Data Science (AI)
Recently, data-analysis technologies such as machine learning and image analysis have made remarkable progress and are being used in a variety of fields. At ENEOS, we are also developing and applying the latest technologies in the field of data science, such as machine learning (including deep learning, unsupervised learning, and reinforcement learning) and mathematical optimization. We are also developing automatic-plant-operation AI and anomaly-detection systems, improving the efficiency of ordering operations, and optimizing ship allocation and land delivery. We are also developing AI models for predicting solar-power-generation and wind-power-generation for the overall optimization of future energy supply, mobility, and life support.
We will continue to develop technologies that can contribute to the creation of a low-carbon society through the integration of AI technologies.
Examples of application to various businesses
- Solar-power-generation forecasting
- Hybrid forecasting method that combines physical models and machine learning to achieve higher forecasting accuracy than conventional methods.
- Ship-allocation optimization
- Building of a high-speed optimization model for a large-scale and complex problem of allocating crude-oil ships.
- Automatic plant operation
- Successful automated operation of a petrochemical plant using AI technology for the first time in Japan.
Solar-power-generation forecasting
Ship-allocation optimization
Automatic plant operation
