[HTML][HTML] Forecasting: theory and practice

F Petropoulos, D Apiletti, V Assimakopoulos… - International Journal of …, 2022 - Elsevier
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

COVID-19: a comparison of time series methods to forecast percentage of active cases per population

V Papastefanopoulos, P Linardatos, S Kotsiantis - Applied sciences, 2020 - mdpi.com
The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing
governments to introduce extreme measures to reduce its spread. Being able to accurately …

[HTML][HTML] Forecasting the renewable energy consumption of the European countries by an adjacent non-homogeneous grey model

L Liu, L Wu - Applied Mathematical Modelling, 2021 - Elsevier
In this paper, a new adjacent non-homogeneous grey model was proposed to predict
renewable energy consumption in Europe. Based on the principle of adjacent accumulation …

RL-NSB: Reinforcement learning-based 5G network slice broker

V Sciancalepore, X Costa-Perez… - IEEE/ACM transactions …, 2019 - ieeexplore.ieee.org
Network slicing is considered one of the main pillars of the upcoming 5G networks. Indeed,
the ability to slice a mobile network and tailor each slice to the needs of the corresponding …

Review of forecasting methods to support photovoltaic predictive maintenance

J Ramirez-Vergara, LB Bosman, E Wollega… - Cleaner Engineering …, 2022 - Elsevier
Predictive maintenance models are thought to be a reliable alternative to costly on-site
maintenance techniques in the solar photovoltaic industry. They provide the owners with a …

Forecasting using simple exponential smoothing method

E Ostertagova, O Ostertag - Acta Electrotechnica et Informatica, 2012 - search.proquest.com
In the paper a relatively simple yet powerful and versatile technique for forecasting time
series data-simple exponential smoothing is described. The simple exponential smoothing …

Deep-learning model using hybrid adaptive trend estimated series for modelling and forecasting sales

MIA Efat, P Hajek, MZ Abedin, RU Azad… - Annals of Operations …, 2024 - Springer
Existing sales forecasting models are not comprehensive and flexible enough to consider
dynamic changes and nonlinearities in sales time-series at the store and product levels. To …

A hybrid demand forecasting model for greater forecasting accuracy: the case of the pharmaceutical industry

R Siddiqui, M Azmat, S Ahmed… - Supply Chain Forum: An …, 2022 - Taylor & Francis
In the era of modern technology, the competitive paradigm among organisations is changing
at an unprecedented rate. New success measures are applied to the organisation's supply …

The recursive grey model and its application

L Liu, S Liu, Z Fang, A Jiang, G Shang - Applied Mathematical Modelling, 2023 - Elsevier
The fixed structure parameters limit the performance of grey prediction algorithm in
unsmoothed time series prediction tasks. Based on the mechanism of recursive iteration, this …

Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model

M Arashi, MM Rounaghi - Future Business Journal, 2022 - Springer
The multi-fractal analysis has been applied to investigate various stylized facts of the
financial market including market efficiency, financial crisis, risk evaluation and crash …