Design of Data Classification and Classification Management System for Big Data of Hydropower Enterprises Based on Data Standards

Wei Luo,Ziqi Zhou,Jian Xu,Omar Cheikhrouhou

doi:10.1155/2022/8103897

Abstract

The advent of the era of big data has had a great impact on traditional management methods, and companies have also begun to make changes. The management approach has changed from initially focusing on business development to now focusing on user experience and putting people first. The data standard classification management system is a system for management and analysis based on the database. Therefore, this article is based on data standards, taking hydropower companies as an example, to design and research the data classification management system to promote the operation and safety of hydropower companies. This article mainly uses the experimental method, data collection method, and algorithm analysis method to thoroughly understand and explore the content of this article. The experimental results show that the testability of this article can basically reach the general level, and the delay time of the system does not exceed 10 seconds, which can be applied to the company.

Highlights

As we all know, in modern life, hydropower is a must-have product for every household
(1) Hoeffding tree algorithm is a data flow classification method based on the decision tree. It is the basis of incremental learning of data flow classification. e concept adaptive fast decision tree adopts the method based on sliding window to maintain a fixed sliding window in the process of classifier learning
According to the conventional data classification algorithm combined with hydropower users, the hydropower load data is processed, and the results are obtained to classify users in a conventional manner

Summary

Introduction

In modern life, hydropower is a must-have product for every household. E data standard is the basis for classifying data; that is, it is estimated to be unknown based on the known and converted into a specified format In this way, some items with the same characteristics can be expressed to reflect the basic situation and management requirements of the enterprise [3]. E data classification index is formulated according to the actual situation and needs of the enterprise It is classified by a classification system according to data standards and divides users of different types, different age groups, and different purposes into multiple subcategories. Data classification algorithms based on access frequency mainly include a fixed threshold method [6, 7]. (1) Hoeffding tree algorithm is a data flow classification method based on the decision tree It is the basis of incremental learning of data flow classification. Extract the user’s load data within a certain period of time and make the user’s average load change curve according to different seasons and periods

Results and analysis

System Detailed Design

System Implementation

Experimental Results