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The objective of the paper is to show the role of geodetic monitoring and modern methods of measurement data processing with the use of neural-fuzzy systems in identifying changes occurring in engineering structures. Fast methods of measurement and data processing are of key importance whenever rapidly changing phenomena should be captured (e.g. deformations of buildings, fires spreading in forest areas, flood waves, landslides caused by endogenous and exogeonic factors). Processes and phenomena occurring in engineering structures can be modelled based on information obtained by geodetic monitoring. At present, elements of geodetic technologies are being supplemented with artificial intelligence methods, which include neuro-fuzzy systems. These systems can process information that is provided at the input both as numerical and linguistic values. This approach is used for qualitative assessment of the condition of objects and physical quantities and it is characterized by parallel information processing. The paper presents the possibility of using the Takaga-Sugeno neural-fuzzy model for prediction and assessment of horizontal and vertical displacements of engineering structures as illustrated by the example of a historical footbridge in Muskauer Park, located in Germany and Poland.

Application of the Takaga-Sugeno neuro-fuzzy model for determining of engineering structures