Environmental Impact Assessments of Heavy Metal on Soil Using ANN Modeling Techniques
Artificial Neural Network Model used to predict the Heavy metal in various localities Topsoil samples (0-20cm) were taken at various locations with reference to latitude and longitude. The concentration of heavy metal Fe were analyzed in the Atomic Absorption spectrometer. An artificial neural network technique is used to develop a model to predict the constituents of the heavy metal in the soils such as Mercury, Cadmium, Iron. The developed neural networks consists of 2 input neurons for latitude and longitude, 6 hidden layers consisting of 10 to 20 neurons in each layer for training the data and 1 neuron to predict the constituents of the heavy metal in the soils.
Keywords- Heavy Metal, Artificial Neural Network, Soil pollution, Assessment of Heavy metal.