Unemployment rate forecasting: LSTM-GRU hybrid approach

M Yurtsever - Journal for Labour Market Research, 2023 - Springer
Unemployment rates provide information on the economic development of countries.
Unemployment is not only an economic problem but also a social one. As such …

Unemployment Rate Prediction Using a Hybrid Model of Recurrent Neural Networks and Genetic Algorithms

K Mero, N Salgado, J Meza, J Pacheco-Delgado… - Applied Sciences, 2024 - mdpi.com
Unemployment, a significant economic and social challenge, triggers repercussions that
affect individual workers and companies, generating a national economic impact …

Comparison of ARIMA, SutteARIMA, and holt-winters, and NNAR models to predict food grain in India

AS Ahmar, PK Singh, R Ruliana, AK Pandey, S Gupta - Forecasting, 2023 - mdpi.com
The agriculture sector plays an essential function within the Indian economic system.
Foodgrains provide almost all the calories and proteins. This paper aims to compare ARIMA …

[HTML][HTML] Unemployment rates forecasting with grey-based models in the post-COVID-19 period: A case study from Vietnam

PH Nguyen, JF Tsai, IE Kayral, MH Lin - Sustainability, 2021 - mdpi.com
The Coronavirus (COVID-19) pandemic has had a significant impact on most countries'
social and economic perspectives worldwide. Unemployment has become a vital challenge …

Modeling the number of unemployed in South Sumatra Province using the exponential smoothing methods

R Gustriansyah, J Alie, N Suhandi - Quality & Quantity, 2023 - Springer
The number of open unemployment in South Sumatra Province from year to year is found to
be unstable. It can cause serious developmental problems. One solution to this problem is to …

Time series trend detection and forecasting of SUHI in Tabriz, Iran

MAK Vatan, M Nemati, A Sekertekin, MZ Aslkhiabani - Urban Climate, 2025 - Elsevier
This study aims to evaluate the seasonal daytime and nighttime SUHI trend of Tabriz, using
the non-parametric Mann-Kendall, Innovative Trend Analysis, and MODIS data, and to …

COMPARATIVE PERFORMANCE OF ARIMA, SARIMA AND GARCH MODELS IN MODELLING AND FORECASTING UNEMPLOYMENT AMONG ASEAN-5 …

KY Ng, Z Zainal, S Samsudin - International Journal of …, 2023 - publisher.unimas.my
Unemployment, especially after the COVID-19 pandemic, is a critical issue for any country
as it has economic and social ramifications. Consequently, forecasting unemployment …

[HTML][HTML] A comparative analysis of variants of machine learning and time series models in predicting women's participation in the labor force

R Elstohy, N Aneis, EM Ali - PeerJ Computer Science, 2024 - peerj.com
Labor force participation of Egyptian women has been a chronic economic problem in Egypt.
Despite the improvement in the human capital front, whether on the education or health …

A hybrid approach based on seasonal autoregressive integrated moving average and neural network autoregressive models to predict scorpion sting incidence in el …

S Zenia, M L'Hadj, S Selmane - Journal of Research in Health …, 2023 - pmc.ncbi.nlm.nih.gov
Background: This study was designed to find the best statistical approach to scorpion sting
predictions. Study Design: A retrospective study. Methods: Multiple regression, seasonal …

Forecasting unemployment rate in South Africa with unexpected events using robust estimators

SS Nkoane, SM Seeletse - International Journal of Economics and …, 2021 - agbioforum.org
The purpose of the study is to build the time series model and forecast the unemployment
rate in South Africa in the presence of the unexpected events or contamination of data using …