Zobrazeno 1 - 10 of 312 780 pro vyhledávání: '"Support vector machine(SVM)"'
1
Akademický článek
Sentiment Analysis on Tabungan Perumahan Rakyat (TAPERA) Program by using Support Vector Machine (SVM)
Autor: Rizki Agam Syahputra, Riski Arifin, Suryadi ., Muhammad Iqbal
Publikováno v: Journal of Applied Informatics and Computing, Vol 8, Iss 2, Pp 531-541 (2024)
This study aims to analyze public sentiment towards the Housing Savings Program (TAPERA) using the Support Vector Machine (SVM) algorithm. The dataset comprises 16,061 reviews about TAPERA which was gathered from web scrapping and YouTube API. The se
Externí odkaz: https://doaj.org/article/119b7f76a9354c0d85a63a8725dc25c9
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2
Akademický článek
An integrated approach of support vector machine (SVM) and weight of evidence (WOE) techniques to map groundwater potential and assess water quality.
Autor: Riaz, Malik Talha1,2 (AUTHOR), Riaz, Muhammad Tayyib2 (AUTHOR), Rehman, Adnanul3 (AUTHOR), Bindajam, Ahmed Ali4 (AUTHOR), Mallick, Javed5 (AUTHOR), Abdo, Hazem Ghassan6 (AUTHOR) Hazemabdo@tartous-univ.edu.sy
Publikováno v: Scientific Reports. 10/31/2024, Vol. 14 Issue 1, p1-23. 23p.
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3
Akademický článek
Research on fault localization of distribution transformers based on frequency response analysis and support vector machine (SVM)
Autor: Xingting Liu, Haiqi Wang, Zhuo Gao, Xutao Han
Publikováno v: Frontiers in Energy Research, Vol 12 (2024)
Distribution transformers are vital to the stability of the power system, but long-term operation and environmental factors can cause distribution transformers to discharge, posing a potential threat. The impulse voltage withstand test rigorously eva
Externí odkaz: https://doaj.org/article/1ca6b4500f204b07b63b8e5fd9ecf12d
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4
Akademický článek
Applying a Support Vector Machine (SVM-RFE) Learning Approach to Investigate Students' Scientific Literacy Development: Evidence from Asia, Europe, and South America.
Autor: Li, Jian1 (AUTHOR) 11112018031@bnu.edu.cn, Wang, Jianing2 (AUTHOR) wangjianing2023@mail.bnu.edu.cn, Xue, Eryong3 (AUTHOR) wangjianing2023@mail.bnu.edu.cn
Publikováno v: Journal of Intelligence. Nov2024, Vol. 12 Issue 11, p111. 18p.
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5
Akademický článek
Image Processing and Support Vector Machine (SVM) for Classifying Environmental Stress Symptoms of Pepper Seedlings Grown in a Plant Factory.
Autor: Islam, Sumaiya1 (AUTHOR) dina0075@o.cnu.ac.kr, Samsuzzaman2 (AUTHOR) samsuzzaman@o.cnu.ac.kr, Reza, Md Nasim1,2 (AUTHOR) reza5575@cnu.ac.kr, Lee, Kyu-Ho1,2 (AUTHOR) elkyu0927@cnu.ac.kr, Ahmed, Shahriar2 (AUTHOR), Cho, Yeon Jin3 (AUTHOR) yeon0830@korea.kr, Noh, Dong Hee4 (AUTHOR) dhee.noh@keti.re.kr, Chung, Sun-Ok1,2 (AUTHOR) sochung@cnu.ac.kr
Publikováno v: Agronomy. Sep2024, Vol. 14 Issue 9, p2043. 28p.
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6
Report
Performance Analysis of Support Vector Machine (SVM) on Challenging Datasets for Forest Fire Detection
Autor: Kar, Ankan, Nath, Nirjhar, Kemprai, Utpalraj, Aman
Publikováno v: Int. J. Communications, Network and System Sciences, 17, 11-29 (2024)
This article delves into the analysis of performance and utilization of Support Vector Machines (SVMs) for the critical task of forest fire detection using image datasets. With the increasing threat of forest fires to ecosystems and human settlements
Externí odkaz: http://arxiv.org/abs/2401.12924
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7
Akademický článek
Forecasting for Haditha reservoir inflow in the West of Iraq using Support Vector Machine (SVM).
Autor: Mahmood, Othman A.1 (AUTHOR), Sulaiman, Sadeq Oleiwi1 (AUTHOR), Al-Jumeily, Dhiya2 (AUTHOR) d.aljumeily@ljmu.ac.uk
Publikováno v: PLoS ONE. 9/6/2024, Vol. 19 Issue 9, p1-21. 21p.
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8
Akademický článek
Classification of Northern Thai Rice Varieties Using Random Forest (RF) and Support Vector Machine (SVM) on Google Earth Engine with Sentinel Imagery: A Case Study in Buak Khang Subdistrict, San Kamphaeng District, Chiang Mai Province.
Autor: Boonma, R.1 raweewan_b@cmu.ac.th, Suwanprasit, C.1 chanida.suwanprasit@cmu.ac.th, Homhuan, S.1 sakda.homhuan@cmu.ac.th, Shahnawaz2 s.shahnawaz@sbg.ac.at
Publikováno v: International Journal of Geoinformatics. Sep2024, Vol. 20 Issue 9, p27-42. 16p.
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9
Akademický článek
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10
Akademický článek
An integrated approach of support vector machine (SVM) and weight of evidence (WOE) techniques to map groundwater potential and assess water quality
Autor: Malik Talha Riaz, Muhammad Tayyib Riaz, Adnanul Rehman, Ahmed Ali Bindajam, Javed Mallick, Hazem Ghassan Abdo
Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract This study addresses the critical need for effective groundwater (GW) management in Muzaffarabad, Pakistan, amidst challenges posed by rapid urbanization and population growth. By integrating Support Vector Machine (SVM) and Weight of Eviden
Externí odkaz: https://doaj.org/article/6033fe274a1d48b9b23dba92032ec032
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