Results 131 to 140 of about 153,678 (301)
Forecasting Wheat Production in Libya Using ARIMA Model-ARIMA
The wheat crop is a strategic crop in Libya as a food crop and a raw material for some food industries. The study aimed to predict the amount of wheat production in context of Libya during the next six years from 2023-2028. The Auto-regressive Integrated Moving Average (ARIMA) model has been used and relied on Food and Agriculture Organization data ...
openaire +1 more source
A Novel Approach to Forecasting After Large Forecast Errors
ABSTRACT A sequence of increasingly large same‐sign 1‐step‐ahead forecast errors are most likely due to a sudden unexpected shift. Large forecast errors can be expensive, but also contain valuable information. Impulse indicators acting as intercept corrections to set forecasts back on track can be quickly tested for replacing outliers, a location shift
Jennifer L. Castle +2 more
wiley +1 more source
Seasonal Decomposition‐Enhanced Deep Learning Architecture for Probabilistic Forecasting
ABSTRACT Time series decomposition as a general preprocessing method has been widely used in the field of time series forecasting. However, since the future is unknown, this preprocessing practice is limited in realistic forecasting, especially in real‐time forecasting scenarios.
Keyan Jin +1 more
wiley +1 more source
PROPERTIES OF PREDICTORS IN OVERDIFFERENCED NEARLY NONSTATIONARY AUTOREGRESSION [PDF]
This paper analyzes the effect of overdifferencing a stationary AR(p+1) process whoselargest root is near unity. It is found that if the process is nearly nonstationary, the estimators ofthe overdifferenced model ARIMA (p, 1, 0) are root-T consistent. It
Daniel Peña, Ismael Sánchez
core
ABSTRACT Advances in hepatology—such as noninvasive serum biomarkers (e.g., Fibrosure since 2004), imaging techniques (e.g., MR Elastography since 2009 and FibroScan since 2013), and effective direct‐acting antivirals for the treatment of chronic hepatitis C—have likely influenced liver biopsy practices.
Nazire E. Albayrak +8 more
wiley +1 more source
Noppakun Thammatacharee, 1, 2 Rapeepong Suphanchaimat 2, 3 1Health Systems Research Institute, Nonthaburi, Thailand; 2International Health Policy Program (IHPP), the Ministry of Public Health, Nonthaburi, Thailand; 3Division of Epidemiology ...
Thammatacharee N, Suphanchaimat R
doaj
Edge‐Oriented DoS/DDoS Intrusion Detection and Supervision Platform
ABSTRACT This work presents an Edge Node‐Oriented DoS/DDoS Intrusion Detection and Monitoring Platform, a novel anomaly detection system based on temporal analysis with machine learning (ML) and deep learning (DL) algorithms, specifically designed to operate on edge servers with limited resources.
Geraldo Eufrazio Martins Júnior +3 more
wiley +1 more source

