Search Results - (( parameter estimation mining algorithm ) OR ( parameter optimization technique algorithm ))

Tree-based contrast subspace mining method by Florence Sia Fui Sze

“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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Dynamic investment model for the restructed power market in the presence of wind source by Esfahani, Mohammad Tolou Askari Sedehi

“…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

“…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”

LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

“…In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameters of interest. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm by Gan, Melvin Yeou Wei, Hamzah, Rostam Affendi, Nik Anwar, Nik Syahrim, Herman, Adi Irwan, Jamil Alsayaydeh, Jamil Abedalrahim

“…Then, the research continues to optimize the proposed local based SVDM algorithm through parameters optimization in obtaining the final disparity map. …”
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PID-Controller Tuning of Brushless DC Motor by Using ACO (Ant Colony Optimization) Technique by SIAW KAH , JING

“…ACO algorithm is used as the technique for the PID controller parameters optimization. …”
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OPTIMAL DESIGN OF A BLDC MOTOR BY GENETIC ALGORITHM by OTHMAN, AZRUL HISHAM

“…A constrained optimization on the objective function is performed and optimal parameters are derived. …”
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Artificial intelligence technique in solving nano-process parameter optimization problem / Norlina Mohd Sabri...[et al.] by Mohd Sabri, Norlina, Puteh, Mazidah, Md Sin, Nor Diyana

“…The techniques are Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). …”
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Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

“…This project proposed a new optimization technique based on the ant colony algorithm for solving single-pass turning optimization problems. …”
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Reactive approach for automating exploration and exploitation in ant colony optimization by Allwawi, Rafid Sagban Abbood

“…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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Modeling and Prediction of the mechanical properties of feedstock by cooling-slope casting process using MOJaya algorithm by Mohd Said, Rahaini, Mohamad Kamal, Mohamad Ridzuan, Hussin, Nor Hafizah, Mohamad Suhaili, Sinarwati, Hairol Anuar, Siti Haryanti, Samsudin, Adam, Mohd Yussoff, Nurul Hajar, Winanto, Eko Arip

“…In casting optimization, modeling and optimization of CS parameters have been considered to identify optimal CS parameters that would lead to better feedstock performance. …”
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DESIGN OPTIMIZATION OF A BLDC MOTOR BY GENETIC ALGORITHM AND SIMULATED ANNEALING by K. S. , Rama Rao, Azrul, Hisham Bin Othman

“…The optimal design parameters of the motor derived by GA are compared with those obtained by SA, another stochastic combinatorial optimization technique.…”
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Dynamic social behavior algorithm for real-parameter optimization problems and optimization of hyper beamforming of linear antenna arrays by Prajindra�Sankar K., Kiong T.S., Siaw�Paw J.K.

“…Animals; Antenna arrays; Antennas; Beam forming networks; Beamforming; Behavioral research; Bioinformatics; Evolutionary algorithms; Global optimization; Problem solving; Swarm intelligence; Bio-inspired algorithms; Co-operative behaviors; Global optimization problems; Meta heuristics; Optimization algorithms; Optimization techniques; Real-parameter optimization; Swarm algorithms; Optimization…”

Modeling and Prediction of The Mechanical Properties of Feedstock by Cooling-Slope Casting Process using MOJaya Algorithm by Rahaini, Mohd Said, Mohamad Ridzuan, Mohamad Kamal, Nor Hafizah, Hussin, Sinarwati, Mohamad Suhaili, Siti Haryanti, Hairol Anuar, Adam, Samsuddin, Nurul Hajar, Mohd Yussoff, Eko Arip, Winanto

“…In casting optimization, modeling and optimization of CS parameters have been considered to identify optimal CS parameters that would lead to better feedstock performance. …”
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Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review by Sulaiman, Ahmad S. S., Wayayok, Aimrun, Aziz, Samsuzana A., Yun, Wong Mui, Leifeng, Guo

“…The objective of this review is to analyse the existing literature on algorithm development, parameter optimization techniques, and their application in crop water modelling, specifically emphasizing the importance of crop factors, soil factors, and weather factors. …”
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Overview of PSO for Optimizing Process Parameters of Machining by Norfadzlan, Yusup, Azlan, Mohd Zain, Siti Zaiton, Mohd Hashim

“…In the current trends of optimizing machining process parameters, various evolutionary or meta-heuristic techniques such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), Ant Colony Optimization (ACO) and Artificial Bee Colony algorithm (ABC) have been used. …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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