Carbon emission prediction models: A review

Y Jin, A Sharifi, Z Li, S Chen, S Zeng, S Zhao - Science of the Total …, 2024 - Elsevier
Amidst growing concerns over the greenhouse effect, especially its consequential impacts,
establishing effective Carbon Emission Prediction Models (CEPMs) to comprehend and …

Forecasting of daily new lumpy skin disease cases in Thailand at different stages of the epidemic using fuzzy logic time series, NNAR, and ARIMA methods

V Punyapornwithaya, O Arjkumpa, N Buamithup… - Preventive Veterinary …, 2023 - Elsevier
Lumpy skin disease (LSD) is an important transboundary disease affecting cattle in
numerous countries in various continents. In Thailand, LSD is regarded as a serious threat …

Epidemiological Forecasting Models Using ARIMA, SARIMA, and Holt–Winter Multiplicative Approach for Pakistan

M Riaz, M Hussain Sial, S Sharif… - … of Environmental and …, 2023 - Wiley Online Library
Background of the Study. Statistical models have been extensively used in modeling and
forecasting the different fields of agriculture, economics, social sciences, and medical …

Pakistan CO2 Emission Modelling and Forecasting: A Linear and Nonlinear Time Series Approach

K Tawiah, M Daniyal, M Qureshi - Journal of Environmental and …, 2023 - Wiley Online Library
Pakistan is considered among the top five countries with the highest CO2 emissions
globally. This calls for pragmatic policy implementation by all stakeholders to bring finality to …

A comparative analysis of traditional SARIMA and machine learning models for CPI data modelling in Pakistan

M Qureshi, A Khan, M Daniyal… - … Intelligence and Soft …, 2023 - Wiley Online Library
Background. In economic theory, a steady consumer price index (CPI) and its associated
low inflation rate (IR) are very much preferred to a volatile one. CPI is considered a major …

[HTML][HTML] Trends and multi-model prediction of hepatitis B incidence in Xiamen

R Zhang, H Mi, T He, S Ren, R Zhang, L Xu… - Infectious Disease …, 2024 - Elsevier
Background This study aims to analyze the trend of Hepatitis B incidence in Xiamen City
from 2004 to 2022, and to select the best-performing model for predicting the number of …

Collateral effects of COVID-19 countermeasures on hepatitis E incidence pattern: a case study of china based on time series models

Y Qin, H Peng, J Li, J Gong - BMC Infectious Diseases, 2024 - Springer
Background There are abundant studies on COVID-19 but few on its impact on hepatitis E.
We aimed to assess the effect of the COVID-19 countermeasures on the pattern of hepatitis …

Comparison of Artificial Intelligence and Machine Learning Methods Used in Electric Power System Operation

M Hallmann, R Pietracho, P Komarnicki - Energies, 2024 - mdpi.com
The methods of artificial intelligence (AI) have been used in the planning and operation of
electric power systems for more than 40 years. In recent years, due to the development of …

Forecasting meteorological indicators based on neural networks

V Kan, O Alsova - 2022 IEEE International Multi-Conference on …, 2022 - ieeexplore.ieee.org
The results of the development, software implementation and study of the applicability of the
neural models for the prediction of meteorological indicators are presented in this paper …

Time series forecasting of the COVID-19 pandemic: a critical assessment in retrospect

M Güngör - Alphanumeric Journal, 2023 - dergipark.org.tr
The COVID-19 pandemic is perceived by many to have run its course, and forecasting its
progress is no longer a topic of much interest to policymakers and researchers as it once …