Titlebook: System Fault Diagnostics, Reliability and Related Knowledge-Based Approaches; Volume 1 Fault Diagn Spyros Tzafestas,Madan Singh,Günther Sch

rheumatology

Adaptive and Coloured Structured Petri-Nets for Description, Analysis and Synthesis of Hierarchical bed by a three levels modelization: the production tools the direct automatic-control of the operative system and the hierarchical level to parameter the working conditions. Adaptive coloured and structured Petri-nets are used to model the “Control System” with high level of parallelism and its diff

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Weibull Parameter Estimation on a Personal Computer Maximum Likelihood Estimators (MLE), Wyckoff, Bain and Engelhardts simple percentile estimators (WBE), Zanakis estimators (ZE), Modified Moment Estimators (MME) and emperical estimators suggested by Sen and Prabhashanker (SPE), have been evaluated by Monte Carlo Simulation on a mainframe computer.

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in September-October 2006.Soft Computing admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments. "Soft Computing in Industrial Applications" contains a collectio

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n (PSO) is presented in this paper. PSO is a method for optimizing hard numerical functions on metaphor of social behavior of flocks of birds and schools of fish. A swarm consists of individuals, called particles, which change their positions over time. Each particle represents a potential solution

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Rolf Isermannn (PSO) is presented in this paper. PSO is a method for optimizing hard numerical functions on metaphor of social behavior of flocks of birds and schools of fish. A swarm consists of individuals, called particles, which change their positions over time. Each particle represents a potential solution

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P. M. Frank of problems simultaneously, it partitions the datasets into cluster of objects that are similar to each other and describes the clusters by cluster prototypes to provide some information about the distribution of the data. In most of the cases these cluster prototypes describe the clusters as simpl

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Jason Papastavrou,Michael Athans of problems simultaneously, it partitions the datasets into cluster of objects that are similar to each other and describes the clusters by cluster prototypes to provide some information about the distribution of the data. In most of the cases these cluster prototypes describe the clusters as simpl

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G. Dauphin-Tanguy,P. Bornep and closed-loop multivariable identification based on neural networks are evaluated in this paper. Neural networks of multilayer perceptron and radial basis function types are employed. Radial basis function neural network is configured with training by k-means clustering (centers), nearest neighb

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