Abstract
In this paper, we first consider the phenomenon of exponential growth of existing equipment data in substation, introduce the cloud computing operation mode, and build a more scalable MapReduce processing system based on Hadoop platform. Cloud computing is completed by using decision tree C4.5 algorithm, and the algorithm is used to optimize the parallel computing mode on the Hadoop platform as the core of the same data processing. Based on this point, this paper considers the impact of the ecological restoration effect of L County in the northern mountainous area of T city on the environment of the study area, analyzes the climate and hydrological conditions of the study area, provides the basic data of the mountain ecological environment of Y mountain area for the study of mountain landscape planning, and facilitates the practice. The combination of landscape planning, ecological restoration, and environmental reconstruction system theory provides a theoretical and practical basis for ecological planning in the central mountainous area of T city. Finally, based on MOOC components and software architecture, this paper constructs a college English remote system. After comprehensive testing in many aspects, this paper reduces the cost of software development in this field, which not only improves the reliability of the system, but also shortens the development cycle, speeds up the maintenance speed of the system, and increases the scale of the system. About the system testing, this paper tests the function, performance, feasibility, integrity, and security of the system through the network testing method and cookie method. Based on the basic C4.5 decision-making algorithm and college English remote system, this paper studies the impact of mountain ecological environment restoration, provides ideas for promoting the development of the system, and provides reference for the reform and practice methods and processes in other courses.
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