机器学习在生态环境大数据中的应用

Application of Machine Learning in Ecological Environment Big Data

近年来,生态环境大数据建设得到长足发展,积累了大量数据资源,但大多数情况只是对数据的简单展示,缺乏场景化的数据深度挖掘分析与关联影响分析,没有最大程度地发挥数据应用价值,在生态环境管理工作中的决策支撑效果不明显。机器学习是数据挖掘的重要技术之一,能让计算机具有人一样的学习能力,从海量的数据中找出有价值的信息,特别是对于复杂的数据集识别、分类、预测有着良好的效果。将结合生态环境工作实际,对机器学习在生态环境大数据中的应用过程进行阐述与分析,并针对当前存在的不足,提出相关建议。

In recent years,the construction of ecological and environmental big data has developed significantly and accumulated a large amount of data resources,but in most cases,it is only a simple display of data,lacking scenario-based deep data mining analysis and correlation impact analysis,which does not maximize the value of data application and is not effective in supporting decision-making in ecological and environmental management.Machine learning is one of the important techniques of data mining,which enables computers to have human-like learning ability to find out valuable information from massive data,especially for complex data set identification,classification and prediction with good effect.The author will explain and analyze the application process of machine learning in big data of ecological environment in combination with the actual work of ecological environment,and put forward relevant suggestions for the current shortcomings.