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33 articles for “ARIMA time series”
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Research ArticleOpen accessEvery word in the titleA Time Series Forecasting for the Cumulative Confirmed and Critical Cases of the Covid-19 Pandemic in Saudi Arabia using Autoregressive Integrated Moving Average (ARIMA) ModelSamer H. Atawneh, Osamah A.M. Ghaleb, Ahmad MohdAziz Hussein et al.Reviews at present, different machine learning techniques and algorithms have been applied for predicting significant factors of the Coronavirus Disease-2019 (COVID-19) such as the outbreak and diagnosis. In this study, the most accurate time series forecasting model, namely, the Autoregressive Integrated Moving Average (ARIMA) model is used to forecast the expected cumulative number of confirmed and critical cases in Saudi … …Journal of Computer Science, Vol. 16, Issue 9 · 30 Sep 2020 · 7,596 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSales Forecasting Models: Comparison between ARIMA, LSTM and ProphetDmitry BrykinSales forecasting is crucial for business planning and resource allocation. Data-driven approaches have become popular in this field. This study compares the performance of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM) and Prophet within the context of specific sales categories derived from acquiring data provided by a bank. This study uses a time series dataset … …Journal of Computer Science, Vol. 20, Issue 10 · 1 Aug 2024 · 7,981 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting Ozone Concentrations Using Box-Jenkins ARIMA Modeling in MalaysiaWan Rozita Wan Mahiyuddin, Nur Izzah Jamil, Zamtira Seman et al.Time series analysis and forecasting has become a major tool in many applications in air pollution and environmental management fields. Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins. In this study, we used Box-Jenkins methodology to build Autoregressive Integrated Moving Average (ARIMA) model on the average of monthly ozone data … …American Journal of Environmental Sciences, Vol. 14, Issue 3 · 25 May 2018 · 8,943 accessesView PDFCite
Research ArticleOpen accessIn the keywordsApplication of Time Series Modeling to Study River Water QualityMaryam Ghashghaie, Kaveh Ostad-Ali-Askari, Saeid Eslamian, Vijay P. SinghWater deficit problem originates from two factors: population increase and water pollution. However, studying and forecasting the quality of water are necessary to avoid serious problems in future through managerial works. In present study, using time series modeling, the quality of Madian Rood River is studied at Baraftab station using time series analysis. Nine parameters of water quality are studied … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 2 · 25 Apr 2018 · 8,933 accessesView PDFCite
Research ArticleOpen accessIn the keywordsModeling Tourist Arrivals Using Time Series Analysis: Evidence From AustraliaGurudeo AnandTularam, Victor Siew Howe Wong, Seyed AbdelhamidShobeiriNejadAustralian tourism has a logistic trend as Butler’s model shows. The stagnation has not been reached so opportunities exist to increase tourism. The logistic model predicts 7.2 million tourists in 2015 but time series models of ARIMA and VAR improve the prediction and explain the data. The ARIMA (2, 2, 2) fits well while the VAR lead to Granger causalities … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 10 Sep 2012 · 7,857 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSeasonal ARIMA for Forecasting Air Pollution Index: A Case StudyMuhammad Hisyam Lee, Nur Haizum Abd. Rahman, Suhartono et al.Problem statement: Both developed and developing countries are the major reason that affects the world environment quality. In that case, without limit or warning, this pollution may affect human health, agricultural, forest species and ecosystems. Therefore, the aim of this study was to determine the monthly and seasonal variations of Air Pollution Index (API) at all monitoring stations in Johor. … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 14 Feb 2012 · 10,326 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting Daily Demand in Cash Supply ChainsMichael WagnerProblem statement: Previous studies focused on explaining the long run determinants of currency demand offering limited insight into the short-run determinants and co-variability of daily demand in cash supply chains. Approach: This study contrasted competing techniques of forecasting daily demand in cash supply chains in order to determine the overall performance and the potential of joint forecasting for integrated planning. … …American Journal of Economics and Business Administration, Vol. 2, Issue 4 · 28 Nov 2010 · 7,736 accessesView PDFCite
Research ArticleOpen accessIn the keywordsTime Series Analysis of Rainfall and Temperature Interactions in Coastal CatchmentsGurudeo Anand Tularam, Mahbub IlaheeProblem statement: As a result of climate change more work is now being done on climate indices such as SOI, rainfall, temperature and so on. The research concerning rainfall and temperature variations in coastal tropical and subtropical catchments as noted by the dated references in this study shows a lack of attention. The authors examined long term data from coastal … …Journal of Mathematics and Statistics, Vol. 6, Issue 3 · 30 Sep 2010 · 15,823 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting and Time Series Analysis of Air Pollutants in Several Area of MalaysiaMohd Zamri Ibrahim, Roziah Zailan, Marzuki Ismail, Muhd Safiih LolaProblem statement: In keeping abreast with Malaysia’s rapid economic development and to meet the nation's aspiration for an improved quality of life, clean-air legislation limiting industrial and automobile emissions was adopted in 1978. Approach: Yet, to this day, air pollution from both sources still poses a problem for the nation. In order to predict the status of future air quality … …American Journal of Environmental Sciences, Vol. 5, Issue 5 · 31 Oct 2009 · 7,761 accessesView PDFCite
Research ArticleOpen accessIn the keywordsTime Series Analysis Model for Rainfall Data in Jordan: Case Study for Using Time Series AnalysisP.E. Naill M. MomaniProblem statement: Time series analysis and forecasting has become a major tool in different applications in hydrology and environmental management fields. Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins, ARIMA (Autoregressive Integrated Moving Average). Approach: In this study we used Box-Jenkins methodology to build ARIMA model for monthly rainfall data … …American Journal of Environmental Sciences, Vol. 5, Issue 5 · 31 Oct 2009 · 8,813 accessesView PDFCite