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  • 2000-2004  (2)
  • 2000  (2)
  • Key words Toluene diisocyanate  (1)
  • Keywords: Fuzzy clustering; Fuzzy modelling; Neural fuzzy systems; Non-linear system identification  (1)
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Years
  • 2000-2004  (2)
Year
  • 2000  (2)
Keywords
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    International archives of occupational and environmental health 73 (2000), S. 570-574 
    ISSN: 1432-1246
    Keywords: Key words Toluene diisocyanate ; Sampling efficiency ; Closed-face cassette ; Open-face cassette
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine
    Notes: Abstract Objectives: A modified closed-face cassette was developed for sampling and derivatizing airborne toluene diisocyanate (TDI). Methods: The cassette was assembled as a regular two-piece cassette sampler except that the whole inner surface of the sampler was loaded with coated filters to ensure that all of the aspirated TDI react with 1-(2-pyridyl) piperazine (1-2pp). Results: A test atmosphere study showed that the sampling efficiencies were 89.4% and 94.3% for 2,4-TDI and 2,6-TDI. One-third of the 2,4-TDI and 2,6-TDI mass was constantly collected on the top and middle-rim filters. A polyurethane (PU)-manufacturing plant study revealed an average of 35% and 33% of both isomer masses collected on the top and middle-rim filters. The 2,4-TDI collection of the closed-face cassette sampling was 21% higher than that of open-face sampling. Furthermore, consistent isomeric compositions of airborne 2,4-/2,6- TDI obtained from both types of samplers validated the use of the modified cassette sampler. Conclusions: The closed-face cassette sampler is capable of a higher collection of airborne TDI and the technique involved is as simple and feasible as that of the open-face sampler.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Neural computing & applications 9 (2000), S. 44-49 
    ISSN: 1433-3058
    Keywords: Keywords: Fuzzy clustering; Fuzzy modelling; Neural fuzzy systems; Non-linear system identification
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: A simple and effective fuzzy modelling approach is presented in this paper. A three-layer hierarchical clustering neural network is developed to build fuzzy rule-based models from numerical data. Differing from existing clustering-based methods, in this approach the structure identification of the fuzzy model is implemented on the basis of a class of sub-clusters created by a self-organising network instead of on raw data. By combined use of unsupervised and supervised learning, both structure identification and parameter optimisation of the fuzzy model can be carried out automatically. The simulation results show that the proposed method can provide good model structure for fuzzy modelling and has high computing efficiency.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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