基于数据挖掘技术的智能仪器数据推荐算法  

Intelligent Instrument Data Recommendation Algorithmbased on Data Mining Technology

作　　者：王彬彬 WANG Binbin(Continuing Education College,Fuyang Preschool Teachers College,Fuyang 236015,China)

机构地区：[1]阜阳幼儿师范高等专科学校继续教育学院,安徽阜阳236015

出　　处：《成都工业学院学报》2024年第2期41-46,共6页Journal of Chengdu Technological University

基　　金：阜阳幼儿师范高等专科学校重点科研项目(ZK20210002)。

摘　　要：单机、手工管理监测数据效率低,数据的实时性和准确性不高。为了有效地对海洋生态环境的优劣进行评价,以海洋环境的数据推荐为研究对象,对智能仪器数据推荐系统进行设计。该系统主要包括数据应用系统、数据处理系统、通信系统、数据采集系统和数据库。通过卫星遥感采集海洋相关信息,采用K均值(K-means)和先验(Apriori)算法获取参数之间的关系,利用决策树算法对海洋生态环境进行有效评价。采用模糊C均值聚类算法对海洋出现赤潮进行分析、预测。为了验证系统有效性,对系统进行海洋生态环境分析试验和赤潮预测试验。试验结果表明,系统可以有效分析海洋生态环境,并对赤潮进行较为准确的预测。The monitoring data efficiency of single machine and manual management is low,and the real-time and accuracy of data are not high.The data recommendation of marine environment was taken as the research object and the intelligent instrument data recommendation system was designed.The system was constituted of data application system,data processing system,communication system,data acquisition system and database.Marine related information was collected by satellite remote sensing,the relation ship between parameters was obtained by K-means algorithm and Apriori algorithm,and the decision tree algorithm was used to evaluate the marine ecological environment effectively.Then the fuzzy C-means clustering algorithm was used to analyze and predict the occurrence of red tide in the ocean.To verify the effectiveness of the system,the analysis test for marine ecological environment and red tide prediction test were carried out.The test results show that the system could effectively analyze the marine ecological environment and predict the red tide more accurately.

关 键 词：数据挖掘技术 智能仪器数据推荐算法 K-MEANS算法 APRIORI算法 模糊C均值聚类算法 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]