Search Results - (( wave optimization methods algorithm ) OR ( model optimization svm algorithm ))

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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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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A hybrid novel SVM model for predicting CO2 emissions using Multiobjective Seagull Optimization by Ehteram M., Sammen S.S., Panahi F., Sidek L.M.

Solving SVM model selection problem using ACOR and IACOR by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization (ACO) has been used to solve Support Vector Machine (SVM) model selection problem.ACO originally deals with discrete optimization problem. …”
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Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study by Got, Adel, Zouache, Djaafar, Moussaoui, Abdelouahab, Laith, Abualigah *, Alsayat, Ahmed

“…In this paper, the MRFO + SVM algorithm is introduced by investigating the recent manta ray foraging optimizer to fine-tune the SVM parameters and identify the optimal feature subset simultaneously. …”
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Mixed variable ant colony optimization technique for feature subset selection and model selection by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

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Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm by Mohamadi S., Sammen S.S., Panahi F., Ehteram M., Kisi O., Mosavi A., Ahmed A.N., El-Shafie A., Al-Ansari N.

An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system by M. W., Mustafa, H., Shareef, M. H., Sulaiman, S. N., Abd. Khalid, S. R., Abd. Rahim, Omar, Aliman

“…The idea is to use GA as an optimizer to find the optimal values of hyper-parameters of LS-SVM and adopt a supervised learning approach to train the LS-SVM model. …”
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An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system by Mohd. Herwan, Sulaiman, Siti Rafidah, Abdul Rahim, Mohd Wazir, Mustafa, Hussain, Shareef, Dr., Saifulnizam, Abd. Khalid, Dr., Omar, Aliman

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SVM modelling of agarwood oil quality grading using radial basis function (RBF) and sequential minimal optimization (SMO) learning algorithms by Muhammad Haziq Haikal, Hisham, Nurlaila, Ismail, Nor Azah, Mohd Ali, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

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Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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Sentiment analysis on COVID-19 outbreak using PSO-SVM / Amir Danial Shahrul Sazali by Shahrul Sazali, Amir Danial

“…This project provides the analyzation of attitudes expressed in textual data connected to the COVID-19 outbreak using Particle Swarm Optimization with Support Vector Machines (SVM). This project is driven by the objectives to identify the requirement of Particle Swarm Optimization with Support Vector Machines (PSO-SVM) in sentiment analysis of covid-19 tweets, to apply the PSO-SVM method for sentiment analysis that classified tweets accurately and to evaluate the result of the PSO-SVM model for Covid-19 outbreak sentiment analysis. …”
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An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin by Mazlin, Mohd Irwan

“…For future work, it is recommended to extend the dataset so that the model can predict the classes in more detail and combine the model with an optimization algorithm to improve the performance of the model.…”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…Both models' parameters are optimized to achieve optimal performance. …”
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Optimization of feature selection in Support Vector Machines (SVM) using recursive feature elimination (RFE) and particle swarm optimization (PSO) for heart disease detection by Bayuaji, Luhur, Kusnadi, Kusnadi, Amzah, Mochamad Yamin, Pebrianti, Dwi

“…RFE combines a dimensionality reduction process with a machine learning process where the least important features are iteratively removed until the best feature subset is obtained, while the PSO method is used to optimize the C and gamma parameters of SVM. The results of the SVM-RFE PSO model trial showed increased accuracy in classifying heart disease. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Transmission loss allocation in deregulated power system using the hybrid genetic algorithm-support vector machine technique by M. W, Mustafa, Mohd Herwan, Sulaiman, H., Shareef, S. N., Abd. Khalid

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Prediction of COVID-19 outbbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

“…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
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Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill by Abunama, Taher, Othman, Faridah, Ansari, Mozafar, El-Shafie, Ahmed

“…These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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