Automation and Robotics

In many applications multiple time series of measurement parameters are taken. Th e aim is not to forecast how the single time series will evolve. Th e aim of this study was to fi gure out when a biological system, an engineering system, or a system under observation will go into a critical status that requires immediately action to preserve the system. Th is task requires diff erent intelligent observations from prediction to decision making over multiple time-parameters. Oft en the measurement data points are not equidistant. Th ey are oft en on diff erent time-intervals and they have to be brought into a common time interval by adequate interpolation methods. Th e status of the system in the past and how it will be behaving in the future will also play an important role. Th at does not bring it into a single point observation but rather into a more complex consideration that needs to take into an account the system status. We will show on diff erent application how such an application can be solved. We will review the state of the art of single time-signal prediction. We will show how the system theory method has to be applied. We demonstrate that it is necessary to take the system theory quotation into account to solve the problem, it does not matter if it is a biological, engineering, or maintenance object; and fi nally, we will show on diff erent application how we solved the applications with system-theory data mining methods