New Environmental Prediction Model Using Fuzzy logic and Neural Networks
This work introduces a new prediction model. This prediction model is designed to accomplish its task by only one type of measurements while other prediction models need at least three types of measurements. This feature makes this model less expensive than other models. The user who works with other models such as Statistical model, Chemical model, Physical model and neural network model needs more than two types of measurements and if any type of these measurement is not available the user must buy the unavailable data to operate his or her model. This work uses this model for predicting the Gamma radiation levels measurements in ambient air. The results from this model are good enough to depend on it for environmental prediction, recognizing the artificial phenomena and covering lost or missing data and making a temporally monitoring system. This model can be used in any continuous environmental monitoring system.
Keywords: Data Mining, Environmental Prediction model, Fuzzy Logic, Neural Networks, Radiation Prediction.
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ABOUT THE AUTHORS
Abou-Bakr Ramadan
academy degree : professor job : head of Department of National Network for Monitoring Radioactivity
Ahmed El-Garhy
academy : assistant professor
Fathy Zaky
academy : assistant professor
Mazhar Mahmoud Hefnawi
academy degree : assistant teachear
Abou-Bakr Ramadan
academy degree : professor job : head of Department of National Network for Monitoring Radioactivity
Ahmed El-Garhy
academy : assistant professor
Fathy Zaky
academy : assistant professor
Mazhar Mahmoud Hefnawi
academy degree : assistant teachear