In previous studies we first concentrated on utilizing crisp simulationto produce discrete event fuzzy systems simulations. Then we extendedthis research to the simulation of continuous fuzzy systems models. In this paperwe continue our study of continuous fuzzy systems using crisp continuoussimulation. Consider a crisp continuous system whose evolution depends ondifferential equations. Such a ...

The applications of fuzzy logic and fuzzy algorithms to the classification of celestial objects will be explored through various prominent papers in the field. Specifically, these papers will address issues concerning star and galaxy separation, classification of stars into their spectral types, classification of galaxies into the main galaxy types, and comparing the results to their neural net...

introduction: rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature sst sea surface temperature and sea level pressure slp sea level pressure. climate anomalies being related to each other at large distance is called teleconnection. as physical relationships between rainfall and teleconnection patterns are not defined clearly, we used inte...

The Wadden Sea is an almost untouched area with a size of about 7300 km along the German, Dutch and Danish coast. Because of tide the area is flooded two times a day, creating a very special and sensitive ecosystem. In order to protect the Wadden Sea up-todate Digital Terrain Models (DTM) of high accuracy are needed to detect morphological changes. Lidar is an adequate method to obtain an accur...

In this paper, we propose a new residual analysis method using Fourier series transform into fuzzy time series model for improving the forecasting performance. This hybrid model takes advantage of the high predictable power of fuzzy time series model and Fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...

This work is focused on creating fuzzy granular classification models based on general type-2 fuzzy logic systems when consequents are represented by interval type-2 TSK linear functions. Due to the complexity of general type-2 TSK fuzzy logic systems, a hybrid learning approach is proposed, where the principle of justifiable granularity is heuristically used to define an amount of uncertainty ...