Search Results - probable distribution ((_ algorithm) OR (modified algorithm))
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…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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Thesis -
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Winsorize tree algorithm for handling outliers in classification problem
Published 2016“…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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Stochastic And Modified Sequent Peak Algorithm For Reservoir Planning Analysis Considering Performance Indices
Published 2016“…In the next stage, the modified Sequent Peak Algorithm (SPA) is employed for the Storage-yield planning analysis of reservoir systems at different demands, reliability and vulnerability performance metrics employing the synthetic streamflow data. …”
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4
An improvement on the valiantbrebner hypercube data broadcasting technique / Nasaruddin Zenon
Published 1990“…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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Application of Mellin-Kamal transformation in EL Gamal Ciphertext Cryptosystem / Nurul Syazwani Husairi and Nurul Aqilah Mohd Fauzi
Published 2023“…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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Student Project -
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates
Published 2017“…Kumaraswamy distribution has a closed form of probability density function (PDF) and CDF, which makes it tractable. …”
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Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong
Published 2014“…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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Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks
Published 2017“…We use concepts from matching theory, specifically the stable marriage problem, to formulate the interactions among the cogni- tive radio users as a matching game for collaborative distributed spectrum sensing under target detection probability constraint. …”
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An empirical study of density and distribution functions for ant swarm optimized rough reducts
Published 2011“…To describe relative probability of different random variables, Probability Density Function (PDF) and the Cumulative Density Function (CDF) are capable to specify its own characterization of Gaussian distributions. …”
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Book Chapter -
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
Published 2015“…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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Thesis -
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Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory
Published 2017“…Specifically, the stable marriage problem is used to formulate the interactions among the cognitive radio users as a matching game for collaborative distributed spectrum sensing under target detection probability constraint. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023“…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”
Conference Paper -
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Robust Kernel Density Function Estimation
Published 2010“…To remedy this problem, Kim and Scott (2008) proposed an Iteratively Re-weighted Least Squares (IRWLS) algorithm for Robust Kernel Density Estimation (RKDE). …”
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Fault section detection and location on distribution network using analytical voltage sags database
Published 2006“…By doing this all the possible sections due to the fault can be selected. Finally, the most probable faulty section is identified using probability approach.This paper presents the implemented algorithms and the test of the algorithms on typical distribution networks. …”
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Conference or Workshop Item -
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Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search
Published 2008“…The relative performance of the proposed HGATS is compared to each GA and TS alone, on a set of randomly generated problems following some discrete probability distributions. The problem data are inspired by real case of VRPSD in waste collection. …”
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The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer
Published 2015“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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Monograph -
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Statistical selection algorithm for peer-to-peer system
Published 2008“…However, this algorithm has a high probability of failure. A few improvements have been done to this original algorithm. …”
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Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat
Published 2020“…The activation function in this neural network model then estimated using genetic algorithms. Determination of the best factor is carried out in a genetic algorithm by combining several parameters of the crossover probability (Pc) and mutation probability (Pm). …”
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