Zobrazeno 1 - 10
of 681
pro vyhledávání: '"Hybrid machine learning"'
Autor:
Muhammad Shoaib Bhutta, Yang Li, Muhammad Abubakar, Fahad M. Almasoudi, Khaled Saleem S. Alatawi, Mohammad R. Altimania, Maged Al-Barashi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-25 (2024)
Abstract The fourth energy revolution is characterized by the incorporation of renewable energy supplies into intelligent networks. As the world is shifting towards cleaner energy sources, there is a need for efficient and reliable methods to predict
Externí odkaz:
https://doaj.org/article/44d39fc78dc94d0db4aa358e3b214fb5
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-27 (2024)
Abstract The Electrocardiogram (ECG) records are crucial for predicting heart diseases and evaluating patient’s health conditions. ECG signals provide essential peak values that reflect reliable health information. Analyzing ECG signals is a fundam
Externí odkaz:
https://doaj.org/article/6d3f607dca6244a28675343e55b4ddcb
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Ensuring the security of China’s rice harvest is imperative for sustainable food production. The existing study addresses a critical need by employing a comprehensive approach that integrates multi-source data, including climate, remote se
Externí odkaz:
https://doaj.org/article/9ee3ef72a06a43f99e33e4a43d7c94db
Publikováno v:
Journal of Engineering and Applied Science, Vol 71, Iss 1, Pp 1-32 (2024)
Abstract It is costly, time-consuming, and difficult to measure unconfined compressive strength (UCS) using typical laboratory procedures, particularly when dealing with weak, extremely porous, and fractured rock. By efficiently choosing the variable
Externí odkaz:
https://doaj.org/article/b150733a0743497186440c5d76af6099
Publikováno v:
Journal of Agrometeorology, Vol 26, Iss 3 (2024)
Paddy is a major crop in India which is highly affected by the weather variables resulting in drastic reduction of its yield; adverse all the variables drastically reduce the paddy yield. In this research, machine learning model was developed for pre
Externí odkaz:
https://doaj.org/article/441dc6c043324b94b6cd363046fa0dc3
Publikováno v:
e-Prime: Advances in Electrical Engineering, Electronics and Energy, Vol 9, Iss , Pp 100636- (2024)
Forecasting solar power generation (SPG) is vital for the development and planning of power systems, offering significant benefits in terms of technical performance and financial efficiency. It enhances system reliability, safety, stability and it re
Externí odkaz:
https://doaj.org/article/cc8c536f05ff4b5f8953fa2d917da67d
Autor:
Stephen Fox, Vitor Fortes Rey
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 1, Pp 580-592 (2024)
Hybrid machine learning encompasses predefinition of rules and ongoing learning from data. Human organizations can implement hybrid machine learning (HML) to automate some of their operations. Human organizations need to ensure that their HML impleme
Externí odkaz:
https://doaj.org/article/69297ae668554396ad131f5afb523f16
Publikováno v:
Case Studies in Construction Materials, Vol 21, Iss , Pp e03439- (2024)
With the development of green, low-carbon, and sustainable economic systems, the issues of high pollution and energy consumption in construction materials have become increasingly prominent. This study focuses on adopting one-part geopolymer (OPG) in
Externí odkaz:
https://doaj.org/article/4bb95791abcd420f9f00a1345a886cab
Publikováno v:
Case Studies in Construction Materials, Vol 20, Iss , Pp e03030- (2024)
The construction industry is making efforts to reduce the environmental impact of cement production in concrete by incorporating alternative and supplementary cementitious materials, as well as lowering carbon emissions. One such material that has ga
Externí odkaz:
https://doaj.org/article/fd32f9f3d0d043efa6fcd6682a9d47a2
Autor:
Abul Kashem, Rezaul Karim, Somir Chandra Malo, Pobithra Das, Shuvo Dip Datta, Mohammad Alharthai
Publikováno v:
Case Studies in Construction Materials, Vol 20, Iss , Pp e02991- (2024)
Ultra-high-performance concrete (UHPC) is a cutting-edge and advanced construction material known for its exceptional mechanical properties and durability. Recently, machine learning (ML) methods have played a pivotal role in predicting the compressi
Externí odkaz:
https://doaj.org/article/6138b04f78464b19a6491453515418c3