Subsequently, the Extreme Gradient Boosting (XGBoost) algorithm, machine learning algorithm, is employed to classify and identify working states of the sucker rod pumps. At last, this paper uses the dataset collected from the oil field to corroborate the proposed method. The experimental results ...
Auto_TS Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows. cesium Open-Source Platform for Time Series Inference. darts Time Series Made Easy in Python. A python libra...
Shapley Additive Explanations (SHAP) were calculated for the top 10 extracted features from the Extreme Gradient Boosting (XGBoost) model to evaluate the amount and contribution direction categorized by teleworking rates (mean): low: <0.2 (more than 4 days/week in office), middle: 0.2 to <0.6...
The recursive feature elimination (RFE) algorithm is applied to adaptively identify the most representative features from cutting forces and torque signals. The XGBoost model is utilized to establish the tool wear prediction model, with ISSA optimizing its hyperparameters. The experimental results ...
Furthermore, the novel sixteen features are extracted in time and frequency domains with the analysis of the working mechanism of the sucker rod pump. Subsequently, the Extreme Gradient Boosting (XGBoost) algorithm, machine learning algorithm, is employed to classify and identify working states of ...
The three main parameters of n_estimators, learning_rate, and max_depth in XGBoost are optimized through WOA, which solves the problem of difficult parameter adjustment due to the large number of parameters in the XGBoost algorithm and improves the prediction effect of the XGBoost algorithm. "...
📦 Packages Python Libraries for working with dates and times. astralPython calculations for the position of the sun and moon. Arrow- A Python library that offers a sensible and human-friendly approach to creating, manipulating, formatting and converting dates, times and timestamps. ...
Types of such methods that can be applied to the the considered project include random forest (RF) and XGBoost. The random forest (RF) is based on the use of an ensemble of decision trees [35]. XGBoost is a gradient boosting algorithm proposed by T. Chen [36], which is also an ...