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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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2
Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…On the other hand, to test the network operational limits when uncertainties of the photovoltaic generation and load demand are included, the probabilistic load flow was simulated using Monte Carlo Simulation method. The beta probability density functions were used to model the photovoltaic generation, while the normal probability density functions were used to model the load demand. …”
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A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties
Published 2024“…The Active Power Loss (APL) index was calculated considering the risk of uncertain photovoltaic generation and urban load distributions. The Monte Carlo Probability Density Function method was initially used to manage uncertainties. …”
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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 -
5
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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10
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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12
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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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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Optimized clustering with modified K-means algorithm
Published 2021“…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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15
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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A near-optimal centroids initialization in K-means algorithm using bees algorithm
Published 2009“…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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Conference or Workshop Item -
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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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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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
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