Search Results - (( normal distribution methods 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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Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

“…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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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 by Hassan, Siti Fatimah

“…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

“…Statistical approaches which use the Standard Deviation and conditional Bayesian methods are considered to assign the grades. In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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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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Identification of non-equilibrium growth for bitcoin exchange rate: mathematical derivation method in Islamic financial engineering by Rosbi, Sofian, Abu Bakar, Nashirah

“…Graphical method indicates the first difference of data distribution is a non-normal distribution. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

“…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. Nevertheless, in real situations, many estimates are not normal and the use of bootstrap method is more appropriate as it does not rely on the normality assumption. …”
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Statistical approach on grading the student achievement via normal mixture modeling by Md. Desa, Zairul Nor Deana, Mohamad, Ismail, Mohd. Khalid, Zarina, Md. Zin, Hanafiah

“…Statistical approaches which used the Standard Deviation (GC) and conditional Bayesian methods are considered to assign the grades. In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer by Ahmad, Noor Ashikin

“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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Statistical approach on grading the student achievement via mixture modelling by Md. Desa, Zairul Nor Deana, Mohamad, lsmail

“…In the conditional Bayesian model, we assume the Normal Mixture distribution where the grades are distinctively separated means and proportions of the Normal Mixture distribution. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

“…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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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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Omega grey wolf optimizer (ωGWO) for optimization of overcurrent relays coordination with distributed generation by Noor Zaihan, Jamal

“…The overall protection coordination is thus very complicated and could not be satisfied using the conventional method moreover for the modern distribution system. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

“…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution by Sayed, Amani Idris A

“…It offers greater flexibility compared to the commonly used normal distribution.…”
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Optimal placement and sizing of distributed generation in radial distribution networks using particle swarm optimization and forward backward sweep method by Lawal, Sani Mohammed

“…The proposed PSO algorithm is used to determine optimal placement and size of DG in radial distribution networks, where Forward Backward Sweep Method (FBSM) of distribution load flow analysis was used, to determine the actual power loss in the system. …”
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Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

“…The entropy increased and came close to the normal traffic entropy. The proposed method in this project was able to detect and mitigate the attack effectively in its early stages before the intensity escalate to a degree that exhausts the controller. …”
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