Solar irradiance resource and forecasting: a comprehensive review

DS Kumar, GM Yagli, M Kashyap… - IET Renewable Power …, 2020 - Wiley Online Library
With the increase in demand for energy, penetration of alternative sources of energy in the
power grid has increased. Photovoltaic (PV) energy is the most common and popular form of …

An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments

M Gul, E Celik - Health Systems, 2020 - Taylor & Francis
Emergency departments (EDs) provide medical treatment for a broad spectrum of illnesses
and injuries to patients who arrive at all hours of the day. The quality and efficient delivery of …

Gated spiking neural P systems for time series forecasting

Q Liu, L Long, H Peng, J Wang, Q Yang… - … on Neural Networks …, 2021 - ieeexplore.ieee.org
Spiking neural P (SNP) systems are a class of neural-like computing models, abstracted by
the mechanism of spiking neurons. This article proposes a new variant of SNP systems …

MAG-D: A multivariate attention network based approach for cloud workload forecasting

YS Patel, J Bedi - Future Generation Computer Systems, 2023 - Elsevier
The Coronavirus pandemic and the work-from-home have drastically changed the working
style and forced us to rapidly shift towards cloud-based platforms & services for seamless …

Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study

VK Sudarshan, M Brabrand, TM Range… - Computers in Biology and …, 2021 - Elsevier
The volume of daily patient arrivals at Emergency Departments (EDs) is unpredictable and is
a significant reason of ED crowding in hospitals worldwide. Timely forecast of patients …

Modified genetic algorithm-based feature selection combined with pre-trained deep neural network for demand forecasting in outpatient department

S Jiang, KS Chin, L Wang, G Qu, KL Tsui - Expert systems with applications, 2017 - Elsevier
A well-performed demand forecasting can provide outpatient department (OPD) managers
with essential information for staff scheduling and rostering, considering the non-reservation …

Time series model for forecasting the number of new admission inpatients

L Zhou, P Zhao, D Wu, C Cheng, H Huang - BMC medical informatics and …, 2018 - Springer
Background Hospital crowding is a rising problem, effective predicting and detecting
managment can helpful to reduce crowding. Our team has successfully proposed a hybrid …

Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models

L Luo, L Luo, X Zhang, X He - BMC health services research, 2017 - Springer
Background Accurate forecasting of hospital outpatient visits is beneficial for the reasonable
planning and allocation of healthcare resource to meet the medical demands. In terms of the …

Combining deep neural network and bibliometric indicator for emerging research topic prediction

Z Liang, J Mao, K Lu, Z Ba, G Li - Information Processing & Management, 2021 - Elsevier
Predicting emerging research topics is important to researchers and policymakers. In this
study, we propose a two-step solution to the problem of emerging topic prediction. The first …

A long-term multivariate time series forecasting network combining series decomposition and convolutional neural networks

X Wang, H Liu, J Du, X Dong, Z Yang - Applied Soft Computing, 2023 - Elsevier
In multivariate time series forecasting tasks, expanding forecast length and improving
forecast efficiency is an urgent need for practical applications. Accurate long-term …