Review of ML and AutoML solutions to forecast time-series data
Time-series forecasting is a significant discipline of data modeling where past observations
of the same variable are analyzed to predict the future values of the time series. Its …
of the same variable are analyzed to predict the future values of the time series. Its …
Artificial intelligence and new business models in agriculture: a structured literature review and future research agenda
Purpose Artificial Intelligence (AI) is a growing technology impacting several business fields.
The agricultural sector is facing several challenges, which may be supported by the use of …
The agricultural sector is facing several challenges, which may be supported by the use of …
STL-ATTLSTM: vegetable price forecasting using STL and attention mechanism-based LSTM
H Yin, D **, YH Gu, CJ Park, SK Han, SJ Yoo - Agriculture, 2020 - mdpi.com
It is difficult to forecast vegetable prices because they are affected by numerous factors, such
as weather and crop production, and the time-series data have strong non-linear and non …
as weather and crop production, and the time-series data have strong non-linear and non …
Forecasting agricultural commodity prices using dual input attention LSTM
YH Gu, D **, H Yin, R Zheng, X Piao, SJ Yoo - Agriculture, 2022 - mdpi.com
Fluctuations in agricultural commodity prices affect the supply and demand of agricultural
commodities and have a significant impact on consumers. Accurate prediction of agricultural …
commodities and have a significant impact on consumers. Accurate prediction of agricultural …
Agricultural product price forecasting methods: research advances and trend
L Wang, J Feng, X Sui, X Chu, W Mu - British Food Journal, 2020 - emerald.com
Purpose The purpose of this paper is to provide reference for researchers by reviewing the
research advances and trend of agricultural product price forecasting methods in recent …
research advances and trend of agricultural product price forecasting methods in recent …
Groundwater level prediction model using correlation and difference mechanisms based on boreholes data for sustainable hydraulic resource management
Drilling data for groundwater extraction incur changes over time due to variations in
hydrogeological and weather conditions. At any time, if there is a need to deploy a change in …
hydrogeological and weather conditions. At any time, if there is a need to deploy a change in …
A heterogeneous graph enhanced LSTM network for hog price prediction using online discussion
Forecasting the prices of hogs has always been a popular field of research. Such
information has played an essential role in decision-making for farmers, consumers …
information has played an essential role in decision-making for farmers, consumers …
Process optimization for conversion of waste banana peels to biobutanol by a yeast co-culture fermentation system
In the present investigation, sodium hydroxide (NaOH) and sulfuric acid (H 2 SO 4)
pretreatment were conducted using response surface methodology (RSM) technique for …
pretreatment were conducted using response surface methodology (RSM) technique for …
A ML-AI Enabled ensemble model for predicting agricultural yield
Simplistic linear methods for predicting crop yield leave out important factors like climate,
rainfall, soil, irrigation, and land characteristics. Recent literature points to use of individual …
rainfall, soil, irrigation, and land characteristics. Recent literature points to use of individual …
Analytics in develo** countries: methods, applications, and the impact on the UN Sustainable Development Goals
The growing availability of data coupled with advanced methods and computing power have
fostered organizations to adopt business analytics in their decision‐making. Nevertheless …
fostered organizations to adopt business analytics in their decision‐making. Nevertheless …