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41 articles for “ARIMA”
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Research ArticleOpen accessEvery word in the titleSales 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 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 accessEvery word in the titleForecasting 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 accessEvery word in the titleDAILY CRUDE OIL PRICE FORECASTING MODEL USING ARIMA, GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC AND SUPPORT VECTOR MACHINESRana Abdullah Ahmed, Ani Bin ShabriCrude oil price forecasting is gaining increased interest globally. This interest is due mainly to the economic value attached to the product. For this reason, new forecasting methods are proposed in the literature. This paper proposes a novel technique for forecasting crude oil price based on Support Vector Machines (SVM). The study adopts the data on crude oil price of … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 11 Jan 2014 · 8,725 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSeasonal 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 accessEvery word in the titleForecasting Foreign Direct Investment Inflow in Jordan: Univariate ARIMA ModelAl-Abdulrazag Bashier, Bataineh TalalThe present study is an attempt to build a Univariate time series model to forecast the FDI inflows into Jordan over the coming period 2004-2025. The study employs Box-Jenkins methodology of building ARIMA (Autoregressive Integrated Moving Average) model to achieve the goals of the study. An annual sample time series data for the FDI in Jordan was utilized over the … …Journal of Social Sciences, Vol. 3, Issue 1 · 31 Mar 2007 · 8,385 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntegrated ARIMA and Multi-Scale GRU for Crop Recommendation and Yield Prediction in Precision AgricultureVani Vijay Kumar Ballapuram, Gurupraksh Chirathahalli DyamannaAgriculture is the fundamental source of food, income, and livelihood for rural communities in India. Numerous crops are affected due to the lack of technical decision-making support and variations in weather patterns, temperature, rainfall, and atmosphere factors, which play a critical role in defining crop yield. Hence, choosing the appropriate crop to maximize yield is key to enhancing real-time farming … …Journal of Computer Science, Vol. 21, Issue 10 · 26 Nov 2025 · 2,022 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleWeather Forecasting Using Merged Long Short-Term Memory Model (LSTM) and Autoregressive Integrated Moving Average (ARIMA) ModelAfan Galih Salman, Yaya Heryadi, Edi Abdurahman, Wayan SupartaWeather forecasting is an interesting research problem in flight navigation area. One of the important weather data in aviation is visibility. Visibility is an important factor in all phases of flight, especially when the aircraft is maneuvering on or close to the ground, i.e., during taxi-out, take-off and initial climb, approach and landing and taxi-in. The aim of these study … …Journal of Computer Science, Vol. 14, Issue 7 · 28 Jun 2018 · 11,422 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNelson and Plosser Revisited: Evidence from Fractional ARIMA ModelsGuglielmo Maria Caporale, Luis A. Gil-AlanaIn this study fractionally integrated ARIMA (ARFIMA) models are estimated using an extended version of Nelson and Plosser[1]’s data set. The analysis employs[11]’s maximum likelihood procedure. Such a parametric approach requires the model to be correctly specified in order for the estimates to be consistent. A model-selection procedure based on diagnostic tests on the residuals, together with several likelihood criteria, … …American Journal of Applied Sciences, Vol. 2, Issue 4 · 30 Apr 2005 · 6,715 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAutoregressive Integrate Mean Average as Approaches for Modeling Energy Production in the Electricity Network by Seasons of the Electric Energy Company in Lomé, TogoApaloo Bara Komla Kpomonè et al.The work accumulated in this article presents the results of modeling the tduction of electrical energy for the CEET network in Lomé, Togo, taking into account the seasons of the area. The objective is to evaluate the forecasts over the periods in relation to the seasons of the year. Four seasons are detected, namely: Long dry season, long rainy season, … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 4 · 20 Dec 2024 · 3,922 accessesView PDFCite