Model description, observations, and prior knowledge are the three main sources of information that are used for the evaluation and estimation of complex systems. Here, model description is given based on the physical mechanism and dynamics of the system. Observational data represent a very important method of verification and can be applied to validate the model. Prior knowledge can help to provide additional information when observation data are not sufficient. On the basis of clearly carding the relationship between a system's observational quantities and the ultimate indices of the observation, the purpose of this paper is to establish the systemic yoyo model for systems evaluation.
Recent advances in systems science in general and the systemic yoyo model in particular are employed in this research as the fundamental logic of reasoning and thread of thinking.
After analyzing the characteristics and connections between the three main sources of information – model description, prior knowledge, and observational data – used in system evaluation and estimation, the authors derive the conservation law of information for system evaluation and estimation and analyze the transitional direction of the process of system evaluation and estimation.
This work lays down the theoretical basis for why certain procedures widely applied in system evaluations and estimations are correct and sound, on which reliable scientific conclusions can be drawn.
This work is the first of its kind that investigates the systemic foundation underlying the commonly applied procedures of system evaluations and estimations.
Duan, X. and Lin, Y. (2011), "1. Conservation law of information and its application in evaluation and estimation of complex systems", Kybernetes, Vol. 40 No. 1/2, pp. 262-274. https://doi.org/10.1108/03684921111118031Download as .RIS
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