Comparing Time-Series Analysis Approaches Utilized in Research Papers to Forecast COVID-19 Cases in Africa: A Literature Review
This literature review aimed to compare various time-series analysis approaches utilized in forecasting COVID-19 cases in Africa. The study involved a methodical search for English-language research papers published between January 2020 and July 2023, focusing specifically on papers that utilized time-series analysis approaches on COVID-19 datasets in Africa. A variety of databases including PubMed, Google Scholar, Scopus, and Web of Science were utilized for this process. The research papers underwent an evaluation process to extract relevant information regarding the implementation and performance of the time-series analysis models. The study highlighted the different methodologies employed, evaluating their effectiveness and limitations in forecasting the spread of the virus. The result of this review could contribute deeper insights into the field, and future research should consider these insights to improve time series analysis models and explore the integration of different approaches for enhanced public health decision-making.
Code (0)
등록된 구현이 없습니다.
Tasks
Decision MakingTime SeriesTime Series AnalysisSimilar Papers 제목 키워드 기반
Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants
In this study, we analyze behaviours of the well-known CMA-ES by extracting the time-series features on its dynamic strategy parameters. An extensive experiment was conducted on twelve CMA-ES variants and 24 test problem…
Clusteringfeature selectionTime SeriesTime Series AnalysisMulti-Time-Scale Input Approaches for Hourly-Scale Rainfall-Runoff Modeling based on Recurrent Neural Networks
This study proposes two straightforward yet effective approaches to reduce the required computational time of the training process for time-series modeling through a recurrent neural network (RNN) using multi-time-scale …
Time SeriesTime Series AnalysisAre Large Language Models Useful for Time Series Data Analysis?
Time series data plays a critical role across diverse domains such as healthcare, energy, and finance, where tasks like classification, anomaly detection, and forecasting are essential for informed decision-making. Recen…
Anomaly DetectionDecision MakingTime SeriesTime Series AnalysisComparing Two Different Approaches in Big Data and Business Analysis for Churn Prediction with the Focus on How Apache Spark Employed
Due to the significant importance of Big Data analysis, especially in business-related topics such as improving services, finding potential customers, and selecting practical approaches to manage income and expenses, man…
Deep Learning for Energy Time-Series Analysis and Forecasting
Energy time-series analysis describes the process of analyzing past energy observations and possibly external factors so as to predict the future. Different tasks are involved in the general field of energy time-series a…
Deep LearningDemand ForecastingTime SeriesTime Series Analysis+1