Titlebook: Artificial Intelligence and Soft Computing; 14th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

易于出錯(cuò)

Pyelonephritis und Nierenabszessified) formalism are used to propose two formalism for preferences: . (FMPL) and . (CPMPL). We also justify some metalogical properties of both systems such as their completeness and we discuss a satisfiability problem for them. In result, we propose a short juxtaposition of the properties of the considered systems.

絕種

Parasit?re Erkrankungen in der Urologielearning methods for fuzzy rules on applications of Type-2 fuzzy logic systems to control filters reducing air pollution. The filters use Selective Catalytic Reduction (SCR) method and, as for now, this process is controlled manually by a human expert.

現(xiàn)任者

打折

Product Multi-kernels for Sensor Data Analysis an evolutionary learning algorithm for setting its parameters. The algorithm is capable to select different kernels from a dictionary and to set their parameters, including optimal split of inputs into individual products. The approach is tested on real-world data from sensor networks area.

可耕種

愛(ài)哭

Comparative Approach to the Multi-Valued Logic Construction for Preferencesified) formalism are used to propose two formalism for preferences: . (FMPL) and . (CPMPL). We also justify some metalogical properties of both systems such as their completeness and we discuss a satisfiability problem for them. In result, we propose a short juxtaposition of the properties of the considered systems.

恃強(qiáng)凌弱的人

Learning Rules for Type-2 Fuzzy Logic System in the Control of DeNOx Filterlearning methods for fuzzy rules on applications of Type-2 fuzzy logic systems to control filters reducing air pollution. The filters use Selective Catalytic Reduction (SCR) method and, as for now, this process is controlled manually by a human expert.

STRIA

https://doi.org/10.1007/978-3-662-44463-4o be defined in advance. In the gene-based clustering of the considered data, our approach generates clusters that are easily divisible into subclusters related to particular sample classes. It corresponds, in a way, to subspace clustering that is highly desirable in microarray data analysis.

全國(guó)性

Facharztwissen Orthop?die Unfallchirurgieto automatically interconnect representing similar or sequential data. This contribution describes generalized formulas for quick analytical computation of the structure and parameters of ANAKG neural graphs for representing and recalling of training sequences of objects.

COMMA