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Hydrodynamic Modeling for Autonomous Underwater Vehicles Using Computational and Semi-Empirical MethodsGeisbert, Jesse Stuart 31 May 2007 (has links)
Buoyancy driven underwater gliders, which locomote by modulating their buoyancy and their attitude with moving mass actuators and inflatable bladders, are proving their worth as efficient long-distance, long-duration ocean sampling platforms. Gliders have the capability to travel thousands of kilometers without a need to stop or recharge. There is a need for the development of methods for hydrodynamic modeling. This thesis aims to determine the hydrodynamic parameters for the governing equations of motion for three autonomous underwater vehicles. This approach is two fold, using data obtained from computational flight tests and using a semi-empirical approach. The three vehicles which this thesis focuses on are two gliders (Slocum and XRay/Liberdade), and a third vehicle, the Virginia Tech Miniature autonomous underwater vehicle. / Master of Science
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Transcriptional Regulatory Mechanisms for Robust Somite SegmentationZinani, Oriana Q.H. 30 September 2021 (has links)
No description available.
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Modeling and Simulation of Damage Evolution in Crevice CorrosionBrackman, Matthew D. 01 August 2012 (has links)
No description available.
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Cell Loading and Product Sequencing Subject to Manpower Restrictions in Synchronized Manufacturing CellsYarimoglu, Fatih 27 April 2009 (has links)
No description available.
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Estatística espacial e redes neurais aplicadas no estudo de epidemias de huanglongbing e mancha preta na cultura dos citrosAndrade, André Gustavo de [UNESP] 26 November 2008 (has links) (PDF)
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andrade_ag_dr_jabo.pdf: 23073379 bytes, checksum: 890e280dd903085eca5cf094bbbb6ce3 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Para o estudo da viabilidade do emprego de metodologias de sistema de informação geográfica, geoestatística e redes neurais foram desenvolvidos dois ensaios. O primeiro visou a modelagem da evolução espaço-temporal da incidência do Huanglongbing ao longo dos anos de 2004, 2007 e 2008 em cinco grupos de idade (0 a 2 anos, 3 a 5 anos, 6 a 10 anos, mais de 10 anos, todas as idades), por meio da técnica geoestatística da krigagem e da técnica de inteligência artificial de rede neurais do tipo perceptron de múltiplas camadas com topologia 3x10x10x1, treinada pelo algoritmo da propagação elástica do erro. Neste ensaio foi ainda realizada a análise do modelo do semivariograma, cálculo da média zonal dos talhões dentro de cada faixa de idade e mesorregião do estado de São Paulo, e finalmente, foi previsto o padrão espacial da incidência da doença para o ano de 2009 pelas redes neurais. O segundo ensaio consistiu em se verificar o efeito do alinhamento de plantio na severidade da mancha preta dos citros e sua implicação na qualidade do suco e produção. Neste ensaio foram selecionados talhões distribuídos ao longo do cinturão citrícola paulista com diferentes alinhamentos de plantio, onde foram analisadas as variáveis supracitadas nas linhas de plantio e nas faces expostas da planta. / For viability study of using geographic information systems, geostatistics and neural networks two experiments were carried out. The first one was focused on modeling the spatial-temporal progress of Huanglongbing incidence in 2004, 2007 and 2008 on five age groups (0 – 2 years old, 3 – 5 years old, 6 – 7 years old, more than 10 years old and all ages) using the geostatistical technique of kriguing and the artificial intelligence technique of neural networks of multi-layer perceptron type with 3x10x10x1 topology, trained by resilient error propagation. Complementing the study the analysis of semivariogram model, zonal mean calculation of blocks on each age group were realized inside the mesoregions of São Paulo state and finally the disease incidence spatial pattern for 2009 was forecasted by the neural networks. The objective of the second experiment was verifying effect of planting alignment on citrus black spot severity and its implication on juice quality and production. On this experiment was selected blocks distributed among the São Paulo state citrus belt with different planting alignments, where was analyzed those variables on the lines and exposed faces.
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A Multi-Criteria Order Fulfillment Model for a Multi-Marketplace E-Retail Start-UpUran, Korhan 23 September 2019 (has links)
No description available.
