A Method Based on Intellectual Technologies of Data Interoperability Between Software Tools
Abstract
The article explores the potential for exchanging information between software tools using the KNIME program. It provides recommendations on utilizing data preprocessing models, methods, and algorithms for data sharing, and offers examples to illustrate these concepts. The article also discusses the capabilities of KNIME for exchanging information between software tools without the need for coding, such as analyzing and sharing data between databases and making predictions based on the data. The article specifically addresses the issue of geo-location of scooters in use in smart cities and the distribution of scooters over a certain period of time. This includes the number of scooters in use and idle at different times of the day, as well as demand data and real data obtained from statistical systems based on weather data. The article also discusses how KNIME can be used to solve regression problems and predict the daily distribution of scooter usage for each station. KNIME is a powerful program that utilizes intelligent technologies for data interoperability between software tools, making it an effective tool for solving forecasting problems and integrating data.