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Optimisation Procedure (optimisation + procedure)

Distribution by Scientific Domains
Chemistry60%

Selected Abstracts

H-methods in applied sciences

JOURNAL OF CHEMOMETRICS, Issue 3-4 2008
Agnar Höskuldsson
Abstract The author has developed a framework for mathematical modelling within applied sciences. It is characteristic for data from ,nature and industry' that they have reduced rank for inference. It means that full rank solutions normally do not give satisfactory solutions. The basic idea of H-methods is to build up the mathematical model in steps by using weighing schemes. Each weighing scheme produces a score and/or a loading vector that are expected to perform a certain task. Optimisation procedures are used to obtain ,the best' solution at each step. At each step, the optimisation is concerned with finding a balance between the estimation task and the prediction task. The name H-methods has been chosen because of close analogy with the Heisenberg uncertainty inequality. A similar situation is present in modelling data. The mathematical modelling stops, when the prediction aspect of the model cannot be improved. H-methods have been applied to wide range of fields within applied sciences. In each case, the H-methods provide with superior solutions compared to the traditional ones. A background for the H-methods is presented. The H-principle of mathematical modelling is explained. It is shown how the principle leads to well-defined optimisation procedures. This is illustrated in the case of linear regression. The H-methods have been applied in different areas: general linear models, nonlinear models, multi-block methods, path modelling, multi-way data analysis, growth models, dynamic models and pattern recognition. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Optimal capacitors on-line operation on distribution networks by an integrated control system based on local neurocontrollers

EUROPEAN TRANSACTIONS ON ELECTRICAL POWER, Issue 3 2002
I. Arces
This work proposes a contribution to the problem of an optimal control of switched capacitor banks installed in radial distribution networks, by studying the possibility of adopting an integrated control strategy based on the use of neural local controllers able to manage the status of every compensation bank. In order to analyse the feasibility of this solution, the kind of control proposed was implemented in a particular study case, which allowed to compare the performance of a set of local neurocontrollers with the results of a centralized optimisation procedure, for different conditions of load and network configuration. [source]

Reactive Flow Model Parameter Estimation Using Genetic Algorithms

PROPELLANTS, EXPLOSIVES, PYROTECHNICS, Issue 3 2010
Jose Baranda, Ribeiro
Abstract An original real-coded genetic algorithm methodology that has been developed for the estimation of the parameters of the Tarver reactive flow model of shock initiation and detonation of heterogeneous solid explosives is described in detail. This methodology allows, in a single optimisation procedure and without the need for a starting solution, to search for the 15 parameters of the reaction rate law of the reactive flow model that fit the numerical results to the experimental ones. The developed methodology was applied and tested with an experimental situation, described in detail in the literature, involving the acceleration of a tantalum metal plate by an LX-17 explosive charge. The obtained parameters allow a very good description of the experimental results and are close to the ones originally used by Tarver and co-authors in their simulation of the phenomenon. [source]

H-methods in applied sciences

JOURNAL OF CHEMOMETRICS, Issue 3-4 2008
Agnar Höskuldsson
Abstract The author has developed a framework for mathematical modelling within applied sciences. It is characteristic for data from ,nature and industry' that they have reduced rank for inference. It means that full rank solutions normally do not give satisfactory solutions. The basic idea of H-methods is to build up the mathematical model in steps by using weighing schemes. Each weighing scheme produces a score and/or a loading vector that are expected to perform a certain task. Optimisation procedures are used to obtain ,the best' solution at each step. At each step, the optimisation is concerned with finding a balance between the estimation task and the prediction task. The name H-methods has been chosen because of close analogy with the Heisenberg uncertainty inequality. A similar situation is present in modelling data. The mathematical modelling stops, when the prediction aspect of the model cannot be improved. H-methods have been applied to wide range of fields within applied sciences. In each case, the H-methods provide with superior solutions compared to the traditional ones. A background for the H-methods is presented. The H-principle of mathematical modelling is explained. It is shown how the principle leads to well-defined optimisation procedures. This is illustrated in the case of linear regression. The H-methods have been applied in different areas: general linear models, nonlinear models, multi-block methods, path modelling, multi-way data analysis, growth models, dynamic models and pattern recognition. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Identification of desulphoglucosinolates in Brassicaceae by LC/MS/MS: Comparison of ESI and atmospheric pressure chemical ionisation-MS

MOLECULAR NUTRITION & FOOD RESEARCH (FORMERLY NAHRUNG/FOOD), Issue 12 2007
Nadine S. Zimmermann
Abstract In order to develop a sensitive method for the detection of desulphoglucosinolates by HPLC-MS, the two most common interfaces for HPLC-MS, atmospheric pressure chemical ionisation (APCI) and ESI, were compared. While working with the APCI-interface the evaporation temperature and corona amperage were optimised. In doing so 300°C and 6 ,A proved to be most suitable for aliphatic and indole desulphoglucosinolates. The use of formic acid instead of water in the eluent in HPLC-ESI-MS measurements increased the sensitivity for the indole desulphoglucosinolates in the presence of 1 mM formic acid, while the sensitivity for the aliphatic desulphoglucosinolate desulphoglucoraphanin was substantially increased by the presence of 5 mM formic acid. Using an Agilent ion trap, two optimisation procedures for the MS parameters, smart and expert mode, were available. In smart mode the software optimises several parameters automatically, which is much more time efficient than expert mode, in which the optimisation is done manually. It turned out that ESI-MS is most sensitive in smart mode, while for APCI-MS a higher sensitivity could be gained using the expert mode. Comparing both interfaces, APCI-MS was more sensitive than ESI-MS. However, no additional information, in terms of structure determination, was obtained by APCI-MS. [source]