| Grant number: | 16/15634-3 |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| Start date: | February 01, 2017 |
| End date: | December 31, 2017 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques |
| Principal Investigator: | Elisa Yumi Nakagawa |
| Grantee: | Bruno Sena da Silva |
| Host Institution: | Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
Abstract Systems-of-systems have gained an important role in industry and academia in response to the continued growth of the complexity and size of software systems, which are often resulting from the composition of several other independent and complex systems. In this scenario, it also observed the growing amount of data collected and generated from these systems. In the context of SoS, a major problem is the useful knowledge extraction from existing data, as they are located within each constituent and end up not generating complete information about the operation of the system as a whole, and therefore not assisting in decision-making. Thus, the main objective of this project is to model and implement a system that assists in the SoS knowledge extraction that is representative enough to assist in decision making of users and generate a new emergent behavior. As a more specific goal, we intend to analyze a flood monitoring SoS to find problems that can be solved basing on the existing data in the constituents, such as predicting whether there is a high risk of flooding in the next 48 hours to some location, and solve them using machine learning techniques that are consistent with the application, generating a result that can act as a new emergent behavior within the SoS. This system will be considered as a new constituent of SoS and will be evaluated with the analysis of information obtained after extraction in order to verify whether this new behavior generated is valid and will cause positive impacts. It is intended, therefore, assist in the development and evolution of SoS to provide a mechanism for making more effective decision. (AU) | |
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