Prediction of true critical temperature and pressure of binary hydrocarbon mixtures: A Comparison between the artificial neural networks and the support vector machine by M. Etebarian, k. movagharnejad

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A hybrid machine learning method of support vector regression with particle swarm optimization for predicting IRI in continuously reinforced concrete pavement by Ali Alnaqbi, Waleed Zeiada, Ghazi Al-Khateeb

“…In order to forecast IRI using data taken from the Long-Term Pavement Performance (LTPP) database, this study proposes a hybrid machine learning model that combines Support Vector Regression (SVR) and Particle Swarm Optimization (PSO). …”
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Analisis Sentimen Berbasis Aspek Pada Ulasan Pelanggan Restoran Menggunakan Algoritma Support Vector Machine (Studi Kasus: Depot Bamara) by Muhammad Fariz Firdaus, Dian Eka Ratnawati, Nanang Yudi Setiawan

“…Terms found in the reviews were weighted using the frequency inverse document frequency (TF-IDF) weighting technique and classified using the support vector machine (SVM) algorithm. The classification model was tested with k-fold cross validation, resulting in an average accuracy of 92%, indicating good performance. …”
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Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for improved trend tracking and risk adjustment by Wei Ni, Qingqing Chen, Xiaochen Guo, Yanan Liu

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Evaluation of underground hard rock mine pillar stability using gene expression programming and decision tree‐support vector machine models by Mohammad H. Kadkhodaei, Ebrahim Ghasemi, Jian Zhou, Melika Zahraei

“…For this purpose, two robust models were developed using a database including 236 case histories from seven underground hard rock mines, based on gene expression programming (GEP) and decision tree‐support vector machine (DT‐SVM) hybrid algorithms. …”
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Increasing the degree of acceptability for chatbots in technical support systems for educational sector by using ML and semantic web by Adel A. Bahaddad

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Evaluating the performance of Random Forest, Decision Tree, Support Vector Regression and Gradient Boosting for streamflow prediction by Osahon Idemudia, Jacob Odeh Ehiorobo, Christopher Osadolor Izinyon, Idowu Ilaboya

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Evaluating the performance of Random Forest, Decision Tree, Support Vector Regression and Gradient Boosting for streamflow prediction by Osahon Idemudia, Jacob Odeh Ehiorobo, Christopher Osadolor Izinyon, Idowu Ilaboya

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Predictive Model for Erosion Rate of Concrete Under Wind Gravel Flow Based on K-Fold Cross-Validation Combined with Support Vector Machine by Yanhua Zhao, Kai Zhang, Aojun Guo, Fukang Hao, Jie Ma

“…The support vector machine (SVM) model demonstrates superior predictive performance, evidenced by its R² value nearing one and a notable reduction in RMSE 1.123 and 1.573 less than the long short-term memory network (LSTM) and BP neural network (BPNN) models, respectively. …”
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Machine Learning Classification of First-Onset Drug-Naive MDD Using Structural MRI by Donghwa Kim, Pilsung Kang, Junhong Kim, Czang Yeob Kim, Jong-Ha Lee, Sangil Suh, Moon-Soo Lee

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A Clinical Data Analysis Based Diagnostic Systems for Heart Disease Prediction Using Ensemble Method by Ankit Kumar, Kamred Udham Singh, Manish Kumar

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Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis by Yulin Zhang, Jian Zhou, Jialu Li, Biao He, Danial Jahed Armaghani, Shuai Huang

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Comparative Study of SVM, KNN, and Naïve Bayes for Sentiment Analysis of Religious Application Reviews by Heti Aprilianti, Khothibul Umam, Maya Rini Handayani

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Wind Turbine Blade Fault Detection Method Based on TROA-SVM by Zhuo Lei, Haijun Lin, Xudong Tang, Yong Xiong, He Wen

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Classification and Recognition Method for Bearing Fault based on IFOA-SVM by Wei Zhang, Zhihua Ma

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Classification of edible vegetable oils based on three-dimensional fluorescence spectroscopy and ISSA-SVM by ZHANG Jing, QI Guohong, CHEN Jingzhao, CAO Xiaoli, LI Lili

Subjects: “…support vector machine…”
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Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning by TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng

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The relationship between activities of daily living and speech impediments based on evidence from statistical and machine learning analyses by Liu Jun, Hongguo Li, Yu Mao, Lan Hu, Dan Wu

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Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…Previously, studies were conducted on the construction of predictive models using artificial neural networks and the CatBoost algorithm. Along with these methods, due to the capability to process data with highly nonlinear dependences between features, machine learning methods such as the k-nearest neighbor method, and the support vector machine (SVM) method, are widely used in related areas. …”
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High‐Impedance Fault Detection in Distribution Networks Based on Support Vector Machine and Wavelet Transform Approach (Case Study: Markazi Province of Iran) by Mohammad Sadegh Attar, Mohammad Reza Miveh

“…This paper employs a support vector machine (SVM) classification algorithm that demonstrates reliable accuracy and discrete wavelet transform (DWT) in HIF detection. …”
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