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Neural network has potential in forestry modelling. This package is designed to create and assess Artificial Intelligence based Neural Networks with varying architectures for prediction of volume of forest trees using two input features: height and diameter at breast height, as they are the key factors in predicting volume, therefore development and validation of efficient volume prediction neural network model is necessary. This package has been developed using the algorithm of Tabassum et al. (2022) <doi:10.18805/ag.D-5555>.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10) |
| Imports: | stats, MLmetrics, ggplot2, neuralnet |
| Published: | 2023-10-12 |
| DOI: | 10.32614/CRAN.package.ImNN |
| Author: | M. Iqbal Jeelani [aut, cre], Fehim Jeelani [aut], Shakeel Ahmad Mir [aut], Syed Naseem Geelani [aut], Mushtaq Ahmad Lone [aut], Nazir A. Pala [aut], Faizan Danish [aut], Afshan Tabassum [aut], Khalid Ul Islam [aut], Imran Rashid [aut], Md Yeasin [aut] |
| Maintainer: | M. Iqbal Jeelani <jeelani.miqbal at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | ImNN results |
| Reference manual: | ImNN.pdf |
| Package source: | ImNN_0.1.0.tar.gz |
| Windows binaries: | r-devel: ImNN_0.1.0.zip, r-release: ImNN_0.1.0.zip, r-oldrel: ImNN_0.1.0.zip |
| macOS binaries: | r-release (arm64): ImNN_0.1.0.tgz, r-oldrel (arm64): ImNN_0.1.0.tgz, r-release (x86_64): ImNN_0.1.0.tgz, r-oldrel (x86_64): ImNN_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.