Research ArticleOpen accessIn the abstractIntegrated 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
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 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 abstractApplication 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 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
Research ArticleOpen accessIn the abstractUtilization of Holt's Forecasting Model for Zakat Collection in IndonesiaAkbarizan, Muhammad Marizal, M. Soleh et al.The practice of zakat is gaining popularity in Indonesia. This development is attributed to the strong role of the government in consistently developing zakat infrastructure and the increased awareness of people to practice zakat. Despite this success, a mechanism for predicting future zakat collection has not yet been developed. This study applies Holt's exponential smoothing and Auto-Regressive Integrated Moving Average … …American Journal of Applied Sciences, Vol. 13, Issue 12 · 22 Dec 2016 · 7,499 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
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite