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Spatial multivariate design in the plane and on stream networksLi, Jie 01 December 2009 (has links)
In environmental studies, measurements of interest are often taken on multiple variables. The results of spatial data analyses can be substantially affected by the spatial configuration of the sites where measurements are taken. Hence, optimal designs which result in data guaranteeing efficient statistical inferences need to be studied.
We study optimal designs on two large classes of spatial regions with respect to three design criteria, which were prediction, covariance parameter estimation, and empirical prediction. The first class of regions includes those in the plane, where Euclidean distance is used. The performance of the optimal designs is compared to that of randomly chosen designs. Optimal designs for a small example and a relatively large example are obtained. For the small example, complete enumeration of all possible designs is computationally feasible. For the large example, the computational difficulty in searching for the optimal spatial sampling design is overcome by a simulated annealing algorithm.
The second class of spatial regions includes streams and rivers, where the distance is defined as distance along the stream network. A moving average construction is used to establish valid covariance and cross-covariance models using stream distance. Optimal designs for small and large examples are obtained. An application of our methodology to a real stream network is included.
We discuss the impact of asymmetry in the cross covariance function on the spatial multivariate design. The relationship between multivariate optimal design and univariate optimal design if the multivariate design is restricted to be completely collocated is studied. The efficiency lost if we consider the design that is optimal within the class of collocated designs is discussed.
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Inteligência computacional aplicada à modelagem e otimização de bioprocessosAquino, Pedro Luiz da Mota e 29 April 2016 (has links)
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Previous issue date: 2016-04-29 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / This work deals with modeling applications, systematic and reliable optimization
methodologies of global search, and other computational tools. It is expected that
existing computational intelligence methods, encoded in an appropriate tool for the
application of process engineering assisted by computer, can lead to useful numerical
results for the modeling and optimization of different processes, including
biotechnological processes (focus of this work). Thus, different types of methodologies
suitable for computer applications, were studied here. The proposed methodologies
were implemented and evaluated for the development and optimization of culture media
for the fermentation process of Clostridium novyi type B, besides the fermentation
process and enzymatic hydrolysis of bagasse associated with the production of
bioethanol (1G and 2G). Thus, the potential application of these computational
techniques was evaluated to biotechnological systems in different approaches. More
specifically, it was performed: Classification of biotechnological systems (
"clustering") in kinetically similar regions to produce cellulosic ethanol (2G ethanol)
using fuzzy logic; estimation by global search of kinetic parameters to an alcoholic
fermentation model using Simmulated Annealing algorithm (SA) (Contributions to the
thematic project FAPESP 2011 / 51902-9); formulation and optimization of
economically viable culture media for Clostridium novyi type B using neuro-fuzzy data
modeling followed by global search which maximize productivity, also utilizing SA
algorithm as a search engine (this step of the project was conducted in partnership with
the veterinary pharmaceutical company Vallée SA). The computational tools presented
in this work were highly effective for modeling and optimization of the bioprocesses
studied. / Este trabalho aborda aplicações de modelagem, metodologias sistemáticas e confiáveis
de otimização por busca global, além de outras ferramentas computacionais. Espera-se
que métodos de inteligência computacional existentes, codificados em uma ferramenta
apropriada para a aplicação da engenharia de processos assistida por computador,
resultem em resultados numéricos úteis para a modelagem e otimização de diferentes
processos, incluindo-se os processos biotecnológicos (foco deste trabalho). Assim,
diferentes tipos de metodologias, apropriadas para aplicações em computador, foram
aqui estudadas. Os métodos propostos foram aplicados e avaliados ao desenvolvimento
e otimização de meios de cultura para o processo fermentativo do microrganismo
Clostridium novyi tipo B, além dos processos de fermentação alcoólica e hidrolise
enzimática de bagaço de cana, associados à produção de bioetanol (1G e 2G). Desta
forma, foi avaliado o potencial de aplicação destas técnicas computacionais aos sistemas
biotecnológicos, em diversas abordagens. Mais especificamente, foram realizadas:
classificação (“clustering”) de sistemas em regiões cineticamente semelhantes para a
produção de etanol celulósico (Etanol 2G) utilizando lógica Fuzzy; estimação por busca
global de parâmetros cinéticos do modelo para uma fermentação alcoólica utilizando o
algoritmo Simmulated Annealing (SA) (Contribuições ao projeto temático FAPESP
2011/51902-9); formulação e otimização do meio de cultura economicamente viável
para o Clostridium novyi tipo B utilizando a modelagem de dados por neuro-fuzzy
seguido de busca global da composição de meio que maximize a produtividade
utilizando também o algoritmo SA como ferramenta de busca global (esta etapa do
projeto foi realizado em parceria com a empresa farmacêutica veterinária Vallée S.A).
As ferramentas computacionais apresentadas neste trabalho se mostraram altamente
efetivas para a modelagem e otimização dos bioprocessos estudados." / FAPESP: 2011/51902-9. / FAPESP: 2008/56246-0.
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