Search Results - data distribution ((using algorithm) OR (means algorithm))

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”

Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data by Rostami, Mohammad

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Power-efficient wireless coverage using minimum number of uavs by Sawalmeh A., Othman N.S., Liu G., Khreishah A., Alenezi A., Alanazi A.

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…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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Replica Creation Algorithm for Data Grids by Madi, Mohammed Kamel

“…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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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

“…Weibull distributions can be used to examine investment behaviour due to their flexibility to be transformed into other types of distribution. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…Yet, the LDA cannot be implemented directly on unsupervised data as it requires the presence of class labels to train the algorithm. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

“…The AADS algorithm uses evolving methods which are evolving autonomous data partitioning (eADP) and non-weighted frequency equations. …”
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Locating fault using voltage sags profile for underground distribution system by Mokhlis, Hazlie, Li, H.Y., Bakar, A.H.A., Mohamad, H.

“…The proposed algorithm uses voltage sags profile as a means to locate fault. …”
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Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

“…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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A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Wendy Ling, Shinyie, Tan Lit, Ken

“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), Hartigan- Wong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Zun, Liang Chuan, Wan Yusof, Wan Nur Syahidah, Senawi, Azlyna, Mohd Akramin, Mohd Romlay, Soo, Fen Fam, Wendy, Ling Shinyie, Tan, Lit Ken

“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), HartiganWong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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An improvement on the valiantbrebner hypercube data broadcasting technique / Nasaruddin Zenon by Zenon, Nasaruddin

“…In section 1.0 a description of the hypercube topological characteristics will be given which can be used to modify the algorithm. Section 2.0 provides the description of the Valiant and Brebner (V-B) algorithm. …”
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Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks by Azam Khalili, Vahid Vahidpour, Amir Rastegarnia, Ali Farzamnia, Teo, Kenneth Tze Kin, Saeid Sanei

“…The incremental least-mean-square (ILMS) algorithm is a useful method to perform distributed adaptation and learning in Hamiltonian networks. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…In this respect, we propose to incorporate our proposed DRBLTS in the bootstrap model selection technique. We also proposed to use an alternative robust location and scale estimates which are less affected by outliers instead of using the classical mean and classical standard deviation. …”
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Final exam question paper data encryption and decryption using advance encryption standard / Khairul Nashran Nazari by Nazari, Khairul Nashran

“…AES is a data encryption technique that exist in the world with as currently the most secured algorithms. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Shinyie, Wendy Ling, Ken, Tan Lit

“…The results of the analysis show that Forgy K-means non-hierarchical (FKNH), HartiganWong K-means non-hierarchical (HKNH), and Lloyd K-means non-hierarchical (LKNH) regionalisation algorithms are superior to other automated agglomerative hierarchical and non-hierarchical regionalisation algorithms. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft by Salvinder Singh, Karam Singh, Shahrum, Abdullah, Nik Abdullah, Nik Mohamed

“…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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