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 all papers are permanently indexed with DOI.

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:



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


      • Engineering optimization
      • Large-scale combinatorial problems
      • Computer vision
      • Complex systems
      • 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