@ARTICLE{id:Siminski2014Neuro,
  author = {Krzysztof Simi\'{n}ski},
  title = {Neuro-fuzzy system with weighted attributes},
  journal = {Soft Computing},
  volume = {18}, 
  number = {2}, 
  pages = {285--297}, 
  year = {2014},
  doi = {10.1007/s00500-013-1057-z},
  abstract = {The paper presents the neuro-fuzzy system with weighted attributes. 
Its crucial part is the fuzzy rule base composed of fuzzy rules (implications). 
In each rule the attributes have their own weights. In our system the weights
of the attributes are numbers from the interval $[0, 1]$ and they are not global: 
each fuzzy rule has its own attributes' weights, thus it exists in its own weighted subspace.

The theoretical description is accompanied by  results of experiments on real life 
data sets. They show that the neuro-fuzzy system  with weighted attributes can elaborate
more precise results than the system that does not apply  weights to attributes. Assigning 
weights to attributes can also discover  knowledge about importance of attributes and their relations.},
   note = {[25 pkt; 2012 Impact Factor 1.124]},
}