This paper anticipates trends in the digital economy during a COVID-19 epidemic worldwide. The United States and China are considered world’s largest economies have attempted to transition fully over last few years. Therefore, this used auto-regressive integrated moving average (ARIMA) model gross domestic product (GDP) for USA period 1960-2019. As we arrive at peak of pandemic, one most squeez...

Accurate forecasting of rainfall has been one of the most important issues in hydrological research. In this paper, a novel neural network technique, support vector regression (SVR), to monthly rainfall forecasting. The aim of this study is to examine the feasibility of SVR in monthly rainfall forecasting by comparing it with back–propagation neural networks (BPNN) and the autoregressive integr...

Wind speed forecasting is difficult not only because of the influence of atmospheric dynamics but also for the impossibility of providing an accurate prediction with traditional statistical forecasting models that work by discovering an inner relationship within historical records. This paper develops a self-adaptive (SA) auto-regressive integrated moving average with exogenous variables (ARIMA...

In this study , after a new Artificial Intelligence technique inspired from the human immune system –the Artificial Immune System (AIS) is described, it is compared with the Artificial Neural Networks (ANNs) and some immune approaches in neural networks are emphasized as application. After the artificial intelligence (AI) has come into existence, especially artificial neural networks took a gre...

With accurate visitor traffic forecasts, retail businesses can optimise their staff schedule and stock distribution for increased profits. Existing models such as Linear Regression, ARIMA and other statistical methods are being employed for traffic predictions, but the accuracy of these models leaves room for improvement. Neural Network models show promising results on similar data. Therefore, ...

Temperature forecasts and trend analyzes were carried out for several locations in Mali as an important tool warning of potentially threatening weather events such severe heat waves, storms, droughts floods, which could pose a great risk to humans their environment. Five (Segou, Sikasso, Kayes, Gao Taoudenni) across (170 00’N – 40 00’W) chosen this research work. Satellite data annual temperatu...

Dataset with Outliers causes poor accuracy in future analysis of data mining tasks. To improve the performance of mining task, it is necessary to detect and revamp of outliers which are there in the dataset. Existing techniques like ARMA (Auto-Regressive Moving Average), ARIMA (AutoRegressive Integrated Moving Average) and Multivariate Linear Gaussian state space model don't consider the p...

Article history: Accepted 16 December 2015 Available online xxxx This study aims to forecast oil prices using evolutionary techniques such as gene expression programming (GEP) and artificial neural network (NN) models to predict oil prices over the period from January 2, 1986 to June 12, 2012. Autoregressive integrated moving average (ARIMA) models are employed to benchmark evolutionary models....