Search Results - (( data visualization study algorithm ) OR ( data optimization means algorithm ))

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  1. 1
    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure

    Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

    Published 2019
    “…This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. …”
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  2. 2
    Customer mobile behavioral segmentation and analysis in telecom using machine learning

    Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

    Published 2021
    “…The study applied analytic pipeline that involved five stages i.e. data generation, data pre-processing, data clustering, clusters analysis, and data visualization. …”
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  3. 3
    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning

    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

    Published 2023
    “…This research contributes novel insights into the application of clustering algorithms in banking, proposing pragmatic solutions for efficient data analysis and campaign optimization. …”
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  4. 4
    A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem

    A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

    Published 2009
    “…All algorithms are coded in ANSI-C using Microsoft Visual C++ 6.0 as the compiler, and run on a Pentium 4, 2.0 GHz computer with 2.0 GB RAM. …”
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  5. 5
    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…These methods present a robust system that enables fully automated identification and removal of artifacts from EEG signals, without the need of visual inspection or arbitrary thresholding. The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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  6. 6
    Mean of correlation method for optimization of affective states detection in children

    Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

    Published 2018
    “…At the moment, most of the studies on classification of affective states for children focus on visual observations and physiological cues, where all data collection for measuring physiological signals are contact-based and invasive. …”
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  7. 7
    Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor

    Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor by Terence Jerome Daim

    Published 2023
    “…First objective is to determine the optimal setup for IR-UWB radar sensor data acquisition, considering factors such as sensor placement and configuration. …”
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  8. 8
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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  9. 9
    A near-optimal centroids initialization in K-means algorithm using bees algorithm

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…This creates problem for novice users especially to those who have no or little knowledge on the data.Trial-error attempt might be one of the possible preference to deal with this issue.In this paper, an optimization algorithm inspired from the bees foraging activities is used to locate near-optimal centroid of a given data set.Result shows that propose approached prove it robustness and competence in finding a near optimal centroid on both synthetic and real data sets.…”
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  10. 10
    Spatial domain image steganography based on right most digit replacement and parity bit differencing / Mehdi Hussain

    Spatial domain image steganography based on right most digit replacement and parity bit differencing / Mehdi Hussain by Mehdi , Hussain

    Published 2017
    “…However, most of the existing embedding algorithms are incapable of overcoming the adverse effects of the challenges simultaneously. …”
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  11. 11
    Data clustering using the bees algorithm

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…K-means clustering involves search and optimization. …”
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  12. 12
    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem

    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem by S. W. Su, Stephanie, Kek, Sie Long

    Published 2021
    “…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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  13. 13
    Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process

    Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process by Kong, Hong Shim

    Published 2008
    “…This would simplify the task of obtaining fuzzy rules from machining data. Beside that, the model is compared with other artificial intelligence approaches, such as fuzzy logic, neural network and genetic algorithm. …”
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  14. 14
    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction

    Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction by Tan, James Yiaw Beng

    Published 2012
    “…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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  15. 15
    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…SGD uses random or batch data sets to compute gradient in solving optimization problems. …”
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  16. 16
    Clustering chemical data set using particle swarm optimization based algorithm

    Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

    Published 2008
    “…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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  17. 17
    An improved data classification framework based on fractional particle swarm optimization

    An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

    Published 2019
    “…The proposed algorithm is tested and verified for optimization performance comparison on ten benchmark functions against six existing established algorithms in terms of Mean of Error and Standard Deviation values. …”
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  18. 18
    Cluster optimization in VANET using MFO algorithm and K-Means clustering

    Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

    Published 2023
    “…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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  19. 19
    The Development Of System For Algorithms Visualization Using Simjava

    The Development Of System For Algorithms Visualization Using Simjava by Jamil Alsayaydeh, Jamil Abedalrahim, Ahmad Idil, Abdul Rahman, Zainon, Maslan, Aziz, Azwan, Zikri Abadi, Baharudin, Oliinyk, Andrii

    Published 2020
    “…It does not simply fit data to a chart to visualize an algorithm, there is no main data set. …”
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  20. 20
    Discovering optimal clusters using firefly algorithm

    Discovering optimal clusters using firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2016
    “…Existing conventional clustering techniques require a pre-determined number of clusters, unluckily; missing information about real world problem makes it a hard challenge.A new orientation in data clustering is to automatically cluster a given set of items by identifying the appropriate number of clusters and the optimal centre for each cluster.In this paper, we present the WFA_selection algorithm that originates from weight-based firefly algorithm.The newly proposed WFA_selection merges selected clusters in order to produce a better quality of clusters.Experiments utilising the WFA and WFA_selection algorithms were conducted on the 20Newsgroups and Reuters-21578 benchmark dataset and the output were compared against bisect K-means and general stochastic clustering method (GSCM).Results demonstrate that the WFA_selection generates a more robust and compact clusters as compared to the WFA, bisect K-means and GSCM.…”
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