A metodologia apresentada neste trabalho contempla os aspectos relevantes para o desenvolvimento de modelos de otimização e de simulação combinados visando a análise de sistemas de reservatórios, e de regras operativas. Foram propostas quatro regras operativas para o Sistema Cantareira (SC), baseadas em uma série de afluências críticas (2003 - 2017). O trabalho foi desenvolvido em três etapas. Na primeira etapa foi utilizado um modelo de programação dinâmica (PD) para otimizar o comportamento do SC com relação ao atendimento das principais demandas. Na segunda etapa duas redes neurais artificiais (RNA) foram utilizadas para se obter as regras operativas para o SC, a partir dos resultados da primeira etapa. O modelo de PD foi calculado com o software CSUDP, e a RNA foi formulada e calculada com o solver padrão do Microsoft Excel. As regras obtidas foram baseadas em estados, ou faixas, de armazenamento do reservatório. Na terceira etapa, as regras operativas foram simuladas para a série histórica do SC, de 1930 a 2017, com auxílio do modelo de rede de fluxo AcquaNet. O trabalho fornece subsídios para aplicações de modelos de otimização e para obtenção de políticas de operação em sistemas de reservatórios. A comparação das regras operativas fornece informações relevantes a respeito dos impactos dos estados de armazenamento considerados e dos valores requeridos para as demandas, na operação do reservatório ao longo da série. A Regra operativa 1 destaca-se por seu desempenho, fornecendo vazões de 33 m³/s com 80% de garantia para a região metropolitana de São Paulo (RMSP), e com menores falhas no atendimento às demandas durante para a série histórica. / The present work provides guidelines for application of optimization and simulation models combined, in reservoir system and reservoir operation analysis. Four operation rules based on a series of critical inflows (2003 - 2017), are proposed for the Cantareira System (CS). The study was developed in three stages. In the first stage, a dynamic programming model (DP) was used to optimize the reservoir releases to the main demands. In the second stage, two artificial neural networks (ANR) were used to obtain the operation rules for SC, based on the results of the first stage. The DP model was solved using CSUDP software, and the ANR model was built and solved using Microsoft Excel. The operation rules were based on the reservoir\'s storage states or ranges. In the third stage, the operation rules were simulated for the system\'s historical inflow series, from 1930 to 2017, using the simulation net-flux model AcquaNet. In the last stage, reservoir operation rules were tested for the Cantareira system\'s historical inflow series, from 1930 to 2017, using the simulation net-flux model AcquaNet. The methodology provides relevant information for the analysis of optimization models and for operation rules in reservoir systems. The comparison of the proposed operation rules provides relevant information on the impacts of volume ranges, and of demand requirement values on long-term reservoir operation. The operation policy 1 shows best performance, providing supply of 33 m³/s to Metropolitan Region of São Paulo (MRSP) during 80% of the period, and with less failures during the historical series.

Os Sistemas de Informação Geográfica (SIG) são sistemas que possuem uma grande variedade de aplicações e podem ser utilizados para tomada de decisões. O presente trabalho apresenta um SIG para localização de pontos de abastecimento de água dentro de um município. Através deste SIG o corpo de bombeiros tem melhores condições de determinar quais os locais ideais para abastecimento de uma viatura durante o atendimento a uma ocorrência de incêndio. Uma pesquisa-ação foi realizada para acompanhar a implantação deste SIG dentro de um posto do corpo de bombeiros. A partir do uso desta ferramenta os bombeiros podem tomar decisões mais rápidas e precisas, melhorando o desempenho da organização / The Geographic Information System (GIS) are systems that possess a great variety of applications and can be used for taking of decisions. The present work inside presents a GIS for localization of points of water supplying of a city. Through this GIS the body of firemen it has better conditions to determine which the ideal places for supplying of a vehicle during the attendance to a fire incident. An action research was realized to follow the implantation of this GIS in the fire department. From the use of this tool the firemen can take faster and necessary decisions, improving the performance of the organization

CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior / A velocidade de concepÃÃo e de execuÃÃo das infraestruturas tem aumentado devido à utilizaÃÃo de softwares e equipamentos eficientes, o que tem exigido um melhor desempenho de cada etapa. No entanto, apesar dos custos envolvidos com equipamentos serem os itens de maior peso na construÃÃo rodoviÃria, poucos sÃo os sistemas existentes de apoio à decisÃo para a seleÃÃo das frotas. Propostas de seleÃÃo de frotas tÃm sido elaboradas por pesquisadores no Brasil e no mundo, porÃm a maioria consideram apenas caminhÃes e escavadeiras/carregadeiras ou scrapers. Este trabalho tem como objetivo desenvolver um sistema de apoio à decisÃo na seleÃÃo de motoniveladoras para a execuÃÃo de obras de terraplenagem e de pavimentaÃÃo, denominado SADPATROL. Inicialmente, foi feita uma anÃlise da evoluÃÃo tecnolÃgica do equipamento motoniveladora visando verificar a influÃncia destas melhorias sobre o aumento da produtividade. Foram analisadas as equaÃÃes existentes na literatura para o cÃlculo de produtividade e apÃs verificada a representatividade da equaÃÃo utilizada no paÃs esta foi escolhida para compor o SADPATROL, com as devidas alteraÃÃes em suas variÃveis. AtravÃs da anÃlise de cada variÃvel da equaÃÃo foi possÃvel identificar o quanto as mesmas influenciavam no resultado da produÃÃo desta forma, foram implementadas melhorias, como a inserÃÃo de valores padrÃes para as variÃveis do sistema, permitindo a obtenÃÃo de resultados mais precisos, caso o usuÃrio nÃo possua dados medidos em campo. O SADPATROL possui cadastrado em seu banco de dados 46 tipos de motoniveladoras, dos mais variados modelos e tamanhos, de 12 fabricantes distintos. à possibilitado ao usuÃrio calcular a frota com equipamentos prÃprios e verificar se esta atende ao prazo da obra. Caso o prazo nÃo seja atendido pela frota prÃpria ou o usuÃrio nÃo possua equipamentos, o sistema executa as informaÃÃes da obra para todos os equipamentos do banco de dados e fornece a soluÃÃo com as 46 opÃÃes organizadas em frotas, em ordem crescente de quantidade de equipamento. à possibilitado ainda selecionar os equipamentos nos quais se possui informaÃÃo de custo horÃrio, para assim obter a frota de menor custo. Toda a multiplicidade de informaÃÃes necessÃrias à seleÃÃo de motoniveladoras, e suas inter-relaÃÃes e dependÃncias, foram organizadas de forma sistÃmica no software SADPATROL, diminuindo assim o empirismo e a dependÃncia da experiÃncia humana na seleÃÃo de frotas. A presente pesquisa pode ainda contribuir para auxiliar a elaboraÃÃo de normas tÃcnicas e para a disseminaÃÃo do conhecimento sobre o referido equipamento. / The demands on speed and efficiency of infrastructure design and construction has increased due to the use of software and more productive equipment, which has required better performance of equipment planners at each step. However, even considering that the costs associated with equipment are one of the items with the greatest weight in road construction, there are few computerized systems for fleet selection decision support. Fleet selection systems have been developed by researchers in Brazil and worldwide, but most of them consider only trucks and excavators/loaders or scrapers. This research aims at developing a decision support system for the selection of motor graders for construction activities involving earthmoving and paving works named SADPATROL. Initially, an analysis of the motor grader technological evolution was performed in order to evaluate the influence of the improvements on productivity gains. The equations presented in the literature were studied for productivity calculation and, after verifying the suitability of the equation, the equation was incorporated in the SADPATROL system with the necessary changes in its variables. Through the analysis of the variables in the equation, it was possible to identify how they influenced the productivity. Through this analysis, improvements were implemented. These improvements consisted of the inclusion of standard values for the system variables, allowing the achievement of more accurate results if the user has no data for productivity measured in the field. The SADPATROL system has 46 types of motor graders included in its database, from many different models and sizes and from 12 different manufacturers. The user is able to plan the fleet with its own equipment and verify if it satisfies the construction project deadline. If the deadline cannot be satisfied using the available fleet or the user has no equipment, the system performs the construction planning using all database equipment and provides the optimal solution with 46 options organized into fleets in increasing order according to the amount of equipment needed. It is also possible for the user to select the equipment using time cost information and, thus, achieve the lowest cost fleet. The significant amount of information necessary for motor graders selection and its inter-relationships and dependencies were organized in a systematic way in the SADPATROL system, reducing, the empiricism and the dependence on human expertise in selecting fleets. This research may also help in assisting in the development of technical standards and expanding the dissemination of knowledge about such equipment.

