Fuel Efficiency Prediction Using TensorFlow in Python: A Machine Learning Approach

Fuel efficiency estimation is a central issue in the automotive sector. With the increasing demand for sustainable and affordable transportation, the application of machine learning has been recognized as a possible solution to estimate fuel consumption with high accuracy. This paper introduces an estimation model from the TensorFlow and Keras libraries coded in Python. With exploratory data analysis, combined with deep learning techniques, the model is able to accurately forecast vehicle parameters such as weight, engine size, and cylinder number to fuel consumption in miles per gallon (mpg). The experimental outcome indicates the potential of the model to assist the automotive sector in improving fuel efficiency and enhancing sustainability.

Keywords

Fuel efficiency, Machine Learning, TensorFlow, Keras, Deep Learning, Python, Predictive Modeling, Automotive

Fuel efficiency Machine Learning TensorFlow Keras Deep Learning Python Predictive Modeling Automotive