Water resources are an indispensable and valuable resource for human survival development. quality predicting plays important role in the protection development of water resources. It is difficult to predict due its random trend changes. Therefore, a method which combines Auto Regressive Integrated Moving Average (ARIMA) clustering model was proposed this paper. By taking monitoring data certai...

Understanding the influence of meteorological parameters in relation to COVID-19 transmission may be a convenient way predict ongoing pandemic towards its adaptive control measures. This study aims explore association between cases and for an extended period covering different climatic patterns. The number cases, daily records rainfall, temperature, relative humidity wind speed data were collec...

Today, there is a crucial need for precise monitoring and prediction of energy consumption at the building level using latest technologies including Internet Things (IoT) data analytics to determine enhance usage. Data-driven models could be used prediction. However, due high non-linearity between inputs outputs models, these improvement in terms accuracy robustness. Therefore, this work aims p...

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...

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...

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...

One of the most basic needs any human being to survive is air. Unfortunately, this need polluted by many natural factors like volcanic eruptions, forest fires, and man-induced transportation emission. Unpolluted air now an ideal environment that can never be achieved. So, pollution levels should monitored continuously. However, monitoring will not fix environment. Forecasting these make society...