The increasing intensity and frequency of precipitation in recent decades, combined with the human interventions in watersheds, has drastically altered the natural regimes of water and sediment transport in watersheds over the whole contiguous United States. Sediment-transport related concerns include the sustainability of aquatic biology, the stability of the river morphology, and the security and vulnerability of various riverine structures. For the present context, the concerns are related to the acceleration of upland erosion (sediment production) and in-stream sediment-transport processes that eventually lead to sediment accumulation at culverts (structures that pass streams under roadways). This nuisance has become widespread in many transportation agencies in the United States, as it has a direct bearing on maintaining normal culvert operations during extreme flows when these waterway crossings are essential for the communities they serve. Despite the prevalence of culvert sedimentation, current specifications for culvert design do not typically consider aspects of sediment transport and deposition. The overall study objective is to systematically identify the likelihood of culvert sedimentation as a function of stream and culvert geometry, along with landscape characteristics (process drivers of culvert sedimentation) in the culvert drainage area. The ideal approach for predicting sedimentation is to track sediment sources dislocated from the watershed, their overland movement, and their delivery into the streams using physical-based modeling. However, there are considerable knowledge gaps in addressing the sedimentation at culverts as an end-to-end process, especially in connecting the upland with in-stream processes and simulating the sediment deposition at culverts in non-uniform, unsteady flows, while also taking into account the vegetation growth in culverts’ vicinity. It is, therefore, no surprise that existing research, textbooks, and guidelines do not typically provide adequate information on sediment control at culverts. This dissertation presents a generalizable data-driven framework that integrates various machine-learning and visual analytics techniques with GIS in a web-based geospatial platform to explore the complex environmental processes of culvert sedimentation. The framework offers systematic procedures for (1) classifying the culvert sedimentation degree using a time-series of aerial images; (2) identifying key process-drivers from a variety of environmental and culvert structural characteristics through feature selections and interactive visual interfaces; (3) supporting human interactions to perceive empirical relationships between drivers and the culvert sedimentation degree through multivariate Geovisualization and Self-Organizing Map (SOM); and (4) forecasting culvert sedimentation potential across Iowa using machine learning algorithms. Developed using modular design and atop national datasets, the framework is generalizable and extendable, and therefore can be applied to address similar river management issues, such as habitat deterioration and water pollution, at the Contiguous US scale. The platform developed through this Ph.D. study offers a web-based problem-solving environment for a) managing inventory and retrieving culvert structural information; b) integrating diverse culvert-related datasets (e.g., culvert inventory, hydrological and land use data, and observations on the degree of sedimentation in the vicinity of culverts) in a digital repository; c) supporting culvert field inspections and real-time data collection through mobile devices; and d) hosting the data-driven framework for exploring culvert sedimentation drivers and forecasting culvert sedimentation potential across Iowa. Insights provided through the data-driven framework can be applied to support decisions for culvert management and sedimentation mitigation, as well as to provide suggestions on parameter selections for the design of these structures.

