Zobrazeno 1 - 10
of 13 838
pro vyhledávání: '"support vector machine (svm)"'
Autor:
Wang, Mei-Hsin, Che, Hui-Chung
Publikováno v:
Journal of Intellectual Capital, 2024, Vol. 25, Issue 7, pp. 129-150.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JIC-12-2023-0286
Autor:
Bian Chao, Huang Guangqiu
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-28 (2024)
Abstract Amid escalating tension between environmental conservation and economic development, the imperative to enhance air quality has become increasingly urgent. This study elucidates a sophisticated approach for the assessment and remediation of a
Externí odkaz:
https://doaj.org/article/ee1bd14ad22945b79ba8f02e8037dc87
Publikováno v:
发电技术, Vol 45, Iss 4, Pp 744-752 (2024)
ObjectivesTo enhance the intelligent management of substation equipment maintenance, timely identify and mitigate the risks of failures caused by device overheating, and ensure the safe and stable operation of the power grid, the temperature situatio
Externí odkaz:
https://doaj.org/article/cae27b697a554c7b9436f9bba67d07fe
Publikováno v:
BioResources, Vol 19, Iss 4, Pp 7591-7605 (2024)
The increasing rates of illicit behaviors, particularly financial crimes, e.g., bank fraud and tax evasion, adversely affect national economies. In such cases, using nondestructive methods, scientists must evaluate relevant documents carefully to pre
Externí odkaz:
https://doaj.org/article/f4964148ad7b4f2fa80a3f104eae38f4
Automatic recognition system for concrete cracks with support vector machine based on crack features
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Cracks are a common problem in concrete surfaces. With the continuous optimization of machine vision-based inspection systems, effective crack detection and recognition is the core of the entire system. In this study, support vector machine
Externí odkaz:
https://doaj.org/article/d7075b97d89443e68345fa2527b19c5a
Autor:
Sobhi M. Ghoneim, Zakaria Hamimi, Kamal Abdelrahman, Mohamed A. Khalifa, Mohamed Shabban, Ashraf S. Abdelmaksoud
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract Machine learning and remote sensing techniques are widely accepted as valuable, cost-effective tools in lithological discrimination and mineralogical investigations. The current study represents an attempt to use machine learning classificat
Externí odkaz:
https://doaj.org/article/dc1235d291454b2a8a80955d33f1843e
Estimation of tunnel axial orientation in the interlayered rock mass using a comprehensive algorithm
Publikováno v:
Journal of Rock Mechanics and Geotechnical Engineering, Vol 16, Iss 7, Pp 2579-2590 (2024)
The axial selection of tunnels constructed in the interlayered soft-hard rock mass affects the stability and safety during construction. Previous optimization is primarily based on experience or comparison and selection of alternative values under sp
Externí odkaz:
https://doaj.org/article/9a5a07d59a0e4fa3ac09b5952ed0f080
Publikováno v:
Iranian Journal of Electrical and Electronic Engineering, Vol 20, Iss 2, Pp 85-96 (2024)
Cardiovascular arrhythmia is indeed one of the most prevalent cardiac issues globally. In this paper, the primary objective was to develop and evaluate an automated classification system. This system utilizes a comprehensive database of electro- card
Externí odkaz:
https://doaj.org/article/2641ab120d3648baae2cd7d0d02a2a77
Autor:
Mehdi Fuladipanah, Alireza Shahhosseini, Namal Rathnayake, Hazi Md. Azamathulla, Upaka Rathnayake, D. P. P. Meddage, Kiran Tota-Maharaj
Publikováno v:
Water Practice and Technology, Vol 19, Iss 6, Pp 2442-2459 (2024)
Measurement inaccuracies and the absence of precise parameters value in conceptual and analytical models pose challenges in simulating the rainfall–runoff modeling (RRM). Accurate prediction of water resources, especially in water scarcity conditio
Externí odkaz:
https://doaj.org/article/22380a96883a4454aa7afe15f7d3d075
Publikováno v:
Jurnal Riset Informatika, Vol 6, Iss 3, Pp 149-158 (2024)
This research aims to conduct sentiment analysis of e-grocery application reviews using the Support Vector Machine (SVM) algorithm. Sentiment analysis is used to distinguish between positive and negative reviews by users who have provided reviews so
Externí odkaz:
https://doaj.org/article/4e006fdd9cca4b1d806aaa4349adbf4d