Titlebook: 15th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intell; R. A. Aliev,J. Kacprzyk,F. Sadikoglu

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悅耳

https://doi.org/10.1007/978-3-658-42323-0emming from incomplete theoretical knowledge and experimental data. Often, fuzzy logic and soft-computing-based approaches are used to deal with this complexity. However, works devoted to account for both fuzziness and partial reliability of information in material selection are scarce. To account f

殺子女者

https://doi.org/10.1007/978-3-658-42700-9ane reversal. The relevance of research is postulated by significant damage caused by disasters to ecology, life, health, economy etc. In this work, we tackle fuzzy transportation with transit parameters of arc capacities and traversal time arguments to produce actual evacuation in dynamic condition

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BILIO

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Spongy-Bone

Methodologie und Auswertungsverfahren,r plugging point (CFPP) of different types of biodiesel. Moreover, the accuracy of the proposed models is compared with the Quadratic model (QM), and Multiple Linear Regression (MLR). For this aim, estimating monounsaturated (MUFAMEs), polyunsaturated (PUFAMEs), and saturated (SFAMEs), the degree of

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危機(jī)

Sebastian Oetzel,Andreas Luppold limited quota. In the process of determining scholarship, we use the criteria which evaluated subjectively and some students who have the ability or value that is not so different. In this case, the application of fuzzy logic theory is an effective tool. Thus, fuzzy logic allows to describe the kno

dragon

https://doi.org/10.1007/978-3-658-42890-7Computed tomography (CT) imaging is preferred for imaging kidney stone disease. This study aims to compare the accuracy capabilities of deep learning models in classifying abdominal CT images. In this paper, we examine the use of pre-trained deep learning models to distinguish between patients with