An Auxiliary Decision-Making System for Electric Power Intelligent Customer Service Based on Hadoop

• Published in: Scientific programming Vol. 2022; pp. 1 - 11
• Main Authors: Wu, Shisong, Dong, Zhaojie
• Format: Journal Article
• Language: English
• Published: New York Hindawi 19.01.2022; John Wiley & Sons, Inc
• Subjects: Algorithms; Big Data; Customer services; Data mining; Data processing; Decision analysis; Decision making; Efficiency; Electricity distribution; Fault tolerance; Occupancy; Power; Quality of service; Response time; System effectiveness; Tables (data)
• ISSN: 1058-9244; 1875-919X; 1875-919X
• DOI: 10.1155/2022/5165718

Aiming at the problems of low security, high occupancy rate, and long response time in the current power intelligent customer service assistant decision-making system, a power intelligent customer service assistant decision-making system based on the Hadoop big data framework is designed. By analyzing the Hadoop big data framework, according to the characteristics and core elements of the HDFS distributed file system, the MapReduce programming model, and the data mining algorithm, the basic process of power intelligent customer service assistance decision-making is established. We analyze the overall and functional requirements of the system, design the overall architecture and application architecture of the system, design the E-R diagram and table structure of the database according to the database design principle, and realize the design of power intelligent customer service auxiliary decision-making system based on Hadoop big data framework. The test results show that the proposed method has high system security and low system occupancy and can effectively shorten the system response time. The systems run more flawlessly as compared to the existing methods and give impressing results with lesser CPU utilization. The response time was recorded to be about 12.2 seconds for 1000 power intelligent customer servers, which is much lower than that of the competitors.