Research

Mg Research

From internal reporting to world-wide dissemination through top JCR-indexed publications, we boost your organization's scientific capacities as well as its visibility in the research community. This enable your organization not only to improve operations results, but also to benefit from institutional and governmental recognition through R+D+i funding and certificates, or tax allowance for investment in research and innovation.

We can provide your research team with advanced knowledge in model programming in such a way that once the operational model has been jointly designed and developed, you can update it to incorporate new variables or extract aditional information. Your operational models can be programmed in Matlab© or in Python, which are reliable and flexible advanced scientific languages enabling you to perform a wide range of mathematical processes, interact with other languages such as C++, Java, HTTP or SQL, or to develop your own programs.

Up to now, we have developed deep research on multi-objective optimization techniques, bottom-up uncertainty analysis methods, visual analytics, cluster analysis and a number of statistical techniques applied to strategic planning, which we will be pleased to transfer to your institution.

Published works:

Our investigations on vulnerability analysis led us to carry out research on the state-of-the-art of urban vulnerability assessment (UVA) methods, as well as to develop a Decision Support System for selecting a proper assessment model. The results of this research were disseminated through several articles published in JCR indexed journals:

• Urban vulnerability assessment: Advances from the strategic planning outlook

• A discursive, many-objective approach for selecting more-evolved urban vulnerability assessment models

In addition, we have carried out deep research into uncertainty analysis applied to urban infrastructure strategic planning, proposing a method for a Dynamic Risk and Opportunity Simultaneous Evaluation (D-ROSE), and a method for Multi-scale Relational uncertainty Risk and Opportunity evaluation (Ms-ReRO):

• MS-ReRO and D-ROSE methods: assessing relational uncertainty and evaluating scenarios’ risks and opportunities on multi-scale infrastructure systems.

At this moment, we have one more paper being peer-reviewed by JCR indexed journals, in which we explore the efficacy of visual analytics and cluster analysis for reducing burdens along the decision-making process:

• VisualUVAM: a decision tool addressing the curse of dimensionality for the selection of urban vulnerability assessment models