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1
Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…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. …”
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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…In this paper, a parallel deep learning-based community detection method in large complex networks (CNs) is proposed. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
4
Grid portal technology for web based education of parallel computing courses, applications and researches
Published 2009“…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.
Published 2001“…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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6
Agents for Fuzzy Indices of Reliability Power System with Uncertainty Using Monte Carlo Algorithm
Published 2014“…Two agents are developed based on fuzzy parameters of Monte Carlo i.e. current with its means and variances; the other agent is the probability of outage capacity for each state. …”
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7
Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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8
A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Published 2013“…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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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…Directional statistics is a branch of statistics which deal with the data in angle form in which the method of analysis is different from linear data. For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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10
An improvement on the valiantbrebner hypercube data broadcasting technique / Nasaruddin Zenon
Published 1990“…The writer tries to improve this algorithm because it is the only known algorithm for the hypercube machine that has the probability of more than i (log n) processors will simultaneously try to transmit a message through a given processor decreases exponentially with i. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…In recent years, photovoltaic distributed generation (PVDG) has seen rapid growth due to its benefits in supporting the power system network, enhancing the transmission and distribution of power, and minimizing power congestion. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…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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13
Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia
Published 2024“…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. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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15
Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…Although the number of these target-like data is small, they may cause false alarm and perturb the target detection. K-distribution is known as the best fit probability density function for the radar sea clutter. …”
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Statistical modeling of the electromechanical behaviour of BI-2223 composite wires
Published 2024text::Final Year Project -
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A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties
Published 2024“…This study proposes a new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping (MVMO-SH) optimisation for planning Photovoltaic Distributed Generation (PVDG) in the urban Radial Distribution Network (RDN). …”
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
Published 2015“…The first agent employed fuzzy parameters such as, current with its means and variances and the second agent is the probability of outage capacity for each state. …”
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19
Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…Furthermore, the probabilistic boundaries at minimum, mean, and maximum of power loss reduction, penetration levels, and voltage profiles have shown better performances when the central distributed generation topology is applied.…”
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20
Malay continuous speech recognition using continuous density hidden Markov model
Published 2007“…With their efficient training algorithm (Baum-Welch and Viterbi/Segmental K-mean) and recognition algorithm (Viterbi), as well as it’s modeling flexibility in model topology, observation probability distribution, representation of speech unit and other knowledge sources, HMM has been successfully applied in solving various tasks in this thesis. …”
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