Assessment for Thermal Conductivity of Frozen Soil Based on Nonlinear Regression and Support Vector Regression Methods by Fu-Qing Cui, Wei Zhang, Zhi-Yun Liu, Wei Wang, Jian-bing Chen, Long Jin, Hui Peng

“…Compared with the unfrozen soil, the specimen preparation and experimental procedures of frozen soil thermal conductivity testing are more complex and challengeable. In this work, considering for essentially multiphase and porous structural characteristic information reflection of unfrozen soil thermal conductivity, prediction models of frozen soil thermal conductivity using nonlinear regression and Support Vector Regression (SVR) methods have been developed. …”
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Non-Invasive Glucose Monitoring Using Optical Sensors and Machine Learning: A Predictive Model for Nutritional and Health Assessment by Heru Agus Santoso, Nur Setiawati Dewi, Susilo, Arga Dwi Pambudi, Hanif Pandu Suhito, Iman Dehzangi

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Coupling Beams’ Shear Capacity Prediction by Hybrid Support Vector Regression and Particle Swarm Optimization by Emad A. Abood, Mustafa Kamal Al-Kamal, Sabih Hashim Muhodir, Nadia Moneem Al-Abdaly, Luís Filipe Almeida Bernardo, Dario De Domenico, Hamza Imran

“…The data of RC coupling beams collected from the previous works were utilized to build the proposed model. …”
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Study on magnetic field parameters in the inductor working chamber by Nikolay V. Limarenko, Victor P. Zharov, Yury V. Panov, Boris G. Shapoval

“…A cybernetic model of the experimental research to assess the inductor performance quality is developed. …”
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Incremental Support Vector Machine Combined with Ultraviolet-Visible Spectroscopy for Rapid Discriminant Analysis of Red Wine by Jun Liu, Tie-Jun Pan, Zheng-Yong Zhang

“…The aim of this work is to develop a new method to overcome the increased training time when a recognition model is updated based on the condition of new features extracted from new samples. …”
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Comparison and general law research of multiple machine-learning models for proton exchange membrane electrolytic cell parameters prediction by Yukun Wang, Hai-Wen Li, Wenhan An, Yudong Mao, Kaimin Yang, Jiying Liu

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A Novel Homogenous Hybridization Scheme for Performance Improvement of Support Vector Machines Regression in Reservoir Characterization by Kabiru O. Akande, Taoreed O. Owolabi, Sunday O. Olatunji, AbdulAzeez Abdulraheem

“…Therefore, the importance of fusing two or more intelligent algorithms to achieve better performance cannot be overemphasized. In this work, a novel homogenous hybridization scheme is proposed for the improvement of the generalization and predictive ability of support vector machines regression (SVR). …”
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Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification by R. Rajesh Sharma, P. Marikkannu

“…The primary objective of this work is to propose a three-dimensional (3D) novel brain tumor classification model using MRI images with both micro- and macroscale textures designed to differentiate the MRI of brain under two classes of lesion, benign and malignant. …”
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Optimization of Hydronic Heating System in a Commercial Building: Application of Predictive Control with Limited Data by Rana Loubani, Didier Defer, Ola Alhaj-Hasan, Julien Chamoin

“…Limited data poses challenges for capturing system dynamics, addressed through a black-box approach combining two machine learning models: an artificial neural network predicts indoor temperature, while a support vector machine estimates gas consumption. …”
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Prediction model of water inrush risk level of coal seam floor based on KPCA-DBO-SVM by Wei Wang, Huangrui Wang, Xuping Li, Yun Qi, Xinchao Cui, Chenhao Bai

“…The KPCA-DBO-SVM model is applied to three coal mine working face to verify the stability and universality of the model whose prediction results are consistent with the actual engineering situation. …”
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Common AAV gene therapy vectors show nonselective transduction of ex vivo human brain tissue by JP McGinnis, Joshua Ortiz-Guzman, Maria Camila Guevara, Sai Mallannagari, Benjamin D.W. Belfort, Suyang Bao, Snigdha Srivastava, Maria Morkas, Emily Ji, Angela Addison, Evelyne K. Tantry, Sarah Chen, Ying Wang, Zihong Chen, Kalman A. Katlowitz, Jeffrey J. Lange, Melissa M. Blessing, Carrie A. Mohila, M. Cecilia Ljungberg, Guillermo Aldave, Ali Jalali, Akash Patel, Sameer A. Sheth, Howard L. Weiner, Shankar Gopinath, Ganesh Rao, Akdes Serin Harmanci, Daniel J. Curry, Benjamin R. Arenkiel

