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15 articles for “Autoregressive Integrated Moving Average (ARIMA)”
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Research ArticleOpen accessPhrase 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 accessPhrase 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 accessIn the keywordsAdaptive Linear Prediction Augmented Autoregressive Integrated Moving Average Based Prediction for VBR Video TrafficT. Raghuveera, P. V.S. Kumar, K. S. EaswarakumarProblem statement: Network traffic prediction plays a vital role in the optimal resource allocation and management in computer networks. This study introduces an ARIMA based model augmented by Adaptive Linear Prediction (ALP) for the real time prediction of VBR video traffic. The synergy of the two can successfully address the challenges in traffic prediction such as accuracy in prediction, resource … …Journal of Computer Science, Vol. 7, Issue 6 · 14 Jun 2011 · 7,013 accessesView PDFCite
Research ArticleOpen accessIn the abstractSales 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
Review ArticleOpen accessIn the abstractThe use of Principal Component Regression and Time Series Analysis to Predict Nitrous Oxide Emissions in GhanaBenjamin Odoi, Lewis Brew, Christopher AttafuahThe disturbing pace of emanation of Nitrous Oxide (N2O) into the atmosphere and its calamitous impact on the environment, as monitored by many governmental agencies and researchers has become a wellspring of worry for many nations and therefore needs due attention. The study deployed nitrous oxide emissions from the three sectors to the total nitrous oxide emissions in Ghana over … …Energy Research Journal, Vol. 12, Issue 1 · 6 Jan 2021 · 8,597 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Based Feature Selection of Macroeconomic Variables for Stock Market PredictionIsaac Kofi Nti, Adebayo Felix Adekoya, Benjamin Asubam WeyoriA firm’s equity price on the stock-market is reported to be closely related to the Macroeconomic Variable (MVs) of the country in which the firm trades. For this reason, researchers, market traders, financial analysts and forecasters to examine the association between MVs and stock-price have carried out numerous studies, using time-series statistical analysis methods like Autoregressive Integrated Moving Average (ARIMA), … …American Journal of Applied Sciences, Vol. 16, Issue 7 · 31 Jul 2019 · 10,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting 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 abstractPrediction of Grain Products in TurkeyÖzlem Akay, Gökmen Bozkurt, Güzin YükselMarketing of agricultural products starts with the planning of production on the farm and ends with the sale of food or other goods to manufacturers or consumers. Overall, marketing is a main part of successful agriculture but its significance is usually underestimated, particularly in developing countries. In Turkey, annual variations in grain production are reasonable and result primarily from changes … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 10 Jul 2017 · 7,322 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling Positive Time Series Data: A Neglected Aspect in Time Series CoursesMaman A. Djauhari, Lee Siaw Li, Rohayu Mohd SallehSomething has been forgotten in time series courses, in particular, when dealing with positive datasets. To describe the pattern hidden in this type of datasets, before we use a sophisticated method of modeling such as Autoregressive Integrated Moving Average (ARIMA), we propose to check first whether the data represent a Geometric Brownian Motion (GBM) process. If it is affirmative, unlike … …American Journal of Applied Sciences, Vol. 13, Issue 7 · 1 Jul 2016 · 7,533 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Humidity of Some Selected Stations from the Northern Part of Bangladesh: An Application of SARIMA ModelMd. Moyazzem Hossain, Md. Atikur Rahman, Md. Zahirul Islam, Ajit Kumar MajumderCommunity risk from natural hazards and climate change depends largely on physical and climatic settings of an area, socio-economic condition of a community and the magnitude, duration and consecutiveness of the hazard or change itself. Impacts of climate change can be characterized by increasing temperatures, rainfall, humidity changes and climate related extreme events such as floods, cyclone, droughts, sea level … …American Journal of Environmental Sciences, Vol. 12, Issue 3 · 10 May 2016 · 8,618 accessesView PDFCite