Identification method of canned food for production line sorting robot based on improved PSO-SVM by GAO Haiyan, GAO Jinyang, WANG Weicheng

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Medium- and Long-term Runoff Prediction Based on SMA-LSSVM by TIAN Jinghuan, LI Congxin, LI Ang

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Analisis Sentimen: Pengaruh Jam Kerja Terhadap Kesehatan Mental Generasi Z by Muhammad Daffa Al Fahreza, Ardytha Luthfiarta, Muhammad Rafid, Michael Indrawan

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Hybrid procurement model for the construction of library literature and information resource procurement by Chuanyu Zhang, Changsheng Wang

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Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

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Machine Learning for Predicting Bank Stability: The Role of Income Diversification in European Banking by Karim Farag, Loubna Ali, Noah Cheruiyot Mutai, Rabia Luqman, Ahmed Mahmoud, Nol Krasniqi

“…It employs a hybrid method that combines econometric techniques, specifically the generalized method of moments and a fixed-effects model, with machine-learning algorithms such as Random Forest and Support Vector Machine. …”
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Persian SMS Spam Detection using Machine Learning and Deep Learning Techniques by Roya Khorashadizade, Somayyeh Jafarali Jassbi, Alireza Yari

“…After applying preprocessing on our gathered dataset, the suggested technique applies two convolutional neural network layers, the first of which being an LSTM layer, and the second one which is a fully connected layer to extract the data characteristics, thereby implementing the suggested deep learning approach. As part of the Machine Learning methodologies, the vector support machine makes use of the data and features at hand to determine the ultimate classification. …”
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Machine learning approach for water quality predictions based on multispectral satellite imageries by Vicky Anand, Bakimchandra Oinam, Silke Wieprecht

“…The main objective of this study to retrieve and map the water quality parameters from Sentinel-2 and ResourceSat-2 [Linear Imaging Self-Scanning Sensor (LISS)–IV] multi-spectral satellite data, using Support Vector Machines (SVM), Random Forests (RF), and Multi-Linear regression (MLR) models. …”
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Support Vector Machine Berbasis Feature Selection Untuk Sentiment Analysis Kepuasan Pelanggan Terhadap Pelayanan Warung dan Restoran Kuliner Kota Tegal by Oman Somantri, Dyah Apriliani

“…Sentiment analysis is used to provide a solution related to this problem by applying the Support Vector Machine (SVM) algorithm model. The purpose of this research is to optimize the generated model by applying feature selection using Informatioan Gain (IG) and Chi Square algorithm on the best model produced by SVM on the classification of customer satisfaction level based on culinary restaurants at Tegal City so that there is an increasing accuracy from the model. …”
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Optimasi Algoritma Support Vector Machine Berbasis Kernel Radial Basis Function (RBF) Menggunakan Metode Particle Swarm Optimization Untuk Analisis Sentimen by Cucun Very Angkoso, Khozainul Asror, Ari Kusumaningsih, Andi Kurniawan Nugroho

“…The study investigates the effectiveness of the Particle Swarm Optimization (PSO) method for balanced and unbalanced datasets and how well it improves sentiment analysis accuracy when applied to the Support Vector Machine (SVM) algorithm when using Radial Basis Function (RBF) kernel. …”
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Prediction of matrilineal specific patatin-like protein governing in-vivo maternal haploid induction in maize using support vector machine and di-peptide composition by Suman Dutta, Rajkumar U. Zunjare, Anirban Sil, Dwijesh Chandra Mishra, Alka Arora, Nisrita Gain, Gulab Chand, Rashmi Chhabra, Vignesh Muthusamy, Firoz Hossain

“…Four different kernels [radial basis function (RBF), sigmoid, polynomial, and linear] were used for building support vector machine (SVM) classifiers using six different sequence-based compositional features (AAC, DPC, GDPC, CTDC, CTDT, and GAAC). …”
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Pengujian Rule-Based pada Dataset Log Server Menggunakan Support Vector Machine Berbasis Linear Discriminat Analysis untuk Deteksi Malicious Activity by Kurnia Adi Cahyanto, Muhammad Anis Al Hilmi, Muhamad Mustamiin

“…Dataset log yang telah didapat, diolah dengan menggunakan pelabelan rule-based yang nantinya diuji dengan pemodelan Support Vector Machine berbasis Linear Discriminant Analysis. …”
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Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

“…The study aims to accurately predict the presence of heart disease using machine learning models. The research evaluates and compares the performance of five algorithms - Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random Forest, and Gradient Boosting - on a dataset containing clinical features of patients. …”
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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

“…Based on the comparison, this paper grouped the top seven ML models such as Neural Networks, Logistic Regression, Nave Bayes Classifier, Multilayer Perceptron, Support Vector Machine, BF Tree, Bayesian Networks algorithms and measured feature importance, and other, to justify the differences between classification models. …”
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Analisis Sentimen Pada Sosial Media Twitter Terhadap Kualitas Jaringan Internet Telkomsel Menggunakan Ensemble K-Nearest Neighbour -Support Vector Machine by Muchammad Farchan Fachrudin, Cucun Very Angkoso, Doni Abdul Fatah

“…This sentiment analysis research uses machine learning algorithm models, namely K-Nearest Neighbor, Support Vector Machine, and KNN-SVM Ensemble which are majority vote-based and average-based. …”
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Supervised methods of machine learning for email classification: a literature survey by Muath AlShaikh, Yasser Alrajeh, Sultan Alamri, Suhib Melhem, Ahmed Abu-Khadrah

“…Notably, supervised methodologies such as support vector machines (SVMs), naive Bayes, decision trees, neural networks, random forests, and deep learning have been exploited for spam filtering. …”
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Integrating machine learning and sentiment analysis in movie recommendation systems by Amany M. Sarhan, Hager Ayman, Mariam Wagdi, Bassant Ali, Aliaa Adel, Rahf Osama

“…To this purpose, the integration of advanced machine learning algorithms such as cosine similarity, support vector machine, and Naive Bayes improves recommendation systems with sentiment analysis. …”
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Machine Learning-Based Cost Estimation Models for Office Buildings by Guolong Chen, Simin Zheng, Xiaorui He, Xian Liang, Xiaohui Liao

“…This paper explores the application of algorithm-optimized back propagation neural networks and support vector machines in predicting the costs of office buildings. …”
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Migraine triggers, phases, and classification using machine learning models by Anusha Reddy, Ajit Reddy

“…In many cases, patients with migraine are often misdiagnosed as regular headaches.MethodsIn this article, we present a study on migraine, covering known triggers, different phases, classification of migraine into different types based on clinical studies, and the use of various machine learning algorithms such as logistic regression (LR), support vector machine (SVM), random forest (RF), and artificial neural network (ANN) to learn and classify different migraine types. …”
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Reliability Optimization of Structural Deformation with Improved Support Vector Regression Model by Zheng-Zheng Zhu, Yun-Wen Feng, Cheng Lu, Cheng-Wei Fei

“…The quality of a model seriously influences the reliability optimization of turbine blades in turbo machines. To improve the reliability optimization of turbine blades, this paper proposes a novel machine learning-based reliability optimization approach, named improved support vector regression (SR) model (ISRM) method, by fusing artificial bee colony (ABC), traditional SR model, and multipopulation genetic algorithm (MPGA). …”
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