Results 101 to 110 of about 58,557 (260)

Trendelenburg positioning with or without norepinephrine infusion for haemodynamic support in anaesthetised hypovolemic horses

Equine Veterinary Journal, EarlyView.
Abstract Background Intraoperative haemorrhage during equine anaesthesia is a rare but potentially fatal complication requiring prompt haemodynamic support. Postural manoeuvres such as Trendelenburg (TL) positioning and vasopressor support augment venous return and improve cardiac output (CO), yet their efficacy in anaesthetised hypovolemic horses ...
Vaidehi V. Paranjape, Klaus Hopster, Ismar Lutvikadic, Bernd Driessen   +3 more
wiley   +1 more source

Discussion of the article “Prediction of creep of recycled aggregate concrete using back‐propagation neural network and support vector machine”

, 2023
Structural Concrete, EarlyView.
Nikola Tošić, Albert de la Fuente, Snežana Marinković   +2 more
wiley   +1 more source

Verteilungsfragen in Deutschland: Herausforderungen der Messung und der zielgerichteten Umverteilung

Wirtschaftsdienst, 2020
Lars P. Feld, Jan L. Fries, Malte Preuß, Christoph M. Schmidt   +3 more
doaj   +1 more source

Zuwanderung zum Zweck der Erwerbstätigkeit

ZUWANDERUNG ZUM ZWECK DER ERWERBSTÄTIGKEIT Zuwanderung zum Zweck der Erwerbstätigkeit / (SVR) gGmbH, Sachverständigenrat für Integration und Migration (Rights reserved) (-
(SVR) gGmbH, Sachverständigenrat für Integration und Migration
core  

Hybrid Temporal Autoencoder and Similarity Matching for Low Aggregation Level Long Time Series Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT Deep learning‐based long time series forecasting (LTSF) has achieved high accuracy by effectively capturing the underlying trends, seasonality, and temporal dependencies within time series data. However, at the individual entity level, termed the low aggregation level (LAL), intermittency, irregularity, and data sparsity undermine the ...
Hanbyeol Park, Sunghyun Sim, Kikun Park, Yongjae Lee, Eunhee Park, Hyerim Bae   +5 more
wiley   +1 more source

PERFORMANCE EVALUATION OF SEASONAL ARIMA-SVR AND SEASONAL ARIMAX-SVR HYBRID METHODS ON FORECASTING PADDY PRODUCTION [PDF]

This study explores advances in forecasting time series data by combining linear and non-linear models. Traditional methods such as ARIMA and its variant ARIMAX are effective for linear data but have limitations when dealing with non-linearity.
Afendi, Farit Mochamad, Sumertajaya, I Made, Risnawati, I'lmisukma   +2 more
core   +1 more source

Machine Learning‐Based Estimation of Reference Evapotranspiration and Crop Coefficients for Wheat Under Diverse Climatic Conditions

Irrigation and Drainage, EarlyView.
ABSTRACT Accurate estimation of reference evapotranspiration (ET0) and crop coefficients (Kc) is critical for irrigation planning, particularly in data‐limited regions where agriculture dominates freshwater consumption. Although machine learning (ML) methods have been widely applied to ET0 and Kc estimation, most studies address these parameters ...
Ilker Angin, Hasan Er, Mete Yaganoglu, Muhammed Sungur Demir, Abdullah Muratoglu   +4 more
wiley   +1 more source

SVR predictive model parameters.

, 2018
SVR predictive model parameters.
Azadeh Ansari (5814800), Leily Farrokhvar (5814797), Behrooz Kamali (5814803)   +2 more
core   +1 more source

Integrated Bioinformatics Analysis Identifies FCER1G, IL1R2, and BST1 as Diagnostic Biomarkers and Therapeutic Targets in Sepsis

Journal of Clinical Laboratory Analysis, EarlyView.
Integrative bioinformatics and experimental validation of FCER1G, IL1R2, and BST1 as biomarkers and therapeutic targets in neonatal sepsis. ABSTRACT Background Sepsis remains difficult to diagnose since blood culture has low sensitivity and current biomarkers lack sufficient specificity.
Junjie Li, Guanghui Xiu, Ping Liu, Xianzhong Chen, Kailv Zhou, Yunfeng Yang   +5 more
wiley   +1 more source

Deviation in SVR [30].

, 2018
Deviation in SVR [30].
Azadeh Ansari (5814800), Leily Farrokhvar (5814797), Behrooz Kamali (5814803)   +2 more
core   +1 more source