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Comparative study of mixture designs for complex phenomena
- Source :
- Chemometrics and Intelligent Laboratory Systems, Chemometrics and Intelligent Laboratory Systems, Elsevier, 2018, 178, pp.65-72. ⟨10.1016/j.chemolab.2018.05.004⟩, Chemometrics and Intelligent Laboratory Systems, 2018, 178, pp.65-72. ⟨10.1016/j.chemolab.2018.05.004⟩
- Publication Year :
- 2018
- Publisher :
- HAL CCSD, 2018.
-
Abstract
- In the field of formulation, the behaviour of phenomena studied are often complex, including non-linear or chaotic zones which make classical strategies based on polynomial models inappropriate. In these situations, uniform experimental designs and kriging models are recommended. Nonetheless, when researchers have to set up an experimental strategy, they must choice the class of designs to be constructed, the number of experiments to be performed and the modeling kriging parameters to be used. To help with these choices, we propose a catalogue combining various uniform designs characterized by several intrinsic quality criteria and to establish decision-making rules linking these criteria to the quality of the information obtained from the design.
- Subjects :
- Polynomial
Class (set theory)
Mathematical optimization
Computer science
media_common.quotation_subject
0211 other engineering and technologies
Chaotic
02 engineering and technology
01 natural sciences
Field (computer science)
Analytical Chemistry
Set (abstract data type)
[SPI]Engineering Sciences [physics]
Kriging
Quality (business)
Spectroscopy
ComputingMilieux_MISCELLANEOUS
media_common
021103 operations research
Process Chemistry and Technology
Design of experiments
010401 analytical chemistry
0104 chemical sciences
Computer Science Applications
[STAT]Statistics [stat]
Software
Subjects
Details
- Language :
- English
- ISSN :
- 01697439
- Database :
- OpenAIRE
- Journal :
- Chemometrics and Intelligent Laboratory Systems, Chemometrics and Intelligent Laboratory Systems, Elsevier, 2018, 178, pp.65-72. ⟨10.1016/j.chemolab.2018.05.004⟩, Chemometrics and Intelligent Laboratory Systems, 2018, 178, pp.65-72. ⟨10.1016/j.chemolab.2018.05.004⟩
- Accession number :
- edsair.doi.dedup.....25e41d9a11091ca13b39512aece6d5cd
- Full Text :
- https://doi.org/10.1016/j.chemolab.2018.05.004⟩