and successful aspects of more than one algorithm are algorithms inspired by nature. …”
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10
Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding
Published 2007“…Based on Gradient Descent, Conjugate Gradient, Quasi-Newton techniques three different error back propagation algorithms have been developed for use in training two types of neural networks, a single hidden layer network and three hidden layers network. …”
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11
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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Development of classification algorithms of human gait
Published 2022“…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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Final Year Project / Dissertation / Thesis -
14
PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…Despite the fact that ANN has been developing rapidly for many years, there are still some challenges concerning the development of an ANN model that performs effectively for the problem at hand. …”
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15
Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks
Published 2008“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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16
Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks
Published 2009“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
Published 2023Article -
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Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization
Published 2018“…A multilayer feedforward neural network (FFNN) model with 11 different training algorithms is developed for the multivariable nonlinear biopolymerization of polycaprolactone (PCL). …”
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19
Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir
Published 2013“…In this study, sentiment classifier using clonal algorithm selection was developed to categorize sentiment in Malay newspaper (Berita Harian). …”
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20
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Once training samples for each class are collected, the training statistics for each class and band are extracted to select those bands, which are most effective in discriminating each class of information from all others for classification. …”
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