Sugarcane industry is of crucial importance to the South Asian countries. These countries depend heavily on agriculture and sugarcane has immense potential contribute towards its economic development. Hence, precise timely forecast production concern for farmers, policy makers other stakeholders. In this manuscript, we strived growth rate important commodity using standard statistical approache...

Malaysia often suffers from haze problems almost every year. Therefore, there is a need for good air quality forecasting model monitoring and management purposes. In this study, the based on Long Short-Term Memory Network (LSTM) Auto-Regressive Integrated Moving Average (ARIMA) was developed. The prediction of particulate matter 10 micrometres or less in diameter (PM10) could be made both model...

Oil is one of the vital energy sources in a country. Indonesia countries that was once world's primary leading producer but currently threatened with an oil deficit. This condition certainly requires right strategy and policy so can meet its domestic needs. study aims to forecast Indonesia's consumption production for 2022-2026 using past data from 1980-2021. used Auto-Regressive Integrated Mov...

As modern vehicles system becomes increasingly complex, there is an urgent need to develop a framework monitor the behavior and detect unhealthy states appropriately arrange maintenance in order extend vehicle life cycle. Sensors installed are able record huge amount of multiple channel time series data. This paper develops prediction model state detection strategy for monitoring operating by a...

To model the trajectory of pandemic in Kuwait from February 24, 2020 to 28, 2021, we used two modeling procedures: Auto Regressive Integrated Moving Average (ARIMA) with structural breaks and Multivariate Adaptive Regression Splines (MARS), then mapped key breakpoints models set government-enforced interventions. The MARS model, as opposed ARIMA provides a more precise interpretation interventi...

This study compared the methods used to forecast increases in power consumption caused by rising popularity of electric vehicles (EVs). An excellent model for each region was proposed using multiple scaled geographical datasets over two years. EV charging volumes are influenced various factors, including condition a vehicle, battery’s state-of-charge (SOC), and distance destination. However, su...

Abstract Drought stress under a changing climate can significantly affect agricultural production. Simulation of soil water dynamics in field conditions becomes necessary to understand changes develop irrigation guidelines. In this study, three models including Auto-Regressive Integrated Moving Average (ARIMA), Back-Propagation Artificial Neural Network (BP-ANN), and Least Squares Support Vecto...

The massive spread of COVID-19 has disrupted trading activities worldwide plunging the economy a nation; particularly, trade-dependent nations are severely affected by restriction in exports and imports. This paper aims to evaluate implications on trade New Zealand exploratory data analysis ARIMA modeling. Based comprehensive strategy prediction, were processed notice impact pandemic sales. (Au...