Management of offshore oil pollution and logistics transportation based on decision tree

Decision tree algorithm is one of the most widely used inductive thinking algorithms in data mining. Its construction does not require any domain knowledge or parameter settings, and it is widely suitable for exploratory knowledge discovery. The decision tree algorithm has clear structure, fast calculation speed, high precision, and higher flexibility and reliability. It can be used to process multidimensional data, and the acquired knowledge is intuitive and easy to understand. Decision tree algorithms are now widely used in medicine, manufacturing, financial analysis, astronomy, molecular biology, and remote sensing image classification. For example, in the field of marine oil pollution, the influence of bacterial flora has been studied through experiments with simulated bar graphs and bio-enhanced seawater oil pollution remediation, environmental parameters, and microbial metabolism have been found to affect the oil diffusion rate at the same time. In the early days, due to the high concentration of microorganisms, the established bacterial colonies that degraded petroleum had a certain degrading ability. As the abundance of microbial communities increases, the benefits of TCOB-4 and TCOB-5 gradually decrease. The oil of TCOB-5 is highly degradable, and may continue to function during the test period, and is compatible with other oil-degrading bacteria. The dominant position. With the rapid development of third-party logistics, logistics profits, the third source of profits, have become a black hole in the entire supply chain. If transportation costs can be reduced, the efficiency of the logistics system can be improved and profits can be maximized. Therefore, studying the decisions of third-party logistics transportation providers has undoubtedly become the top priority of ensuring fast transportation, reducing transportation costs, and conducting effective logistics management research. © 2021, Saudi Society for Geosciences.