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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA) by Hitam, Nor Azizah, Ismail, Amelia Ritahani, Samsudin, Ruhaidah, Ameerbakhsh, Omair

“…Support Vector Machine (SVM) technique is used with the Whale Optimization Algorithm (WOA) which is inspired by the swarm optimization algorithms. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

“…The purpose of the study is to detect, classify malware attacks using a variety of ML Algorithm models such as SVM, KNN and Neural Network and testing detection performance. …”
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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study by Lestari, Widya, Abdullah, Adilah Syahirah, Ahmad Amin, Afifah Munirah, faridah, Nur, Sukotjo, Cortino, Ismail, Azlini, mohamad ibrahim, mohamad shafiq, Insani, Nashuha, Utomo, Chandra Prasetyo

“…RF was the most precise algorithm for predicting grades A, B, and C, followed by LR, DT, and SVM. …”
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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine by Almansi, Khaled Yousef, Mohamed Shariff, Abdul Rashid, Abdullah, Ahmad Fikri, Syed Ismail, Sharifah Norkhadijah

“…Thus, the suitability map of potential hospital sites was modeled using a support vector machine (SVM), multilayer perceptron (MLP), and linear regression (LR) models. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…News classification into factors affecting stock market turning point was done using Naïve Bayes, Deep Learning, Generalized Linear Model (GLM) and Support Vector Machine (SVM). …”
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Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

“…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”

Groundwater level as an input to monthly predicting of water level using various machine learning algorithms by Sapitang M., Ridwan W.M., Ahmed A.N., Fai C.M., El-Shafie A.

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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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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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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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.

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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Data-driven rice yield predictions and prescriptive analytics for sustainable agriculture in Malaysia by Marong, Muhammad, Husin, Nor Azura, Zolkepli, Maslina, Affendey, Lilly Suriani

“…This research investigates the impact of environmental conditions and management methods on crop yields, focusing on accurate predictions to inform decision-making by farmers. Utilizing machine learning algorithms as decision-support tools, the study analyses commonly used models—Linear Regression, Support Vector Machines, Random Forest, and Artificial Neural Networks—alongside key environmental factors such as temperature, rainfall, and historical yield data. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…This paper presents an intelligent system to reduce Non Technical Loss (NTL) using hybrid Support Vector Machine (SVM) and Genetic Algorithm (GA). …”

Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

“…The optimal model was selected based on the mean area under the receiver operating characteristic curve (AUC-ROC) across 10 cross-validation runs and was used with Shapley Additive exPlanations to analyze the risk factors. …”
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Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique by Lee, Zhong Zhen, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Abraham, Ajith

“…The SVM algorithm uses the Radial Basis Function (RBF) kernel function and optim ization of the gam ma and large margin parameters are done using the PSO algorithm. …”
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