Search Results - (( probable distribution modified algorithm ) OR ( parallel distribution mining algorithm ))

Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

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Winsorize tree algorithm for handling outliers in classification problem by Ch’ng, Chee Keong

“…This study proposes a modified classification tree algorithm called Winsorize tree based on the distribution of classes in the training dataset. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. The higher level priority agreements give a higher or equal probability than the lower level, this technique is perfect at a core router by scheduling algorithm. …”
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Stochastic And Modified Sequent Peak Algorithm For Reservoir Planning Analysis Considering Performance Indices by Oskoui, Issa Saket

“…The tests are implemented for testing consistency, stationarity, randomness and determining the most appropriate probability distribution function of the historical data. …”
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Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

“…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. …”
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

“…Kumaraswamy distribution has a closed form of probability density function (PDF) and CDF, which makes it tractable. …”
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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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Modification of fractal algorithm for oil spill detection from RADARSAT-1 SAR data by Marghany, Maged, Cracknell, Arthur P., Hashim, Mazlan

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Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution by Salih Al-Badri, Qussay Abbas

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Application of Mellin-Kamal transformation in EL Gamal Ciphertext Cryptosystem / Nurul Syazwani Husairi and Nurul Aqilah Mohd Fauzi by Husairi, Nurul Syazwani, Mohd Fauzi, Nurul Aqilah

“…So, this study contributed to show a complete calculation and working to assist other future researchers know the complete step of the proposed scheme and reduce the probability of middle attackers and strengthen the existing algorithm with several cryptosystem integration. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

“…The probability agent is to determine the capacity in service while a fuzzy model agent is to estimate the operation or failure probability. …”
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Robust Kernel Density Function Estimation by Dadkhah, Kourosh

“…The statement of Chandola et al. (2009) that the normal (clean) data appear in high probability area of stochastic model, while the outliers appear in low probability area of stochastic model, has motivated us to develop RDWF. …”
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Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong by Karoon, Suksonghong

“…The superiority of this method is its ability to generate a set of MVS efficient portfolios within a single run of algorithm. The non-dominated sorting genetic algorithm II (NSGA-II), the improved strength Pareto evolutionary algorithm II (SPEA-II), and the compressed objective genetic algorithm II (COGA-II) were applied. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

“…An alternative way to estimate the coefficients of MHTan is through maximum likelihood estimation (MLE) and the probability density function of wind speed. In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. …”
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