Intelligent Analysis of Data Streams
Rozinajova, V., Bou Ezzeddine, A., Grmanova, G., Vrablecova, P., Pomffyova, M.
The huge amount of data generated on a daily basis in many areas of our lives predetermines data science to be one of the most significant current IT research areas. Thanks to the recent technological trends, such as internet of things (IoT), the data streams constitute a majority of currently created data. This chapter aims to provide one possible view on the recent trends in stream mining.
Our focus is on two frequent data mining tasks – namely the prediction and the optimization. We have several years of experience in predictive modeling and we would like to offer here a summarization of the selected outcomes of our research work. The domain in which we have verified our methods, is the power engineering area. Due to population growth and technological advancement, there has been a huge increase of global energy demand in recent years.
The ultimate goal is to manage the energy supply in the most efficient way. To propose smart solutions, the first step is to have a clear idea about its future consumption and production. Then we can proceed to efficient control of the smart grid, by involving recent trends in optimization and utilizing machine learning approaches. Hence the second part of the chapter is devoted to our endeavors in solving tasks of smart grid optimization. The common denominator of the described approaches is the effort to cover various types of knowledge entering these procedures.