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

Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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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.

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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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…They can be useful for taking a decision on choosing concrete values of traffic classification environments element parameters in a real network. …”
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Improved back propagation neural network for the diagnosis of pathological voices by Paulraj, M.P., Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Hariharan, Muthusamy

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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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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.

“…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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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

“…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah by Airul Sharizli, Abdullah

“…Hence, the success of CAWS system relies very much on whether the activation algorithm or model used is able to indicate a minimum safe distance precisely and timely. …”
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Power quality problem classification based on Wavelet Transform and a Rule-Based method by Nallagownden, Perumal

“…It is presented in this paper that the choice of sampling frequency is important since it affects the average energy profile of the details and eventually may cause error in detection of power quality disturbances. The model is tested by using MATLAB toolbox. The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. …”
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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

“…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method by Chuah , Heng keow, Nallagownden, Perumal, Kondapalli, K.S. Rama Rao

“…It is presented in this paper that the choice of sampling frequency is important since it affects the average energy profile of the details and eventually may cause error in detection of power quality disturbances. The model is tested by using MATLAB toolbox. The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. …”
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Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method by keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

“…It is presented in this paper that the choice of sampling frequency is important since it affects the average energy profile of the details and eventually may cause error in detection of power quality disturbances. The model is tested by using MATLAB toolbox. The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. …”
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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. …”

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

“…Most existing approaches modify the learning model in order to add a random factor to the model which can help to overcome the tendency to sink into local minima. …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia by Joe Wee Wei, Mr.

“…Both standalone and hybrid models were developed to identify the most optimum parameter to be used for river SF forecasting. …”

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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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

“…Performance analysis was achieved using simulated and eighteen real-life classification and regression microarray cancer datasets. …”
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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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