On any given day, traffic flow managers must often rely on past experience and intuition when developing traffic flow management initiatives that mitigate imbalances between aircraft demand and weather impacted airport capacity. The goal of this study was to build on recent efforts to apply data mining classification and clustering algorithms to vast archives of historical weather and air traff...

On any given day, constraints in the National Airspace System, for instance weather, necessitate the implementation of Traffic Flow Management initiatives, such as Ground Delay Programs. The parameters associated with these initiatives, for example the location, scope, duration, etc., are typically left to human decision makers, who must rely on intuition, past experience, and weather and traff...

The important, while mostly underestimated, step in the process of short-term load forecasting–STLF is selection similar days. Similar days are identified based on numerous factors, such as weather, time, electricity prices, geographical conditions and consumers’ types. However, those factors influence differently within different circumstances conditions. To investigate optimise process, a new...

accurate and effective electricity price forecasting is critical to market participants in order to make an appropriate risk management in competitive electricity markets. market participants rely on price forecasts to decide on their bidding strategies, allocate assets and plan facility investments. however, due to its time variant behavior and non-linear and non-stationary nature, electricity...

Abstract Considering similar air traffic control techniques for the present based on close historical dates is a good approach due to unpredictability of weather and traffic, as well increase controller efficiency. A K-prototype clustering technique grey correlation analysis are proposed discover days address problem identification. Firstly, datasets used create set features broken down into nu...

It is challenging to obtain accurate and efficient predictions in short-term load forecasting (STLF) systems due the complexity nonlinearity of electric signals. To address these problems, we propose a hybrid predictive model that includes sliding-window algorithm, stacking ensemble neural network, similar-days method. First, leverage algorithm process time-series data with high non-stationarit...

If, in some cataclysm, all of scientific knowledge were to be destroyed, and only one sentence passed on to the next generations of creatures, what statement would contain the most information in the fewest words? I believe it is the atomic hypothesis (or the atomic fact, or whatever you wish to call it) that all things are made of atoms—little particles that move around in perpetual motion, at...