Search Results - (( property distribution function algorithm ) OR ( parallel distributed learning 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.

“…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. …”

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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Grid portal technology for web based education of parallel computing courses, applications and researches by Alias, Norma, Islam, Md. Rajibul, Mydin, Suhaimi, Hamzah, Norhafiza, Safiza Abd. Ghaffar, Zarith, Satam, Noriza, Darwis, Roziha

“…This paper proposes the web service education technology for postgraduate parallel computing course, e-learning students, real-time solutions and for supervising projects related to the application of parallel computing, that focuses on the fundamental principles to parallel computer architecture, multimedia, communication cost, master-worker model, parallel algorithm, web services and performance evaluations. …”
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Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath. by Hasan, Nurul

“…For commercial CFD packages, in many cases the solution algorithms are black boxes, even though parallel computing helps in many cases to overcome the limitations, as shown here. …”
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A new Gompertz-three-parameter-lindley distribution for modeling survival time data by Liang, Fei, Lu, Hezhi, Xi, Yuhang

“…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

“…The first part of the study derives the explicit solutions of the moment properties (mean, variance, skewness and kurtosis) of the distributions together with their respective autocovariance and autocorrelation functions, up to the ith order. …”
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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah

“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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On a new transmuted three-parameter lindley distribution and its applications by Xi, Yuhang, Lu, Hezhi, Liang, Fei

“…The statistical properties of the TTHPLD model, which are based on moments, order statistics, hazard rate functions, reliability functions, and Renyi entropy, have been studied. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Thus, using neural network-based semi-supervised stream data learning is inadequate due to capture the changes in the distribution and characteristics of various classes of data while avoiding the effect of the outdated stored knowledge in neural networks (NN). …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…Also, a one-step iterative algorithm, called expected rank algorithm, is introduced which is more complicated than the estimation-approximation algorithm, but more accurate. …”
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Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia by Adli Zakaria M.N., Ahmed A.N., Abdul Malek M., Birima A.H., Hayet Khan M.M., Sherif M., Elshafie A.

“…Even though the lowest reported performance was reported by the XGBoost, it is the faster of the three algorithms due to its advanced parallel processing capabilities and distributed computing architecture. …”

Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…Some of the theoretical properties of the distributions are derived and the distributions' characteristics are studied. …”
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A Novel Approach Of Groebner Bases Computation For Safety Analysis Of Distributed Discrete Controllers by Alwi @ Suhaimi, Saifulza, Salleh, Mohd Rizal, Jaafar, Hazriq Izzuan, Ab Ghani, Mohd Ruddin, Md Fauadi, Muhammad Hafidz Fazli

“…One of the favorite topic is the formal verification via model checking, which is to verify whether a mathematical model of a system meets the formal specification that describes the property to be checked. In this research, our main objective is to generate a new model checking computation method based on Groebner bases algorithm for safety property analysis of distributed discrete controllers. …”
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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

“…However, simultaneously estimating all three parameters (shape, scale, and growth) through the maximum-likelihood function is computationally complex. Alternative approaches such as the Simulated Annealing (SA) algorithm, which maximizes the log-likelihood function, and Bayesian MCMC estimation are considered. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

“…Then, the proposed BAGD algorithm is frnther hybridized with Simulated Annealing (SA) and Genetic Algorithm (GA) to perform two stage optimization in which the former algorithm finds the optimal solution and the latter algorithm starts from where the first one is converged. …”
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A New Cryptosystem Based on Decimal Numbers and Nonlinear Function by Alfaris, Rand Qusay

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High performance visualization of human tumor growth software by Alias, Norma, Mohd. Said, Norfarizan, Khalid, Siti Nur Hidayah, Sin, Dolly Tien Ching, Phang, Tau Ing

“…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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Enhanced Automated Framework For Cattle Tracking And Classification by Williams, Bello Rotimi

“…Mean-shift strength is its sensitivity to object’s movement and colour distribution by using similarity function but, with inability to track object’s non-linear movement and full occlusion as its weakness.…”
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