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22 results for “Seasonal Time Series”
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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 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
EditorialOpen accessIn the abstractNew Kind of Statistical MethodsCagdas Hakan AladagAladag, C.H. and E. Egrioglu, 2012. Advanced Time Series Forecasting Methods. In: Advances in Time Series Forecasting, Aladag, C.H. and E. Egrioglu (Eds.), Bentham Science Publishers, Oak Park, ISBN-10: 1608053733. Aladag, C.H., 2011. A Hybrid Intelligent Technique Combines Neural Networks and Tabu Search Methods for Forecasting, Computer Search Algorithms. 1st Edn., Nova Publisher, ISBN: 978-1-61209-043-6. Aladag, C.H., E Egrioglu, U. … …Journal of Mathematics and Statistics, Vol. 10, Issue 4 · 28 Nov 2014 · 7,588 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling 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 abstractSeasonal 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 abstractFuzzy Time Series: An Application to Tourism Demand ForecastingMuhammad Hisyam Lee, Maria Elena Nor, Suhartono et al.Problem statement: Forecasting is very important in many types of organizations since predictions of future events must be incorporated into the decision-making process. In the case of tourism demand, better forecast would help directors and investors make operational, tactical and strategic decisions. Besides that, government bodies need accurate tourism demand forecasts to plan required tourism infrastructures, such as accommodation site … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,474 accessesView PDFCite
Research ArticleOpen accessIn the abstractTime 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 abstractMonitoring Growing Season Length of Deciduous Broad Leaf Forest Derived From Satellite Data in IranSasan Babaei Kafaki, Asadollah Mataji, Seyed Armin HashemiProblem statement: Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and biogeochemical cycles. This study aimed to quantify changes in plant phenology of deciduous broadleaf forests between the years 1982-1999 and investigate the relationships between the onset dates of phenology and climatic factors. Approach: We studied the … …American Journal of Environmental Sciences, Vol. 5, Issue 5 · 31 Oct 2009 · 8,557 accessesView PDFCite
Research ArticleOpen accessIn the abstractObserved Abrupt Changes in Minimum and Maximum Temperatures in Jordan in the 20th CenturyMahmoud M. SmadiThis study examines changes in annual and seasonal mean (minimum and maximum) temperatures variations in Jordan during the 20th century. The analyses focus on the time series records at the Amman Airport Meteorological (AAM) station. The occurrence of abrupt changes and trends were examined using cumulative sum charts (CUSUM) and bootstrapping and the Mann-Kendall rank test. Statistically significant abrupt changes … …American Journal of Environmental Sciences, Vol. 2, Issue 3 · 30 Sep 2006 · 7,925 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordTime Series Analysis for Predicting Tea Harvest Yield: A SARIMAX-Based ApproachPallavi Nagpal, Deepika Chaudhary, Jaiteg SinghPrecise prediction of tea yield is crucial for both agricultural planning and economic forecasting. Projection of the future trends, which rely on present and historical data, is the process termed 'forecasting'. Yield prediction is fundamental for research and development. By gathering the yield data over historic times, the researchers can make their work more valuable by predicting the yield patterns. … …Journal of Computer Science, Vol. 22, Issue 2 · 19 Feb 2026 · 1,891 accessesView PDFCite