Search Results - (( probable distribution function algorithm ) OR ( variable optimisation based algorithm ))

An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

“…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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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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ENGINEERING DESIGN WITH PSO ALGORITHM by MHD BASIR, SITI NUR HAJAR

“…Creating a PSO algorithm-based infrastructure integrating with the recommendation system will further enhance solution to the design problem. …”
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A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

“…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 by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

“…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 by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

“…The utility function is defined as the average probability of false alarm per cognitive radio user. …”
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Probabilistic evaluation of wind power generation by Razali N.M.M., Misbah M.

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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…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 by Muhamad Razali N.M., Hashim A.H.

“…Two-parameter Weibull type probability density function (PDF) is used to model wind profile at two locations. …”

Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…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 by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

“…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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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 by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

“…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 by Ali, A., Nor, N.M., Ibrahim, T., Romlie, M.F., Bingi, K.

“…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 by Goh, Kwang Yi

“…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 by Shen, jiazheng, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan, Wang, Xinming

“…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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Sizing and placement of solar photovoltaic plants by using time-series historical weather data by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

“…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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Sizing and placement of solar photovoltaic plants by using time-series historical weather data by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

“…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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Analytical Modelling And Efficiency Optimisation Of Permanent Magnet Synchronous Machine Using Particle Swarm Optimisation by Ling, Poh Ping

“…From PSO study, the four machine design variables has been simultaneously optimised and successfully produced parameters for a performance-optimised machine. …”
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Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

“…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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