Search Results - (( pattern machine algorithm ) OR ( patterns ((means algorithm) OR (based algorithm)) ))
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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An algorithm for Elliott Waves pattern detection
Published 2018“…All of the fundamental features of an proper Elliott Wave pattern (EW pattern) are reviewed and explained. Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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An algorithm for Elliott Waves pattern detection
Published 2018“…All of the fundamental features of an proper Elliott Wave pattern (EW pattern) are reviewed and explained. Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm
Published 2015“…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Music Recommender System Using Machine Learning Content-Based Filtering Technique
Published 2022“…These algorithms identify hidden patterns or data groupings without the assistance of a human. …”
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Undergraduates Project Papers -
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Single Frame Profilometry With Rapid Phase Demodulation On Colour-Coded Fringes
Published 2019“…Therefore, a corresponding fringe analysis algorithm was developed for De Bruijn colour-coded fringe pattern to circumvent the conventional phase unwrapping techniques which are unreliable and time-consuming. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…Therefore, prediction of laser machining cut quality, namely surface roughness was carried out using machine learning techniques based on Quick Back Propagation Algorithm using ANN. …”
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Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
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User authentication for mobile devices using motion sensors based on Moore’s neighborhood / Muhammad Asyraf Akop
Published 2017“…This is where an algorithm based on Moore’s Neighborhood concept is used to measure the similarity of the current gesture recorded to the real user gesture saved inside the smartphone. …”
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Student Project -
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River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network
Published 2024“…Therefore, it is necessary to precisely estimate how the river flow will alter as a result of changing rainfall patterns. Finding the best value for the hyper-parameters is one of the problems with machine learning algorithms, which have lately been adopted by many academics. …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…For the overall performances which were based on the six data sets, the &-AMH algorithm recorded the highest mean accuracy scores of 0.93 as compared to the other algorithms: the ^-Population (0.91), the &-Modes-RVF (0.81), the New Fuzzy &-Modes (0.80), A:-Modes (0.76), &-Modes-HI (0.76), £-Modes- HII (0.75), Fuzzy £-Modes (0.74) and £-Modes-UAVM (0.70). …”
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Cabbage disease detection system using k-NN algorithm
Published 2022“…Identification of plant diseases is key to avoiding losses in agricultural yields and product quantities. Plant disease study means the study of disease patterns that can be visually seen on plants. …”
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Academic Exercise -
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A framework for predicting oil-palm yield from climate data
Published 2006“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering the data. …”
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Conference or Workshop Item -
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