Výsledky vyhledávání - "eXtreme Gradient Boosting algorithm"

Akademický článek

Decoding the synergy: unveiling gradient boosting regression model for multivariate quantitation of pioglitazone, alogliptin and glimepiride in pure and tablet dosage forms

Autor: Mahmoud M. Elkhoudary, Aya A. Marie, Sherin F. Hammad, Mohamed M. Salim, Amira H. Kamal

Publikováno v: BMC Chemistry, Vol 18, Iss 1, Pp 1-13 (2024)

Abstract This study represents a comparison among the performances of four multivariate procedures: partial least square (PLS) and artificial neural networks (ANN) in addition to support vector regression (SVR) and extreme gradient boosting (XG Boost

Externí odkaz: https://doaj.org/article/9f1c1343a9e74c53b0b827fd99b2c718

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Akademický článek

An integrated cloud system based serverless android app for generalised tractor drawbar pull prediction model using machine learning

Autor: Harsh Nagar, Rajendra Machavaram, Ambuj, Peeyush Soni, Subhajit Saha, T. Subhash Chandra Bose

Publikováno v: Systems Science & Control Engineering, Vol 12, Iss 1 (2024)

Knowing tractor drawbar pull is crucial to ensure the tractor can handle the required workload efficiently and safely, preventing soil damage and optimising field productivity. The present study proposes a novel approach for tractor drawbar pull pred

Externí odkaz: https://doaj.org/article/c0a3baaad9104e48af44c4e409709736

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Akademický článek

Prediction of Ionospheric Scintillations Using Machine Learning Techniques during Solar Cycle 24 across the Equatorial Anomaly

Autor: Sebwato Nasurudiin, Akimasa Yoshikawa, Ahmed Elsaid, Ayman Mahrous

Publikováno v: Atmosphere, Vol 15, Iss 10, p 1213 (2024)

Ionospheric scintillation is a pressing issue in space weather studies due to its diverse effects on positioning, navigation, and timing (PNT) systems. Developing an accurate and timely prediction model for this event is crucial. In this work, we dev

Externí odkaz: https://doaj.org/article/53585aa945f24ddd9c00666ee670140f

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Akademický článek

Early prediction of battery degradation in grid-scale battery energy storage system using extreme gradient boosting algorithm

Autor: Chico Hermanu Brillianto Apribowo, Sasongko Pramono Hadi, Franscisco Danang Wijaya, Mokhammad Isnaeni Bambang Setyonegoro, Sarjiya

Publikováno v: Results in Engineering, Vol 21, Iss , Pp 101709- (2024)

The growth of battery energy storage systems (BESS) is caused by the variability and intermittent nature of high demand and renewable power generation at the network scale. In the context of BESS, Lithium-ion (Li-ion) battery occupies a crucial posit

Externí odkaz: https://doaj.org/article/81be6e336e14402c80fb86221fe34894

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Akademický článek

Comparison of Two Methods, Gradient Boosting and Extreme Gradient Boosting to Pre- dict Survival in Covid-19 Data

Autor: Nadiasadat Taghavi Razavizadeh, Maryam Salari, Mostafa Jafari, Ehsan Sabaghian, Vahid Ghavami

Publikováno v: Journal of Biostatistics and Epidemiology, Vol 9, Iss 3 (2023)

Introduction: The present study discusses the importance of having a predictive method to determine the prognosis of patients with diseases like Covid-19. This method can assist physicians in making treatment decisions that improve survival rates and

Externí odkaz: https://doaj.org/article/101467ecd14a4b9b9d357098a75c8465

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Akademický článek

A Sustainable Approach to Asthma Diagnosis: Classification with Data Augmentation, Feature Selection, and Boosting Algorithm

Autor: Zne-Jung Lee, Ming-Ren Yang, Bor-Jiunn Hwang

Publikováno v: Diagnostics, Vol 14, Iss 7, p 723 (2024)

Asthma is a diverse disease that affects over 300 million individuals globally. The prevalence of asthma has increased by 50% every decade since the 1960s, making it a serious global health issue. In addition to its associated high mortality, asthma

Externí odkaz: https://doaj.org/article/c34471b39ca14d3da31ed60fc7fb2f4c

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Prediction of strata behaviors law based on GRU and XGBoost

Autor: CHAI Jing, LIU Yilong, WANG Anyi, QU Shijia, OUYANG Yibo

Publikováno v: Gong-kuang zidonghua, Vol 48, Iss 1, Pp 91-97 (2022)

In the process of using optical fiber frequency shift value monitored by optical fiber sensor to characterize the strata behaviors law, the data collected by the sensor is missing, and the strata behaviors law can not be accurately predicted. In orde

Externí odkaz: https://doaj.org/article/16c0494d38f14bf2bda16f7938cc908c

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