Search Results - (( data distribution means algorithm ) OR ( re evaluation tool algorithm ))
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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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State-Aware re-configuration model for multi-radio wireless Mesh Networks
Published 2017“…The ns-2 simulator is used as simulation tool and various metrics are evaluated. These metrics include channel-link utilization, channel re-assignment cost, re-routing cost, throughput, and delay. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Sustainable renewable energy resources utilization in rural areas
Published 2016“…The developed optimization model could be used as a decision making support tool to evaluate and select various alternative renewable energy resources and to determine the optimal locations for developing these resources. …”
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Sustainable renewable energy resources utilization in rural areas
Published 2016“…The developed optimization model could be used as a decision making support tool to evaluate and select various alternative renewable energy resources and to determine the optimal locations for developing these resources. …”
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Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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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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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…Overall, the k-means outperforms the Gaussian mixture distribution in selecting smaller feature subsets. …”
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Book Chapter -
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A dynamic replication aware load balanced scheduling for data grids in distributed environments of internet of things
Published 2018“…Grid computing is a powerful distributed and scalable computing infrastructure that deals with massive data-intensive applications. …”
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Replica Creation Algorithm for Data Grids
Published 2012“…This thesis presents a new replication algorithm that improves data access performance in data grids by distributing relevant data copies around the grid. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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TDMA scheduling analysis of energy consumption for iot wireless sensor network
Published 2019“…Network Simulator NS2.35 is the tool used for simulation of the project. For the evaluation of the performance the parameters used are Energy consumption (Joules). …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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Dynamic replication aware load blanced scheduling in distributed environment / Said Bakhshad
Published 2018“…Grid computing is an effective distributed and adaptable processing network that manages a huge number of data applications. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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Development of an effective clustering algorithm for older fallers
Published 2022“…The proposed algorithm was developed through the stages of: data pre-processing, feature identification and extraction with either t-Distributed Stochastic Neighbour Embedding (t-SNE) or principal component analysis (PCA)), clustering (K-means clustering, Hierarchical clustering, and Fuzzy C-means clustering) and characteristics interpretation with statistical analysis. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…A key property of our model is that the distributions of the observed count data are independent, conditional on the latent process, although the observations are correlated marginally. …”
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Locating fault using voltage sags profile for underground distribution system
Published 2010“…This paper presents an alternative fault location algorithm to estimate short-circuit faults location in electrical distribution networks using only voltage sags data. …”
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