Search Results - (( java implementation learning algorithm ) OR ( using network modified algorithm ))
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm
Published 2012“…This document is a study about LEACH algorithm where the implementation was done using OMNeT++ network simulator to study the performance of this algorithm in term of network lifetime. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…Two modified algorithms are proposed in this research, which are mixture of the momentum algorithm with different learning rate algorithms. …”
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Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…So, the travelling distance, power consumption and lifetime of the network will be calculated in both cases for original algorithm and modified algorithm, which is a modified deployment algorithm, and compared between them. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. …”
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Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin
Published 2018“…Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the ordinary least squares (LS) estimator in terms of mean squared error (MSE). …”
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Modified Kohonen network algorithm for selection of the initial centres of Gustafson-Kessel algorithm in credit scoring
Published 2017“…To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. …”
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A modified weight optimisation for higher-order neural network in time series prediction
Published 2020“…The MCS-MCMC results is further benchmarked with the standard Multilayer Perceptron, standard Pi-Sigma Neural Network (PSNN), Pi-Sigma Neural Network-Modified Cuckoo Search, Pi-Sigma Neural Network-Markov chain Monté Carlo, standard Functional Link Neural Network (FLNN), Functional Link Neural Network-Modified Cuckoo Search and Functional Link Neural Network-Markov chain Monté Carlo which emphasis in optimising the accuracy rate. …”
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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Published 2013“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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The use of SOM for fingerprint classification
Published 2023“…The concept of 'certainty' is introduced and used in the modified algorithms. Our experiments show improved results with increasing network sizes. …”
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A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification
Published 2010“…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping
Published 2016“…Coastal health of ecosystems can be affected by high concentrations of suspended sediment. In this work, a Modified Hopfield Neural Network Algorithm (MHNNA) was used with remote sensing imagery to classify the total suspended solids (TSS) concentrations in the waters of coastal Langkawi Island, Malaysia. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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