Learning and NonLinear Models

Logo Learning & Nonlinear Models (L&NLM) is the official scientific journal of ABRICOM (Brazilian Association of Computational Intelligence, formerly,  Sociedade Brasileira de Redes Neurais – SBRN).

The journal is published online since 2003 (ISSN: 1676-2789) and we are commited with the use of persistent identifiers for both, papers and researchers. Therefore all papers are permanently indexed with DOI and researchers are requested to include their ORCID identifier along the paper submission. When papers are published online, they are immediately linked with their authors.

L&NLM aims at publishing research and survey papers about all areas of Computational Intelligence (CI) and Non-Linear Systems (NLS). The journal accepts research papers reporting theoretical advancements as well as applications papers. Surveys of the state-of-the-art methods are also accepted. The areas of interest of the journal include, but not limited to, the following topics:

 

Methods:

      • Artificial neural networks
      • Deep learning
      • Evolutionary computation
      • Swarm intelligence
      • Fuzzy systems
      • Stochastic modelling
      • Machine learning
      • Metaheuristics and hyperheuristics
      • Complex networks
      • Quantum computing

Applications:

      • Engineering optimization
      • Large-scale combinatorial problems
      • Computer vision
      • Data mining
      • Time-series modelling
      • Chaotic systems
      • Robotics
      • Systems identification
      • Pattern recognition
      • Biomedicine and bioinformatics
      • Fuzzy modelling and control
      • Non-linear control systems
      • Image processing
      • Signal processing