Titlebook: Soft Computing in Industrial Applications; Proceedings of the 1 Václav Snášel,Pavel Krömer,Gerald Schaefer Conference proceedings 2014 Spri

一个搅动不安

Fuzzy Reliability Analysis of Washing Unit in a Paper Plant Using Soft-Computing Based Hybridized Tey fuzzy arithmetic is utilized while in GABLT and NGABLT ordinary arithmetic and nonlinear programming approach are used. The computed results, as obtained by these techniques, are compared. Crisp and defuzzified results are also computed. Based on results some important suggestions are given for future course of action in maintenance planning.

称赞

Goblet-Cells

比赛用背带

Advanced Methods for 3D Magnetic Localization in Industrial Process Distributed Data-Logging with a e been applied in large scale indoor and outdoor systems with solutions based on RF, light based and ultra sound based systems. Data-loggers in liquid filled containers pose new challenges for localization because of the high reflectivity of containers and high attenuation due to the liquids obstruc

文艺

Neural Network Ensemble Based on Feature Selection for Non-Invasive Recognition of Liver Fibrosis Stg the examination is also of high importance. Therefore non-invasive methods that allows to precisely predict the state of the disease are currently one of the key issues in the medical business. The paper presents a novel ensemble of neural networks applied to recognition of liver fibrosis stage fr

annexation

Nomogram

Shuttle

协议

Differential Evolution and Tabu Search to Find Multiple Solutions of Multimodal Optimization Problemlems, but they have the disadvantage since that they converge to only one optimum, even though there are many optima. We proposed a hybrid algorithm combining differential evolution (DE) with tabu search (TS) to find multiple solutions of these problems. The proposed algorithm was tested on optimiza

得罪

A New RBFNDDA-KNN Network and Its Application to Medical Pattern Classificationaking pattern classification problems with noisy data. The RBFNDDA network is integrated with the .nearest neighbours algorithm to form the proposed RBFNDDA-KNN model. Given a set of labelled data samples, the RBFNDDA network undergoes a constructive learning algorithm that exhibits a greedy inserti