CH4goat is a neural network models for calculate the methane emission from goats 🐐. It contains two black-box model (model1 & model2) using the dataset from Konkuk University.
# The development version from GitHub:
# install.packages("devtools")
devtools::install_github("adatalab/CH4goat")
The package contains two black-box model derived from the in vivo enteric methane dataset using respiration-metabolism chamber system.
model1
plot(model1)
model2
plot(model2)
# making a base frame for predict the methane emission from goats
base_frame(model = 1) # use when using model1 (inputs = DMI, OMI, CPI, NDFI, DDMI, DOMI, DCPI, and DNDFI)
base_frame(model = 2) # use when using model2 (inputs = DMI, OMI, CPI, and NDFI)
# OR read the example excel file
example1 <- readxl::read_excel("model1-example.xlsx")
example1_nor <- normalization(data = example1)
# calculating the methane emission from goats using neural network model.
result <- neuralnet::compute(model1, example1_nor)
denormalization(result$net.result) # unit is L/d
This package is under development. Everyone can contribute to this package. If you have the in vivo data of goats and want to progress this model, please contact via email 📧 or github issue
Email: ruminoreticulum@gmail.com