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Inception Petroleum Analysis

This repository shows the code used in the publication "Inception for Petroleum Analysis" for cetane number prediction.

The preprint is currently under peer evaluation at Fuel (Elsevier).

The IPA Deep CNN architecture

The IPA architecture

Getting started

Information : y is already normalized (mean 0 & std 1), the scaler is not given. Therefore, calculated metrics will be 15 times smaller than on the publication.

Python

Follow the next commands:

conda create -n inception-petroleum-analysis python=3.10

conda activate inception-petroleum-analysis 

conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0

pip install "tensorflow<2.11"

pip install -r requirements.txt

Matlab

Install MATLAB R2022b and Eigenvector PLS_Toolbox version 9.2.

Launching environment

Matlab

Open the script within the eponymous software.

Python

Activate the environment, then

IPA calibration

python -m scripts.IPA-calibration

DeepSpectra calibration

python -m scripts.DeepSpectra-calibration

About

Code of "Inception for Petroleum Analysis" for cetane number prediction. Submitted to Fuel (Elsevier) - Review in progress.

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