Os desafios de atender as necessidades do consumidor com uma oferta sustentável de alimentos desponta a aquaponia, que pode desempenhar importante papel no enfrentamento do aumento da demanda de uma crescente população mundial, apresentando resultados positivos incluindo renda, diversificação, melhoria na segurança alimentar, nutrição e benefícios ambientais. O presente trabalho teve como objetivo analisar a viabilidade econômico-financeira de investimento da implantação de uma aquaponia para cultivo de hortaliças (alface e rúcula) consorciadas à produção de tilápia, na cidade de Santa Cruz das Palmeiras/São Paulo. A metodologia seguida para o desenvolvimento deste estudo está amparada nos princípios da analise economia, dos custos de produção e dos aspectos técnicos da Engenharia de Pesca e Agronômica. Foi realizada a coleta de dados de campo para uma padronização de preços de insumos (ração, mudas, juvenil), serviços de documentação, embalagens, salarios, taxas, impostos, preço de mercado das hortaliças e do peixe, custo dos equipamentos e estrutura. Para o processo de avaliação do projeto de investimento foi elaborada uma análise financeira por meio do cálculo do volume de investimentos necessários para a instalação da aquaponia mediante a entrada das receitas e das despesas que ocorreram ao longo de dez anos. Os cálculos foram realizados com auxílio da planilha eletrônica do Software Excel. Para a implantação do empreendimento, a análise de Retorno do Investimento para um período de tempo de 10 anos aplicados a três diferentes cenários (C1 100% de venda para atacado, C2 100% de venda para o varejo e C3 50% de venda para tacado e 50% venda para varejo), indica uma Taxa Interna de Retorno (TIR) de -18,35% para C1, de 71,18% para C2 e de 35,35% para C3; Valor Presente Líquido (VPL) de R$ -168.406,61 para C1, de R$ 871.809,94 para C2 e de R$ 351.701,66 em C3; o Índice de Lucratividade de Longo-Prazo (IL) de 0,200 em C1, de 5,141 em C2 e de 2,670 em C3; a Taxa de Retorno (TR) em C1 é de -79,99%, em C2 de 414,07% e em C3 de 167,04%. Os investimentos produziram indicadores que apontam a viabilidade econômico-financeira para este projeto nos cenários 2 e 3 propostos. A implantação do empreendimento se mostrou favorável positivamente nestes dois cenários de receitas e o período de Retorno Econômico (Payback descontado) do investimento para estes cenários é de mais de 20 anos em C1, para o início do segundo ano em C2 e para o início do quarto ano em C3. / Challenges of meeting consumer needs with sustainable food supply highlight aquaponics that can play an important role in facing the rising demand of a growing world population, with positive results including income, diversification, improvement in food security, nutrition and benefits environmental impacts. The present paper had the objective of analyzing the economical and financial feasibility of investing the implantation of an aquapony for the cultivation of vegetables (lettuce and arugula) consorted to the production of tilapia, in the city of Santa Cruz das Palmeiras / São Paulo. The methodology used for the development of this study is based on the principles of economics, production costs and technical aspects of Fisheries and Agronomy Engineering. Field data were collected for a standardization of input prices (ration, seedlings, juvenile), documentation services, packaging, wages, taxes, market price of vegetables and fish, equipment costs and structure. For the evaluation of the investment project, a financial analysis was elaborated by calculating the volume of investments necessary for the installation of the aquaponics through the entry of revenues and expenses that occurred over ten years. The calculations were performed using the Excel Software spreadsheet. For the implementation of the enterprise, the Investment Return analysis for a time period of 10 years applied to three different scenarios (C1 100% for wholesale, C2 100% for retail and C3 50% for sale and 50% for retail), indicates an Internal Rate of Return (TIR) of -18.35% for C1, 71.18% for C2 and 35.35% for C3; Net Present Value (NPV) of R $ -168,406.61 for C1, R $ 871,809.94 for C2 and R $ 351,701.66 for C3; the Long-Term Profitability Index (IL) of 0.200 in C1, 5,141 in C2 and 2,670 in C3; the Return Rate (TR) in C1 is -79.99%, C2 is 414.07%, and C3 is 167.04%. The investments produced indicators that indicate the economic-financial viability for this project in scenarios 2 and 3 proposed. The implementation of the enterprise proved to be positively favorable in these two revenue scenarios and the Economic Payback period of the investment for these scenarios is more than 20 years in C1, for the beginning of the second year in C2 and for the beginning of the fourth year in C3.

Managing projects in an organization, especially a project-oriented organization, is a challenging task. Project data has a large volume and is complex to manage. It is different from managing a single project, because one needs to integrate and synthesize information from multiple projects and multiple perspectives for high-level strategic business decisions, such as aligning projects with business objectives, balancing investment and expected return, and allocating resources. Current methods and tools either do not well integrate multiple aspects or are not intuitive and easy to use for managers and executives. In this dissertation project, a multidimensional and visual exploration approach was designed and evaluated to provide a unique and intuitive option to support decision making in project portfolio management. The research followed a general design science research methodology involving phases of awareness of problem, suggestion, development, evaluation and conclusion. The approach was implemented into a software system using a prototyping method and was evaluated through user interviews. The evaluation result demonstrates the utility and ease-of-use of the approach, and confirms design objectives. The research brings a new perspective and provides a new decision support tool for project portfolio management. It also contributes to the design knowledge of visual exploration systems for business portfolio management by theorizing the system.

