Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Institut Polytechnique des Sciences Avancées

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (6/6 displayed)

  • 2022Hybrid Genetic Algorithms6citations
  • 2019Hybrid Genetic Algorithmscitations
  • 2014Variational Bayesian inversion for microwave imaging applied to breast cancer detectioncitations
  • 2014Variational Bayesian inversion for microwave breast imagingcitations
  • 2014A gradient-like variational Bayesian approach: Application to microwave imaging for breast tumor detection3citations
  • 2013Microwave tomography for breast cancer detection within a Variational Bayesian Approachcitations

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Duchêne, Bernard
4 / 7 shared
Mohammad-Djafari, Ali
4 / 4 shared
Ayasso, H.
4 / 4 shared
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2019
2014
2013

Co-Authors (by relevance)

  • Duchêne, Bernard
  • Mohammad-Djafari, Ali
  • Ayasso, H.
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booksection

Hybrid Genetic Algorithms

  • Gharsalli, Leila
Abstract

<jats:p>Hybrid optimization methods have known significant interest in recent years and are being growingly used to solve complex problems in science and engineering. For instance, the famous evolutionary Genetic Algorithm can integrate other techniques within its framework to produce a hybrid global algorithm that takes advantages of that combination and overcomes the disadvantages. Several forms of integration between Genetic Algorithms and other search and optimization techniques exist. This chapter aims to review that and present the design of a hybrid Genetic Algorithm incorporating another local optimization technique while recalling the main local search methods and emphasizing the different approaches for employing their information. A test case from the aerospace field is presented where a hybrid genetic algorithm is proposed for the mechanical sizing of a composite structure located in the upper part of a launcher.</jats:p>

Topics
  • impedance spectroscopy
  • composite