Evaluating different strategies for machine learning training applied to flow forecasting based on clustering of flood events by Patrícia Cristina Steffen, Júlio Gomes, Eloy Kaviski, Daniel Henrique Marco Detzel

“…So, five models were trained: one for the complete series, one for all flood events, and one for each cluster. The Support Vector Regression algorithm was used to develop Artificial Intelligence (AI) models, that had better performance in predicting discharge for each group they were trained and showed similar efficiency to the model trained for the entire series for a 1-day forecast time. …”
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Energy Assessment and Diagnosis of Variable Refrigerant Flow System Based on SVR-OCSVM Model by Liu Jiahui, Liu Jiangyan, Chen Huanxin, Huang Ronggeng, Li Zhengfei

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RESEARCH ON GEARBOX FAULT DIAGNOSIS BASE ON ISOMAP AND IGA-SVM by LIU ZhiChuan, TANG LiWei, CAO LiJun

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Fault Diagnosis of Oil Pumping Machine Retarder Based on Sound Texture-Vibration Entropy Characteristics and Gray Wolf Optimization-Support Vector Machine by Shutao Zhao, Ke Chang, Erxu Wang, Bo Li, Kedeng Wang, Qingquan Wu

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Fault analysis on deep groove ball bearing using ResNet50 and AlexNet50 algorithms by Vedant Jaiswal, Narendiranath Babu T, Pandiyan Murugan, Rama Prabha D

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SENTIMENT ANALYSIS OF MERDEKA BELAJAR KAMPUS MERDEKA POLICY USING SUPPORT VECTOR MACHINE WITH WORD2VEC by Nurul Rezki, Sri Astuti Thamrin, Siswanto Siswanto

“…Support Vector Machine is a classification algorithm that separates data classes using the optimum hyperplane. …”
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Decision Tree, Naïve Bayes and Support Vector Machine Applying on Social Media Usage in NYC / Comparative Analysis by Ahmed Burhan Mohammed

“…This study presents the comparison of three algorithms for classifications such as (Decision Tree, Naïve Bayes and Support Vector Machine), applying for social media usage dataset by NYC, to get the best result of the classification algorithm that can classify the instances according to the platforms. …”
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Comprehensive Modeling in Predicting Liquid Density of the Refrigerant Systems Using Least-Squares Support Vector Machine Approach by Jinya Cai, Haiping Zhang, Xinping Yu, Amir Seraj

“…A robust machine learning algorithm known as the least-squares support vector machine (LSSVM) model was used to predict the liquid densities of 48 different refrigerant systems. …”
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A Novel Method for Mechanical Fault Diagnosis Based on Variational Mode Decomposition and Multikernel Support Vector Machine by Zhongliang Lv, Baoping Tang, Yi Zhou, Chuande Zhou

“…A novel fault diagnosis method based on variational mode decomposition (VMD) and multikernel support vector machine (MKSVM) optimized by Immune Genetic Algorithm (IGA) is proposed to accurately and adaptively diagnose mechanical faults. …”
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Particle Swarm Optimization of Support Vector Machine Inversion Model for Overhead Upright Piers Damage-Inducing Factor by Shiliang Zhou, Menghan Tang, Jun Wu, Chunru Ke

“…For intelligent monitoring of existing terminals, this research chooses Chongqing Xintian Port as the study object and proposes a support vector machine (SVM) damage-inducing factor (DIF) inversion model based on particle swarm optimization (PSO). …”
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Aspect-Based Sentiment Analysis on User Perceptions of OVO using Latent Dirichlet Allocation and Support Vector Machine by Eka Fahira Aprilia, Amalia Anjani Arifiyanti, Nambi Sembilu

“…A classification model was then developed using the Support Vector Machine (SVM) algorithm across six testing scenarios. …”
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A real-time wireless wearable electroencephalography system based on Support Vector Machine for encephalopathy daily monitoring by Qing Zhang, Pingping Wang, Yan Liu, Bo Peng, Yufu Zhou, Zhiyong Zhou, Baotong Tong, Bensheng Qiu, Yishan Zheng, Yakang Dai

“…Therefore, we proposed a wireless wearable electroencephalography system for encephalopathy daily monitoring, named as Brain-Health, which focused on the following three points: (a) the monitoring device integrated with electroencephalography acquisition sensors, signal processing chip, and Bluetooth, attached to a sport hat or elastic headband; (b) the mobile terminal with dedicated application, which is not only for continuous recording and displaying electroencephalography signal but also for early warning in real time; and (c) the encephalopathy’s classification algorithm based on intelligent Support Vector Machine, which is used in a new application of wearable electroencephalography for encephalopathy daily monitoring. …”
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Driving Anger States Detection Based on Incremental Association Markov Blanket and Least Square Support Vector Machine by Ping Wan, Chaozhong Wu, Yingzi Lin, Xiaofeng Ma

“…., traffic congestion, vehicles weaving/cutting in line, jaywalking and red light waiting in real traffic environment; (2) apply incremental association Markov blanket (IAMB) algorithm to select typical features related to driving anger states; (3) employ least square support vector machine (LSSVM) to identify different driving anger states based on the selected features. …”
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Kombinasi K-Means dan Support Vector Machine (SVM) untuk Memprediksi Unsur Sara pada Tweet by Wiga Maulana Baihaqi, Muliasari Pinilih, Miftakhul Rohmah

“…This study aims to make sentence corpus containing SARA elements obtained from twitter, then label sentences with labels containing elements of SARA and not, and conduct group sentiments. The algorithm used for the labeling process is k-means, while Support Vector Machine (SVM) is used for the classification process. …”
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A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression by Hilario Gómez-Moreno, Pedro Gil-Jiménez, Sergio Lafuente-Arroyo, Roberto López-Sastre, Saturnino Maldonado-Bascón

“…We present a new impulse noise removal technique based on Support Vector Machines (SVM). Both classification and regression were used to reduce the “salt and pepper” noise found in digital images. …”
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Caffeine Content Prediction in Coffee Beans Using Hyperspectral Reflectance and Machine Learning by Dthenifer Cordeiro Santana, Rafael Felipe Ratke, Fabio Luiz Zanatta, Cid Naudi Silva Campos, Ana Carina da Silva Cândido Seron, Larissa Pereira Ribeiro Teodoro, Natielly Pereira da Silva, Gabriela Souza Oliveira, Regimar Garcia dos Santos, Rita de Cássia Félix Alvarez, Carlos Antonio da Silva Junior, Matildes Blanco, Paulo Eduardo Teodoro

“…Pearson’s correlation coefficient, mean absolute error, and root mean square error were tested as model accuracy metrics. The support vector machine algorithm showed the best accuracy in predicting caffeine content when using hyperspectral data from roasted and ground coffee beans. …”
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Performance Comparison of Support Vector Machine (SVM) and k-Nearest Neighbors (kNN) in Verifying Material Orientation by Eldio Utama, Eko Rudiawan Jamzuri

“…This study compares the performance of Support Vector Machine (SVM) and k-Nearest Neighbors algorithms for verifying material orientation verification through automated optical inspection. …”
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Support Vector and Linear Regression Machine Learning Model on Amperometric Signals to Predict Glucose Concentration and Hematocrit Volume by Kirti Sharma, Pawan K. Tiwari, Sanjay Kumar Sinha

“…In contrast, employing the support vector regressor yielded R2 scores of about 0.961 for GC and 0.506 for HV. …”
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Comparative Study of Random Forest and Support Vector Machine for Land Cover Classification and Post-Wildfire Change Detection by Yan-Cheng Tan, Lia Duarte, Ana Cláudia Teodoro

“…Previous studies have shown that random forest (RF) and support vector machine (SVM) consistently achieve high accuracy for land classification. …”
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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

Subjects: “…Fractional Whale Optimization Algorithm-Enhanced Support Vector Regression…”
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