Due to complexity of biomedical problems, adaptive and intelligent knowledge discovery and data mining systems are highly needed to help humans to understand the inherent mechanism of diseases. For biomedical classification problems, typically it is impossible to build a perfect classifier with 100% prediction accuracy. Hence a more realistic target is to build an effective Decision Support System (DSS). In this dissertation, a novel adaptive Fuzzy Association Rules (FARs) mining algorithm, named FARM-DS, is proposed to build such a DSS for binary classification problems in the biomedical domain. Empirical studies show that FARM-DS is competitive to state-of-the-art classifiers in terms of prediction accuracy. More importantly, FARs can provide strong decision support on disease diagnoses due to their easy interpretability. This dissertation also proposes a fuzzy-granular method to select informative and discriminative genes from huge microarray gene expression data. With fuzzy granulation, information loss in the process of gene selection is decreased. As a result, more informative genes for cancer classification are selected and more accurate classifiers can be modeled. Empirical studies show that the proposed method is more accurate than traditional algorithms for cancer classification. And hence we expect that genes being selected can be more helpful for further biological studies.

Availability of data on accidents and chemical inventories, together with assessment and analysis tools is a prerequisite for integrated control of industrial accidents. Although Turkey has a developing industry, legislative measures for control of industrial accidents are lacking, past accidents are not systematically enlisted and industrial facilities and hazardous substances thereof are not properly registered. While some accident data is available in international databases, they are incomplete and erroneous. In the present study, a decision support system has been developed for collection and analysis of past accident information, assessment of current accident potentials of industrial establishments and modeling of probable accidents to reveal risks possessed thereby. The system supports web based multilingual and multi-user environment,and aims contribution of all interested parties in a collaborative manner. Information on technological accidents can be systematically archived together with reference data and visual materials. Initial data covering a time period of 30 years has been provided. The system is capable of storing hazard classifications and physico-chemical properties of substances, and providing standardized data for calculations. It can determine major-accident potential of industrial facilities as dictated by the 96/82/EC Directive of the EU and update relevant information automatically as required. An easy to use accident model for rapid assessment of off-site consequences of industrial accidents is also featured. Developed system allows integrated management of data on industrial accidents and provides decision support tools for assessing current and future accident potential,which can be used for national as well as the EU needs.

Performance-based landfill design approach is a relatively new design approach adopted recently in solid waste management and applied in USA, European Union countries and some developing-economy countries like South Africa. This approach rejects the strict design criteria and accommodates a design that selects the most appropriate design components of a landfill (final cover, bottom liner, and leachate collection system) and their design details to result in the best overall performance with respect to performance criteria (groundwater contamination and stability) considering the system variables (climatic conditions of the site, site hydrogeology, and size of the landfill). These design components, performance criteria and design variables involved in decision process make performance-based landfill design a complex environmental problem. Decision support systems (DSS) are among the most promising approaches to confront this complexity. The fact that different tools can be integrated under different architectures confers DSSs ability to confront complex problems, and capability to support decision-making processes. In this thesis study, a DSS to aid in the selection of design components considering the design variables and performance criteria for performance-based landfill design was developed. System simulation models and calculation modules were integrated under a unique DSS architecture. A decision support framework composed of preliminary design and detailed design phases were developed. The decision of appropriate design components leading to desired performance was made based on stability issues and vulnerability of groundwater, using knowledge gathered from DSS. Capabilities and use of the developed DSS were demonstrated by one real and one hypothetical landfill case studies.

In the recent years, ongoing debates in the mineral sector has shown that efficient use of natural resources is of vital importance as the use of minerals is essential for modern living. Especially, in the context of sustainable development, it is required that mineral resources should be exploited to maximize the contribution to the well being of current generation without depriving the potential for future generations to meet their own needs. The aim of this thesis is to develop a decision support system using system dynamics methodology where