“…The ability to deliver a therapeutic sequence to a specific cell type in the human brain would make possible innumerable therapeutic options for some of our most challenging diseases; however, studies on adeno-associated virus (AAV) vector tropism have generally relied on animal models with limited translational utility. …”
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Particle Swarm Optimization Support Vector Machine-Based Grounding Fault Detection Method in Distribution Network by Zhongqin Xiong, Shichang Huang, Shen Ren, Yutong Lin, Zewen Li, Dongyu Li, Fangming Deng

“…With the present fault detection method for low-voltage distribution networks, it is difficult to detect single-phase grounding faults under complex working conditions. In this paper, a particle swarm optimization (PSO) support vector machine (SVM)-based grounding fault detection method is proposed for distribution networks. …”
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Performance Enhancement of MRAC via Generalized Dynamic Inversion by Alharith Mahmoud, Abdulrahman H. Bajodah

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A common framework for fermion mass hierarchy, leptogenesis and dark matter by Carolina Arbeláez, A. E. Cárcamo Hernández, Claudio Dib, Patricio Escalona Contreras, Vishnudath K. N., Alfonso Zerwekh

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Mathematical Evaluation of Classical and Quantum Predictive Models Applied to PM2.5 Forecasting in Urban Environments by Jesús Cáceres-Tello, José Javier Galán-Hernández

“…This study provides a mathematical and computational comparison between two predictive paradigms: the classical Long Short-Term Memory (LSTM) model, designed for sequential analysis of time series, and the quantum model Quantum Support Vector Machine (QSVM), based on kernel methods applied in Hilbert spaces. …”
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A Comparative Study of Machine Learning and Deep Learning Models for Automatic Parkinson’s Disease Detection from Electroencephalogram Signals by Sankhadip Bera, Zong Woo Geem, Young-Im Cho, Pawan Kumar Singh

“…<b>Conclusions:</b> Our findings, coupled with advanced feature extraction and deep learning, have the potential to provide a non-invasive, efficient, and reliable approach for diagnosing PD, with further work aimed at enhancing feature sets, inclusion of a large number of subjects, and improving model generalizability across more diverse environments.…”
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Multiple Criteria Decision-Making Based on Vector Similarity Measures under the Framework of Dual Hesitant Fuzzy Sets by Juan Luis García Guirao, M. Sarwar Sindhu, Tabasam Rashid, Agha Kashif

“…In order to identify the similarity between the options, many experts have established several types of similarity measures on the basis of vectors and distances. The Cosine, Dice, and Jaccard are the vector similarity measures. …”
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A Parallel Support Vector Machine algorithm to identify patterns of pollution in Smart Cities for Metropolitan Zone of Guadalajara by Martha Patricia Martínez Vargas, Elsa Estrada Guzmán, Roció Maciel Arellano

“…Currently, these data are captured by constant monitoring stations, generating a large volume of information representing a challenge for the classification process. This work proposes a model for the automatic execution of a classification algorithm using Support Vector Machine implementing libraries in python for parallel processing. …”
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Lung Organoids from hiPSCs Can Be Efficiently Transduced by Recombinant Adeno-Associated Viral and Adenoviral Vectors by Lyubava Belova, Anna Demchenko, Anastasia Erofeeva, Konstantin Kochergin-Nikitsky, Olga Zubkova, Olga Popova, Tatiana Ozharovskaia, Diana Salikhova, Anna Efremova, Alexander Lavrov, Svetlana Smirnikhina

“…<b>Conclusions:</b> rAdV5 and rAAV9 are the most promising vectors for the delivery of transgenes to basal and secretory cells in a lung organoid model, providing a solid foundation for CF gene therapy development.…”
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Health State Prediction of Lithium-Ion Battery Based on Improved Sparrow Search Algorithm and Support Vector Regression by Deyang Yin, Xiao Zhu, Wanjie Zhang, Jianfeng Zheng

“…To enhance prediction performance, this paper introduces an SOH prediction model based on an improved sparrow algorithm and support vector regression (ISSA-SVR). …”
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