Forecasting of Maize Yield in Bihar through Auto Regressive Integrated Moving Average (ARIMA) Models
International Journal of Bio-Resource and Stress ManagementThe experiment was conducted during March, 2023 at Dr Rajendra Prasad Central Agricultural University, Samastipur, Bihar, India based on secondary maize yield data from 1990 to 2021, sourced from the Department of Economics and Statistics and India ...
H. Girijaswathi +5 more
doaj +1 more source
Seasonal Decomposition‐Enhanced Deep Learning Architecture for Probabilistic Forecasting
Journal of Forecasting, EarlyView.ABSTRACT Time series decomposition as a general preprocessing method has been widely used in the field of time series forecasting. However, since the future is unknown, this preprocessing practice is limited in realistic forecasting, especially in real‐time forecasting scenarios.
Keyan Jin +1 more
wiley +1 more source
Prediksi Debit Sungai Bedog dan Gajahwong Dengan Model Arima sebagai Dasar Penentuan Pola Tanam
Agritech, 2017 Planting pattern in an irrigation system is affected by water availability in river which may fluctuate from time to time. The objective of this paper is to assess the discharge fluctuation characteristic of Bedog and Gajahwong Rivers measured ...
Murtiningrum Murtiningrum +3 more
doaj +1 more source
The Comparison among ARIMA and hybrid ARIMA-GARCH Models in Forecasting the Exchange Rate of Iran [PDF]
International Journal of Business and Development Studies, 2015 This paper attempts to compare the forecasting performance of the ARIMA model and hybrid ARMA-GARCH Models by using daily data of the Iran’s exchange rate against the U.S. Dollar (IRR/USD) for the period of 20 March 2014 to 20 June 2015. The period of 20
Mosayeb Pahlavani, Reza Roshan
doaj +1 more source
Load forecasting analysis for regional and industry power systems-based on ARIMA model and LSTM model [PDF]
, 2022 Jiongcheng Chen +4 more
openalex +1 more source
Journal of Forecasting, EarlyView.ABSTRACT Using online job advertisement data improves the timeliness and granularity depth of analysis in the labor market in domains not covered by official data. Specifically, its variation over time may be used as an anticipator of official employment variations.
Pietro Giorgio Lovaglio +1 more
wiley +1 more source
BMC Public Health, 2022 Objective To compare an autoregressive integrated moving average (ARIMA) model with a model that combines ARIMA with the Elman recurrent neural network (ARIMA-ERNN) in predicting the incidence of pertussis in mainland China.
Meng Wang +12 more
doaj +1 more source
Forecasting the US Dollar/Euro Exchange Rate Based on ARIMA Model [PDF]
, 2023 Qimian Zhu
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Improving Short-Term Electricity Price Forecasting Using Day-Ahead LMP with ARIMA Models
, 2018 Short-term electricity price forecasting has become important for demand side management and power generation scheduling. Especially as the electricity market becomes more competitive, a more accurate price prediction than the day-ahead locational ...
Miller, Carol +3 more
core +1 more source
Exploring the trend of New Zealand housing prices to support sustainable development [PDF]
, 2019 The New Zealand housing sector is experiencing rapid growth that has a significant impact on society, the economy, and the environment. In line with the growth, the housing market for both residential and business purposes has been booming, as have house
Liu, Zhansheng +2 more
core +1 more source