Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

“…This work employs single hidden layer extreme learning machine (ELM) algorithm and hybrid particle swarm optimization-based support vector regression (PS-SVR) for determining energy storage efficiency of high-entropy ceramics. …”
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Research on Forecasting Sales of Pure Electric Vehicles in China Based on the Seasonal Autoregressive Integrated Moving Average–Gray Relational Analysis–Support Vector Regression M... by Ru Yu, Xiaoli Wang, Xiaojun Xu, Zhiwen Zhang

“…Secondly, variables that were highly correlated with sales were analyzed using gray relational analysis (GRA) and utilized as input parameters for the support vector regression (SVR) model, which was constructed to optimize sales predictions for EVs. …”
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Theoretical and computational investigations on estimation of viscosity of ionic liquids for green adsorbent: Effect of temperature and composition by Zhaoxiong Han

“…The models used are Gaussian Process Regression (GPR), Multilayer Perceptron (MLP), and Support Vector Regression (SVR). …”
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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

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Analysis of inductive power transfer systems by metamodeling techniques by Pei, Yao, Pichon, Lionel, Bensetti, Mohamed, Le Bihan, Yann

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Machine Learning-Based Lithium Battery State of Health Prediction Research by Kun Li, Xinling Chen

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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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Yield Response of Different Rice Ecotypes to Meteorological, Agro-Chemical, and Soil Physiographic Factors for Interpretable Precision Agriculture Using Extreme Gradient Boosting a... by Md. Sabbir Ahmed, Md. Tasin Tazwar, Haseen Khan, Swadhin Roy, Junaed Iqbal, Md. Golam Rabiul Alam, Md. Rafiul Hassan, Mohammad Mehedi Hassan

“…Moreover, this study found a different set of those factors with respect to the yield response of different rice ecotypes. Machine learning algorithms named Extreme Gradient Boosting (XGBoost) and Support Vector Regression (SVR) have been used for predicting the yield response. …”
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Discrimination of Chinese prickly ash origin place using electronic nose system and feature extraction with support vector boosting machine by Junbo Lian, Peng Wu, Wenhui Han, Yaping Xie, Yue Zheng, Yuxuan Xu, Xinlin Li, Guofeng Hou, Chengxiang Yong, Qi Lv, Qiansheng Ye, Guohua Hui

“…These novel techniques were coupled with a support vector boosting machine for origin place classification. …”
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Computational hybrid analysis of drug diffusion in three-dimensional domain with the aid of mass transfer and machine learning techniques by Mohammed Alqarni, Ali Alqarni

“…We employ three tree-based ensemble models: Kernel Ridge Regression (KRR), $$\:{\upnu\:}$$ -Support Vector Regression ( $$\:{\upnu\:}$$ -SVR), and Multi Linear Regression (MLR) for modeling the relationship between spatial coordinates and the concentration. …”
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Leveraging Machine Learning for Exchange Rate Prediction: A Business and Financial Management Perspective in Nigeria by Adedeji Daniel Gbadebo

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An Inverse Modeling Multi-Objective Optimization Technique Based on Incremental Learning and Fuzzy Clustering by Gadallah Mohamed Abd Elaziz, Yasmine Abouelseoud, Sara H. Kamel

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Research on Wind Power Grid Integration Power Fluctuation Smoothing Control Strategy Based on Energy Storage Battery Health Prediction by Bin Cheng, Jiahui Wu, Guancheng Lv, Zhongbo Li

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IGWO-MSVR model for predicting stress in coal seam during drilling process by Jian Tan, Yanfeng Geng, Liangke Xu

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Application of Support Vector Machines in High Power Device Technology by RAO Wei, LI Yong, YAN Ji

“…As a machine learning algorithm, support vector machine(SVM) has the advantages of good nonlinear processing ability, theoretical global optimum and overcoming the curse of dimensionality. …”
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An improved Multi-Objective Whale Optimization Algorithm for hydrodynamic and acoustic performance optimization of Myring-shaped underwater vehicle by Qigan Wang, Yu Dong, Han Wu, Peizhan Cao, Zhijun Zhang

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Comparative Study of Machine Learning Techniques for Insurance Fraud Detection by Navin Duwadi, Anita Sharma

“…The most popular traditional machine learning algorithms used to identify insurance fraud in the auto industry were found to be support vector machine, logistic regression, and random forest.…”
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Enhancing Compressive Strength Prediction in Recycled Aggregate Concrete through Robust Hybrid Machine Learning Approaches by Samuel Keown, Dylan O’Dwyer

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Enhanced Hyperspectral Forest Soil Organic Matter Prediction Using a Black-Winged Kite Algorithm-Optimized Convolutional Neural Network and Support Vector Machine by Yun Deng, Lifan Xiao, Yuanyuan Shi

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Inverse System Decoupling Control of Composite Cage Rotor Bearingless Induction Motor Based on Support Vector Machine Optimized by Improved Simulated Annealing-Genetic Algorithm by Chengling Lu, Junhui Cheng, Qifeng Ding, Gang Zhang, Jie Fang, Lei Zhang, Chengtao Du, Yanxue Zhang

“…To address the inherent nonlinearity and strong coupling among rotor displacement, speed, and flux linkage in the composite cage rotor bearingless induction motor (CCR-BIM), an inverse system decoupling control strategy based on a support vector machine (SVM) optimized by the improved simulated annealing-genetic algorithm (ISA-GA) is proposed. …”
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