Zobrazeno 1 - 10
of 424
pro vyhledávání: '"Intelligent model"'
Publikováno v:
HighTech and Innovation Journal, Vol 5, Iss 2, Pp 213-230 (2024)
The relevance of the study is due to the need to improve electric drive systems operated in harsh conditions. The goal of the study is to create a model for assessing the state of stability of the electric drive of an ore mill using machine learning
Externí odkaz:
https://doaj.org/article/2c8fc1a7955e4c5fa834a8e9711fbf37
Autor:
Atena Mahmoudzadeh, Behnam Amiri-Ramsheh, Saeid Atashrouz, Ali Abedi, Meftah Ali Abuswer, Mehdi Ostadhassan, Ahmad Mohaddespour, Abdolhossein Hemmati-Sarapardeh
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract The growing application of carbon dioxide (CO2) in various environmental and energy fields, including carbon capture and storage (CCS) and several CO2-based enhanced oil recovery (EOR) techniques, highlights the importance of studying the ph
Externí odkaz:
https://doaj.org/article/7ed70740d17c449b982615ed9e018c67
Publikováno v:
Advances in Environmental Technology, Vol 10, Iss 2, Pp 102-117 (2024)
Suspended sediment load is an indicator of erosion in watersheds. Therefore, accurately estimating the daily suspended sediment load (DSSL) is an important issue in river engineering. In this research, Artificial Neural Networks (ANN), Genetic Expres
Externí odkaz:
https://doaj.org/article/de6ed053dcd24ea0946db4182d0928c6
Publikováno v:
Journal of Hydroinformatics, Vol 26, Iss 1, Pp 175-188 (2024)
In this study, a support vector machine (SVM) and three optimization algorithms are used to develop a discharge coefficient (Cd) prediction model for the semi-circular side weir (SCSW). After that, we derived the input and output parameters of the mo
Externí odkaz:
https://doaj.org/article/d8fac7fc6fb54fe2994c33d14aa9ca3e
Autor:
Muhammad Dawood, Chunagbai Xiao, Shanshan Tu, Faiz Abdullah Alotaibi, Mrim M. Alnfiai, Muhammad Farhan
Publikováno v:
PeerJ Computer Science, Vol 10, p e2027 (2024)
This article explores detecting and categorizing network traffic data using machine-learning (ML) methods, specifically focusing on the Domain Name Server (DNS) protocol. DNS has long been susceptible to various security flaws, frequently exploited o
Externí odkaz:
https://doaj.org/article/c42929799a264c9e9c8b5025477a1b44
Autor:
M. Almetwally Ahmed, S. Samuel Li
Publikováno v:
Hydrology, Vol 11, Iss 9, p 151 (2024)
River discharge is an essential input to hydrosystem projects. This paper aimed to modify the group method of data handling (GMDH) to create a new artificial intelligent forecast model (abbreviated as MGMDH) for predicting discharges at river cross-s
Externí odkaz:
https://doaj.org/article/aae80bd5313f45a58fff5a2047d8753b
Autor:
Hristo Ivanov Beloev, Stanislav Radikovich Saitov, Antonina Andreevna Filimonova, Natalia Dmitrievna Chichirova, Oleg Evgenievich Babikov, Iliya Krastev Iliev
Publikováno v:
Energies, Vol 17, Iss 14, p 3511 (2024)
The correct prediction of heating network pipeline failure rates can increase the reliability of the heat supply to consumers in the cold season. However, due to the large number of factors affecting the corrosion of underground steel pipelines, it i
Externí odkaz:
https://doaj.org/article/c4850718a559435e81fba8028eaafc7b
Autor:
REN Pei-zhong, WANG Zhu
Publikováno v:
Zhihui kongzhi yu fangzhen, Vol 42, Iss 2, Pp 130-136 (2023)
In view of the shortcomings of the existing human-machine command countermeasure system in the design research of the rules, according to the typical structure of human-machine command countermeasure system and rule reasoning operation mechanism, and
Externí odkaz:
https://doaj.org/article/0b80253fb6e6435384b55f200d5fd2d3
Autor:
Łukasz Klimkowski
Publikováno v:
Energies, Vol 17, Iss 13, p 3091 (2024)
The potential of unconventional hydrocarbon resources has been unlocked since the hydraulic fracturing technique in combination with long horizontal wells was applied to develop this type of reservoir economically. The design and optimization of the
Externí odkaz:
https://doaj.org/article/a1925e8de8414d73bd16988e4224deba
Publikováno v:
علوم آب و خاک, Vol 26, Iss 4, Pp 281-297 (2023)
In this study, the accuracy of the Adaptive Network-Based Fuzzy Inference System (ANFIS) in integrating with the Gray Wolf Algorithm (ANFIS-GWO) in predicting groundwater level was evaluated for the first time using unpublished observational data fro
Externí odkaz:
https://doaj.org/article/cb530ab0351f4165b38804c9ac5d2fd7