Search Results - (( process classification using algorithm ) OR ( parameter simulation model algorithm ))

An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”

The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

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Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

“…In order to make all this in a ubiquitous form factor, the algorithm for classification and detection of the pre-seizure conditions should be tremendously simple for processing the signal in a low cost ubiquitous microcontroller. …”
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure state using Real EEG data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

“…In order to make all this in a ubiquitous form factor, the algorithm for classification and detection of the pre-seizure conditions should be tremendously simple for processing the signal in a low cost ubiquitous microcontroller. …”
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

“…In order to make all this in a ubiquitous form factor, the algorithm for classification and detection of the pre-seizure conditions should be tremendously simple for processing the signal in a low cost ubiquitous microcontroller. …”
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Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption by Alsammak I.L.H., Mahmoud M.A., Gunasekaran S.S., Ahmed A.N., Alkilabi M.

“…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”

Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

“…The simulations will be done using the PSCAD/EMTDC software. …”
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Detection of Denial of Service Attacks against Domain Name System Using Neural Networks by Rastegari, Samaneh

“…With the prior knowledge of DoS attacks against DNS, we used a network simulator to model DNS traffic with high variability. …”
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Support vector machine for day ahead electricity price forecasting by Razak I.A.B.W.A., Abidin I.B.Z., Siah Y.K., Rahman T.K.B.A., Lada M.Y., Ramani A.N.B., Nasir M.N.M., Ahmad A.B.

“…Moreover, same parameter settings in trained SVM give same results that absolutely reduce simulation process compared to other techniques such as neural network and time series. …”

Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway by Ahmad Muhaimin, Ismail, Muhammad Akmal, Remli, Yee Wen, Choon, Nurul Athirah, Nasarudin, Norsyahidatul Nazirah, Ismail, Mohd Arfian, Ismail, Mohd Saberi, Mohamad

“…Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. …”
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GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

“…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

“…The application has widespread in many areas especially in system and control engineering. Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

“…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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Simulation algorithm of bayesian approach for choice-conjoint model by Zulhanif

“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”

A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

“…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

“…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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