Search Results - (( initial solution method algorithm ) OR ( probable distribution function 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“…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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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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A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts
Published 2011“…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (ant) survival behavior, depict the common characteristics of both algorithms. Solution vector of ACO is presented by implementing density and distribution function to search for a better solution and to specify a probability functions for every particle (ant). …”
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Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks
Published 2017“…The utility function is defined as the average probability of false alarm per cognitive radio user. …”
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Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory
Published 2017“…The utility function is defined as the average probability of false alarm per cognitive radio user. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…The probability function of the counts is often complicated thus a method using numerical Laplace transform inversion for computing the probabilities and the renewal function is proposed. …”
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Cash-flow analysis of a wind turbine operator
Published 2023“…Two-parameter Weibull type probability density function (PDF) is used to model wind profile at two locations. …”
Conference Paper -
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In addition, experiments prove that incremental genetic-based clustering ensemble algorithm speed up to converge into an optimal clustering solution, where pattern ensemble learning method and the cluster partitions produced by the threshold fuzzy c-means clustering algorithm are employed as recombination operator and initial population, respectively.…”
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Multistage optimal homotopy asymptotic method for solving initial-value problems
Published 2016“…In this paper, a new approximate analytical algorithm namely multistage optimal homotopy asymptotic method (MOHAM) is presented for the first time to obtain approximate analytical solutions for linear, nonlinear and system of initial value problems (IVPs).This algorithm depends on the standard optimal homotopy asymptotic method (OHAM), in which it is treated as an algorithm in a sequence of subinterval. …”
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Combining approximation algorithm with genetic algorithm at the initial population for NP-complete problem
Published 2018“…In Genetic Algorithm (GA), the prevalent approach to population initialization are heuristics and randomization. …”
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Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
Published 2011“…Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. …”
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Sizing and Placement of Battery-Sourced Solar Photovoltaic (B-SSPV) Plants in Distribution Networks
Published 2021“…To deal the stochastic behavior of solar irradiance, 15 years of weather data is modeled by using beta probability density function (Beta-PDF). The proposed algorithm is applied on IEEE 33 bus and IEEE 69 bus test distribution networks and optimum results are acquired for different time varying voltage dependent load models. …”
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Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin
Published 2021“…Newton's Method also called the Newton-Raphson method is a recursive algorithm for approximating the root of a differentiable function. …”
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Shooting method with root finding to solve boundary value problems / Aryani Rima Matakim
Published 2025“…This method involves guessing initial conditions and iteratively adjusting them until the solution satisfies the boundary conditions at the other end of the domain. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…The idea was to change the probability distribution over the sequence space. Instead of making purely random selections, the least frequently executed action is selected so that the GUI can be further explored. …”
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Enhancing the RC4 algorithm by eliminating the Initiative Vector (IV) transmission
Published 2025“…This paper introduces an innovative approach to address the vulnerabilities of the RC4 encryption algorithm by employing an Initiative Vector (IV). The proposed method incorporates a lengthy random text without transmitting an initialization vector. …”
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NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment
Published 2024“…The experiment verified that this strategy can approach the optimal solution more closely during the population convergence process, and compared it with traditional Multi TSP algorithms and single function multi-objective Multi TSP algorithms. …”
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