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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
Research ArticleOpen accessIn the keywordsBAYESIAN MODEL AVERAGING WITH MARKOV CHAIN MONTE CARLO FOR CALIBRATING TEMPERATURE FORECAST FROM COMBINATION OF TIME SERIES MODELSHeri Kuswanto, Mega Rahmatia SariGlobal warming is an important issue related to the climate and weather forecast. It is shown by significantly increasing the atmospheric temperature level. Hence, improving the forecast accuracy of temperature is an important issue. The forecast is commonly done by performing a deterministic forecast meaning that the system will generate a point forecast without taking into account the uncertainty induced … …Journal of Mathematics and Statistics, Vol. 9, Issue 4 · 29 Nov 2013 · 7,078 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 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 abstractAnomaly Detection Algorithms for Streaming Data: Performance ComparisonZirije HasaniToday’s most of the data are streaming time-series data, where is very important anomaly detection over this data because gives significant information of possible critical situations. Detecting anomalies in big streaming data is yet difficult task because we have to process them in real time, even before they are stored and instantly alarm on potential threats. For real time streaming … …Journal of Computer Science, Vol. 16, Issue 7 · 18 Jul 2020 · 7,288 accessesView PDFCite
Research ArticleOpen accessIn the abstractModel Comparison for the Prediction of Stock Prices in the NYSEVictoria Switlyk, Junfeng ShangThe stock market is an integral part of investments as well as the economy. The prediction of stock prices is an exciting and challenging problem that has been considered by many due to the complexity and noise within the market and to the potential profit that can be yielded from accurate predictions. We aim to construct and compare models used … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 26 Sep 2019 · 7,475 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 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 abstractPrediction on Land Market Value Based on the Real Estate Market in USALei WangThe Land Market Value, defined as the total value of land price and quantity data are derived from data on housing values, is an important factor in the estimation of structure costs using price indexes for housing and construction costs. In this study, we gather and analyze 34 years' national data on past and present real estate transaction. According to … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 23 May 2017 · 7,555 accessesView PDFCite