![]() The two-stage ABC-DWKNN Plus MLP-FF model achieved the Perceptron (MLP) algorithms are coupled with artificial-bee colony (ABC) and firefly (FF) Distance-weighted K-nearest-neighbor (DWKNN) and multi-layer Machine-learning-optimizer models to predict a wide range of oil flow rates (Qo) through Study, a dataset of 6292 data records with seven input variables relating to oil flow throughĤ0 pipelines plus processing facilities in southwestern Iran is evaluated with hybrid Simplified by using supervised machine learning techniques exploiting optimizers. Measurements through certain meters requires cumbersome calculations that can be Movements through pipelines and facilities. ![]() Flow measurement is an essential requirement for monitoring and controlling oil
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