ImNN {ImNN} | R Documentation |
Neural Networks for Predicting Volume of Forest Trees
Description
Neural Networks for Predicting Volume of Forest Trees
Usage
ImNN(data, hidden_neurons_range)
Arguments
data |
Datasets |
Number of hidden neurons in neural network's two layers (layer 1 and layer 2) |
Value
results: Results
References
Jeelani, M.I., Tabassum, A., Rather, K and Gul,M.2023. Neural Network Modeling of Height Diameter Relationships for Himalayan Pine through Back Propagation Approach. Journal of The Indian Society of Agricultural Statistics. 76(3): 169–178
Tabassum, A., Jeelani, M.I., Sharma,M., Rather, K R ., Rashid, I and Gul,M.2022. Predictive Modelling of Height and Diameter Relationships of Himalayan Chir Pine . Agricultural Science Digest - A Research Journal. DOI:10.18805/ag.D-5555
Examples
library("ImNN")
data <- system.file("extdata", "data_test.csv", package = "ImNN")
data_test <- read.csv(data)
Model<-ImNN(data =data_test,hidden_neurons_range=2)
[Package ImNN version 0.1.0 Index]