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Estatística espacial e redes neurais aplicadas no estudo de epidemias de huanglongbing e mancha preta na cultura dos citros /Andrade, André Gustavo de. January 2008 (has links)
Orientador: Antonio de Goes / Banca: Margarete Camargo / Banca: Gener Tadeu Pereira / Banca: Renato Beozzo Bassanezi / Banca: Edson Luiz Furtado / Resumo: Para o estudo da viabilidade do emprego de metodologias de sistema de informação geográfica, geoestatística e redes neurais foram desenvolvidos dois ensaios. O primeiro visou a modelagem da evolução espaço-temporal da incidência do Huanglongbing ao longo dos anos de 2004, 2007 e 2008 em cinco grupos de idade (0 a 2 anos, 3 a 5 anos, 6 a 10 anos, mais de 10 anos, todas as idades), por meio da técnica geoestatística da krigagem e da técnica de inteligência artificial de rede neurais do tipo perceptron de múltiplas camadas com topologia 3x10x10x1, treinada pelo algoritmo da propagação elástica do erro. Neste ensaio foi ainda realizada a análise do modelo do semivariograma, cálculo da média zonal dos talhões dentro de cada faixa de idade e mesorregião do estado de São Paulo, e finalmente, foi previsto o padrão espacial da incidência da doença para o ano de 2009 pelas redes neurais. O segundo ensaio consistiu em se verificar o efeito do alinhamento de plantio na severidade da mancha preta dos citros e sua implicação na qualidade do suco e produção. Neste ensaio foram selecionados talhões distribuídos ao longo do cinturão citrícola paulista com diferentes alinhamentos de plantio, onde foram analisadas as variáveis supracitadas nas linhas de plantio e nas faces expostas da planta. / Abstract: For viability study of using geographic information systems, geostatistics and neural networks two experiments were carried out. The first one was focused on modeling the spatial-temporal progress of Huanglongbing incidence in 2004, 2007 and 2008 on five age groups (0 - 2 years old, 3 - 5 years old, 6 - 7 years old, more than 10 years old and all ages) using the geostatistical technique of kriguing and the artificial intelligence technique of neural networks of multi-layer perceptron type with 3x10x10x1 topology, trained by resilient error propagation. Complementing the study the analysis of semivariogram model, zonal mean calculation of blocks on each age group were realized inside the mesoregions of São Paulo state and finally the disease incidence spatial pattern for 2009 was forecasted by the neural networks. The objective of the second experiment was verifying effect of planting alignment on citrus black spot severity and its implication on juice quality and production. On this experiment was selected blocks distributed among the São Paulo state citrus belt with different planting alignments, where was analyzed those variables on the lines and exposed faces. / Doutor
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Cesta k lepší budoucnosti znamená pochopit minulost Matematické modelování výkonnosti podniku / The Way to Better Future Means to Understand the Past The Math ModellingMíková, Libuše January 2009 (has links)
The main aim of my diploma thesis is to prepare easy math model, which can help to understand the development of economic indicators in time. This math model will show the dependence and important moment in their development and can help to improve the efficiency of company. All math models will be working up in system Maple which is very good helper in working up of big group of data. The partial aim is to show characteristics of company, to valorize the efficiency of company and compare this efficiency with main competitors. The results will be recommendations which should help positive influence the future efficiency of company, help with choose of strategy and the make a better position on the market.
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Modeling the Light Field in Macroalgae AquacultureEvans, Oliver Graham, Evans January 2018 (has links)
No description available.
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A Predictive Model for Secondary RNA Structure Using Graph Theory and a Neural Network.Koessler, Denise Renee 08 May 2010 (has links) (PDF)
In this work we use a graph-theoretic representation of secondary RNA structure found in the database RAG: RNA-As-Graphs. We model the bonding of two RNA secondary structures to form a larger structure with a graph operation called merge. The resulting data from each tree merge operation is summarized and represented by a vector. We use these vectors as input values for a neural network and train the network to recognize a tree as RNA-like or not based on the merge data vector.
The network correctly assigned a high probability of RNA-likeness to trees identified as RNA-like in the RAG database, and a low probability of RNA-likeness to those classified as not RNA-like in the RAG database. We then used the neural network to predict the RNA-likeness of all the trees of order 9. The use of a graph operation to theoretically describe the bonding of secondary RNA is novel.
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