Search Results - (( parameter simulation modified algorithm ) OR ( using selection method algorithm ))

Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction by Adnan R.M., Kisi O., Mostafa R.R., Ahmed A.N., El-Shafie A.

Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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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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Intelligent Optimization Techniques for Optimal Power Flow using Interline Power Flow Controller by Mohamed, Mohamed, K.H, Kondapalli, Rama Rao. K. S.

“…In this paper the control parameters of voltage source converters used in Interline Power Flow Controller (IPFC) are designed to realize optimal power flow in a power system with modified Newton-Raphson method. …”
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INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM by MOHAMED ABDELGADIR, KHALID HAROUN

“…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

“…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

“…Artificial intelligence (AI) methods are normally selected to deal with this problem. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…In order to train Ridgelet probabilistic neural network, a modified differential evolution algorithm with new mutation phase, crossover process, and selection mechanism is introduced. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…Spearman Correlation was used to checked multi-collinearity effect on debris flow conditioning factors; evaluations factors of Information Value (IV), Crammer V were assessed.Wrapper feature subset selection technique was used, different metaheuristic search algorithms (e.g. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform by Abu Talib, Muhammad Ashraf

“…First, a synthetic model has been built by modifying ODEH data. Two sets of permeability value have been selected to get two data which are historical and simulated data from the model. …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

“…The methodology encompasses data acquisition, GA program development, SPM technique implementation, and simulation using MATLAB. The study simulated single-input-single-output (SISO) models: ARX and NARX. …”
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Numerical simulation and experimental verification on distortions induced by wire-arc additive manufacturing components and costing analysis / Keval Priapratama Prajadhiana by Prajadhiana, Keval Priapratama

“…On analysing the distortion effect by means of numerical computation method, a commercial specialized simulation software Simufact.Welding was used in the development of the numerical model. …”
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Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

“…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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Improved model for blood glucose control using Multi-Parametric Model Predictive Control (MP-MPC) / Nur Farhana Mohd Yusof by Mohd Yusof, Nur Farhana

“…Parameter addition in diabetic equation showed increment in the sensitivity behaviour of variables and improved the reaction rate through the simulation. …”
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AQUEOUS TWO-PHASE POLYMER MIXTURE SYSTEM AS PROTEIN XTRACTION TECHNIQUE. MODELLING OF PROTEIN PARTITIONING BEHAVIOR by Ahmad, Murni M

“…The minimization problem is solved using the modified Shor's R-algorithm for non-smooth optimization. …”
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Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi by Seyed Hossein, Mahdavi

“…Accordingly, in the second part of this research, the procedure of structural identification and damage detection has been developed by employing the wavelet-based method through the modified genetic algorithms (GAs) to optimally solve inverse problems. …”
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

“…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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