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An empirical study of density and distribution functions for ant swarm optimized rough reducts
Published 2011“…However, the description and comparison of both functions are very limited. Hence, this paper compares the solution vector of ACO is represented by both density and distribution function to search for a better solution and to specify a probability functions for every particle (ant), and generate components of solution vector, which satisfy Gaussian distributions. …”
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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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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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A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts
Published 2011“…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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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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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…A Monte Carlo simulation technique is examined and employed to overcome the computational issues arising from the intractability of the probability mass function of some mixed Poisson distributions. …”
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8
Cash-flow analysis of a wind turbine operator
Published 2023“…The intermittent characteristics of wind energy seriously affect the reliability and output power of wind turbine generator (WTG). The paper outlines a method to evaluate the distribution of WTG operator's daily cash-flow by developing an algorithm based on Monte-Carlo technique. …”
Conference Paper -
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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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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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NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment
Published 2024“…A genetic algorithm based on speed invariant and the elite algorithm is proposed to solve the multi-TSP assignment problem. …”
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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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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…Due to difficulties in comparing actions, most existing test generators ignore this step and randomly select an action. However, a randomly selected action has limitations. It does not test most parts of a GUI within a reasonable amount of time and there is a high probability that the same actions are re-selected. …”
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…By adopting a time-varying commercial load, the proposed algorithm was applied on IEEE 33 bus and IEEE 69 bus distribution networks. …”
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…By adopting a time-varying commercial load, the proposed algorithm was applied on IEEE 33 bus and IEEE 69 bus distribution networks. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions
Published 2022“…Due to difficulties in comparing actions, most existing test generators ignore this step and randomly select an action. However, a randomly selected action has limitations. It does not test most parts of a GUI within a reasonable amount of time and there is a high probability that the same actions are re-selected. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…For the load modelling studies, the Monte Carlo simulation is performed in Gaussian PDF to develop a probability model of various types of loads. …”
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Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems
Published 2017“…This paper proposes a methodology for optimal placement and sizing of renewable distributed generation(s) (i.e., wind, solar and biomass) and capacitor banks into a radial distribution system. …”
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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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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…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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