| import pickle | |
| import numpy as np | |
| import gradio as gr | |
| import sklearn | |
| import pandas as pd | |
| from sklearn.model_selection import train_test_split | |
| from sklearn.ensemble import ExtraTreesRegressor | |
| filename = 'Dataset_RCS_3.csv' | |
| names0 = ['JET', "Suelo",'SPT', 'WtoC', 'Presion', 'Velocidad','RCS'] | |
| dataset=pd.read_csv(filename, names=names0) | |
| y = dataset['RCS'] | |
| X = dataset.drop('RCS', axis=1) | |
| validation_size = 0.20 | |
| seed = 10 | |
| X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=validation_size, random_state=seed) | |
| modelodef=ExtraTreesRegressor( | |
| n_estimators=1000, | |
| max_depth=9, | |
| min_samples_leaf=1, | |
| random_state=seed) | |
| modelodef.fit(X_train, y_train) | |
| pickle.dump(modelodef, open("modelodef.pkl", "wb")) | |
| def RCS(JET, Suelo,SPT, WtoC, Presion, Velocidad): | |
| modelodef = pickle.load(open("modelodef.pkl", "rb")) | |
| prediction0 = modelodef.predict([[JET, Suelo,SPT, WtoC, Presion, Velocidad]]) | |
| prediction = np.round(prediction0,2) | |
| return prediction | |
| title = "ASSESSMENT OF UNIAXIAL COMPRESSIVE STRENGTH OF JET GROUTING" | |
| description = "This app corresponds to the research paper: Assessment of compressive strength of jet grouting by machine learning" | |
| article = """ | |
| Notes: | |
| - Click submit/enviar button to obtain the UCS prediction | |
| - Click clear/limpiar button to refresh text | |
| - Please note the application ranges of the variables in the above-referenced paper (https://doi.org/10.1016/j.jrmge.2023.03.008). Outside these ranges, the predictions may not be reliable | |
| - As a decimal separator you can use either a point or a comma | |
| """ | |
| app = gr.Interface( | |
| RCS, | |
| inputs=[ | |
| gr.Radio(['1', '2', '3'], label="Jet system. 1: Single. 2: Double. 3: Triple",value="1"), | |
| gr.Radio(['1', '2', '3', '4'], label="Soil type. 1: Coarse without fines. 2: Coarse with fines. 3: Fine. 4: Organic",value="1"), | |
| gr.Number(value=1, label="Nspt"), | |
| gr.Number(value=1, label="W/C"), | |
| gr.Number(value=1, label="Grout pressure (bar)"), | |
| gr.Number(value=1, label="Rotation speed (rpm)"), | |
| ], | |
| outputs=[gr.Text(label="UCS (MPa)")], | |
| title=title, | |
| description=description, | |
| article = article, | |
| theme="dark-seafoam" | |
| ) | |
| app.launch() |