Search Results - (( data distribution based algorithm ) OR ( based education a algorithm ))
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1
Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat
Published 2020“…Based on the initial study conducted, there are 6 factors that have the potential to influence the number of DHF cases in an area, namely temperature (X1), rainfall (X2), population density (X3), altitude (X4), distribution of males (X5), and distribution of education level (X6). …”
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2
Density based subspace clustering: a case study on perception of the required skill
Published 2014“…The main idea based on the density in each cluster is that any data has the minimum number of neighbouring data, where data density must be more than a certain threshold. …”
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3
Density subspace clustering: a case study on perception of the required skill
Published 2014“…The main idea based on the density in each cluster is that any data has the minimum number of neighbouring data, where data density must be more than a certain threshold. …”
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4
A study on course timetabling for FCSIT
Published 2014“…The larger classes will be allocated first due to limited resources on large lecture hall. Timetable based on real data from SEM 1 2011/2013 was generated by this automated algorithm. …”
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Final Year Project Report / IMRAD -
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Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin
Published 2020“…In dealing with ASD students in a classroom, there are several problems faced by educators such as catering the appropriate method for the student’s educational needs in a classroom setting. …”
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6
Parameter estimation of the cure fraction based on BCH model using left-censored data with covariates.
Published 2011“…The analysis is constructed by means of the exponential distribution in the case of left censoring and within the framework of the expectation maximization (EM) algorithm. …”
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7
A bayesian via laplace approximation on log-gamma model with censored data
Published 2016“…Log-gamma distribution is the extension of gamma distribution which is more flexible, versatile and provides a great fit to some skewed and censored data. …”
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Legal Innovation in Religious Courts: The Potential Utilization of Artificial Intelligence (AI) in Resolving Contemporary Cases.
Published 2024“…Religious courts face complex challenges in resolving contemporary cases, such as marital disputes, inheritance distribution, and conflicts in Sharia-based economic matters. …”
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Data discovery algorithm for scientific data grid environment
Published 2005“…In this research work, we present our scientific data grid as a large P2P-based distributed system model. …”
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Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution
Published 2014“…Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. …”
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11
Blockchain-enabled cybersecurity framework for healthcare domain
Published 2025“…This framework revealed the optimal performance in terms of mining health data size, average response time, transaction latency, and throughput for secured block transactions in blockchain networks by doing a simulation-based comparative study with the existing work. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…Complementary K-Means clustering grouped the data into two major clusters, indicating that a clear differentiation between economic-based and entrepreneurship-based courses in terms of student enrolment volume and approval distribution. …”
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Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data
Published 2013“…The main objective is to explore the accuracy of the parameter estimation to the change of priors and compare the results with a classical likelihood-based analysis. Focus is on modelling the extreme data based on block maxima approach using Gumbel distribution. …”
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14
Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…By using MATLAB software, the Open Distribution Fitting application is fitted to the collected data to identifying the best distribution and the results presents GPD shows the highest value for best fitted traffic model. …”
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15
Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…This thesis proposes data-intensive workflow optimization algorithms. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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17
Slice sampler algorithm for generalized pareto distribution
Published 2018“…Based on the results, the slice sampler algorithm provides closer posterior mean values and shorter 95% quantile based credible intervals compared to the Metropolis-Hastings algorithm. …”
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Three phase fault algorithm in distribution system by using database approach and impedance based method
Published 2012“…The comparison is made through proposed algorithm with actual data acquired from the utility board. …”
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Distributed Video Tracking
Published 2018“…The focus of the project will be more on object recognition based on colour and shape features. The first Raspberry Pi will send the data feature of colour and shape to the second or next Raspberry Pi and it will track based on the data received. …”
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Final Year Project -
20
Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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