Zobrazeno 1 - 10
of 517
pro vyhledávání: '"Extra Trees"'
Publikováno v:
Jurnal Sisfokom, Vol 13, Iss 3, Pp 337-345 (2024)
This research aims to analyze sentiment on DANA application reviews to find out user perceptions by comparing Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Extra Trees Classifier classification methods. DANA application revie
Externí odkaz:
https://doaj.org/article/03f7db5336314cd595e3b489b1941909
Autor:
V. Gómez-Escalonilla, E. Montero-González, S. Díaz-Alcaide, M. Martín-Loeches, M. Rodríguez del Rosario, P. Martínez-Santos
Publikováno v:
Applied Water Science, Vol 14, Iss 12, Pp 1-19 (2024)
Abstract Effective monitoring of groundwater contamination is crucial to protect human livelihoods and ecosystems. This paper presents a machine learning-based approach to improve groundwater monitoring networks by providing predictions of groundwate
Externí odkaz:
https://doaj.org/article/acf77af4cefe4a7399d273a144965eec
Autor:
Yi Lyu, Hai-Mei Wu, Hai-Xia Yan, Rui Guo, Yu-Jie Xiong, Rui Chen, Wen-Yue Huang, Jing Hong, Rong Lyu, Yi-Qin Wang, Jin Xu
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-21 (2024)
Abstract Background Coronary artery disease (CAD) is a major global cardiovascular health threat and the leading cause of death in many countries. The disease has a significant impact in China, where it has become the leading cause of death. There is
Externí odkaz:
https://doaj.org/article/aa428289c49a4c078a09504e3f0fafdc
Publikováno v:
Alexandria Engineering Journal, Vol 103, Iss , Pp 51-59 (2024)
Metamaterial absorbers (MMAs) have tremendous potential for controlling and modulating Terahertz electromagnetic (EM) waves. It is challenging to design MMAs for optimal performance using conventional methods due to their time-consuming and computati
Externí odkaz:
https://doaj.org/article/e4dbf00a4c4042098d2ce27760bd8c02
Autor:
Guy M. Toche Tchio, Joseph Kenfack, Joseph Voufo, Yves Abessolo Mindzie, Blaise Fouedjou Njoya, Sanoussi S. Ouro-Djobo
Publikováno v:
AIMS Energy, Vol 12, Iss 4, Pp 727-750 (2024)
The application of machine learning techniques for monitoring and diagnosing faults in photovoltaic (PV) systems has been shown to enhance the reliability of PV power generation. This research introduced a novel machine learning classifier for fault
Externí odkaz:
https://doaj.org/article/5e66bd6552f64d60b8e4feee1051eff5
Autor:
Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani
Publikováno v:
Baghdad Science Journal, Vol 21, Iss 12 (2024)
Accurately predicting student performance remains a significant challenge in the educational sector. Identifying students who need additional support early can significantly impact their academic outcomes. This study aims to develop an intelligent so
Externí odkaz:
https://doaj.org/article/8e7307cac0854ae99d003d127379edb2
Autor:
Jamei, Mehdi a, c, g, ⁎, Yaqoob, Nauman b, Farooque, Aitazaz A. a, b, ⁎, Ali, Mumtaz d, Malik, Anurag e, Esau, Travis J. f, Hu, Yulin b
Publikováno v:
In Smart Agricultural Technology March 2025 10
Autor:
S. Roopashree, J. Anitha, Suryateja Challa, T. R. Mahesh, Vinoth Kumar Venkatesan, Suresh Guluwadi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Inadequate conservation of medicinal plants can affect their productivity. Traditional assessments and strategies are often time-consuming and linked with errors. Utilizing herbs has been an integral part of the traditional system of medicin
Externí odkaz:
https://doaj.org/article/f24431f92618447b804f7ff21c59114d
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-13 (2024)
Abstract Analyzing songs is a problem that is being investigated to aid various operations on music access platforms. At the beginning of these problems is the identification of the person who sings the song. In this study, a singer identification ap
Externí odkaz:
https://doaj.org/article/b70c3c3c102944b1a296485a33ed55c9
Publikováno v:
IEEE Access, Vol 12, Pp 117761-117786 (2024)
In this study, we present an innovative network intrusion detection system (IDS) tailored for Internet of Things (IoT)-based smart home environments, offering a novel deployment scheme that addresses the full spectrum of network security challenges.
Externí odkaz:
https://doaj.org/article/8639dd3563c44611bee0b654b7a56e85