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Conclusions

Conclusions

  • Results are very Reliable for a 1-hr and 12-hr ahead Prediction.
  •  For this experiment, Atmospheric Variables didn't show too much influence.
  • More data is needed in order to train the GRNN to perform Predictions along all the year.
  • GRNN can be used to warn authorities over possible Environmental Contingencies.
  • Need to use Techniques to improve the Prediction Performance.
‹ Results for 24-hrs ahead PredictionsupFurther Work ›
The data used for this work, consisted only of data from months of December for 3 years. It's been demonstrated, that Pollutants concentration behaviour is different for all seasons. The literature also mentions that the more data we have to train the Neural Network, The More Accurate the output will be. No methods to diminish the error in predictions were used in this work.

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