Search Results - (( parallel optimization means algorithm ) OR ( probable distribution function algorithm ))
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Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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Thesis -
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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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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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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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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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9
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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11
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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Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
Published 2022“…Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. …”
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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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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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15
An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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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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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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Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…Best Hammerstein parallel NN polynomial based model and series-parallel NN polynomial model are 88.75% and 93.9% respectively, for best Hammerstein parallel NN sigmoid based model and series-parallel NN sigmoid based model 78.26% and 95.95% respectively, and for best Hammerstein parallel NN hyperbolic tangent based model and series-parallel NN hyperbolic tangent based model 70.7% and 96.4% respectively. …”
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Dengue outbreak prediction: hybrid meta-heuristic model
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Conference or Workshop Item -
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…To predict the output from the PV modules, 15 years of solar data were modeled with the aid of a beta probability density function. The total energy loss index was formulated as the main objective function, and the optimization problem was solved by mixed integer optimization by using genetic algorithm. …”
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