Search Results - (( parameter estimation clustering algorithm ) OR ( parallel detection method algorithm ))

Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

“…As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…We derive the maximum likelihood estimation of parameters as well as the variance-covariance of parameters. …”
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

“…This paper proposes a novel approach to estimate the parameters of K-distribution, based on fuzzy Gustafson–Kessel clustering and fuzzy Takagi–Sugeno Kang modelling. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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An investigation of structural breaks on spot and futures crude palm oil returns by Zainudin, Rozaimah, Shaharudin, Roselee Shah

“…In contrast to the spot crude palm oil findings, the futures crude palm oil exhibits a lower persistency estimation when structural changes are considered. The results support the importance of structural breaks in this volatility clustering estimation, and failure to do so may lead to bias persistency parameter estimation.…”
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Semiparametric binary model for clustered survival data by Arlin, Rifina, Ibrahim, Noor Akma, Arasan, Jayanthi, Abu Bakar, Mohd Rizam

“…We investigated the effects of the strength of cluster correlation and censoring rates on properties of the parameters estimate. …”
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Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

“…The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

“…In univariate circular data, the presence of outliers is acclaimed will affect the parameter estimates and inferences. This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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Enhanced and effective parallel optical flow method for vehicle detection and tracking by Bhaskar, P.K., Yong, S.-P., Jung, L.T.

“…With a view to do improvements, it is proposed to develop an unique algorithm for vehicle data recognition and tracking using Parallel Optical Flow method based on Lucas-Kanade algorithm. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

“…In the task of individual tree extraction, the point cloud distance discriminant clustering algorithm outperformed the watershed algorithm. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE) by Alias, Norma, Islam, Md. Rajibul

“…The parallel algorithm for the simulation of human tumor growth is a new invention at the present time. …”
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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

“…In this paper, a parallel deep learning-based community detection method in large complex networks (CNs) is proposed. …”
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Skin region detector for real time face detection system by Mohd Mustafah, Yasir, Azman, Amelia Wong

“…In the implementation, the region of interest is detected using two algorithms, running in parallel. …”
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Parallel system for abnormal cell growth prediction based on fast numerical simulation by Alias, Norma, Islam, Md. Rajibul, Shahir, Rosdiana, Hamzah, Norhafizah, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Ludin, Eliana, Azami, Masrin

“…The paper focuses on a numerical method for detecting, visualizing and monitoring abnormal cell growth using large-scale mathematical simulations. …”
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Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach by Marpaung, Faridawaty, Ramadhani, Fanny, Dinata, Dewan

“…The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
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Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using asic design flow: article / Nurzaima Mahmod by Mahmod, Nurzaima

“…The scope of this paper is to optimize the DNA sequences alignment on the matrix rilling module by implementing a parallel method of the Smith-Waterman algorithm. This method provides magnificent speed up over than traditional sequential implementation methods while it sensitivity detection is still remained. …”
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Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

“…Furthermore, colour threshold analysis and edge detection algorithms are redesigned exclusively to refine the two-dimensional coefficients into a more meaningful low-level representation. …”
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