Construction of Power Marketing Inspection Model Based on Data Mining Technology

The quality of power marketing inspection is an important symbol to measure the level of power marketing management of power supply enterprises, and it is also a comprehensive reflection of the operating results and service quality of power supply enterprises. It is necessary to strengthen effective inspection and monitoring in the inspection work of electric power marketing. One of the goals of power enterprises is to determine and establish a good new mode and method of power marketing inspection management, improve the efficiency of power marketing inspection, and achieve the goal of efficient power marketing management. Aiming at the problem that the traditional method leads to the low implementation effect of related inspection work due to the large scale of power marketing data, this paper proposes research on the construction of power marketing inspection model based on data mining technology. The data mining method is used to analyze the power marketing data, and the minimum support and minimum confidence are taken as the criteria to determine the association relationship. The association relationship between the power marketing index parameters is calculated. According to the weight coefficient of each power marketing data item information in the abnormal power consumption behavior, a power marketing inspection model with the correlation as the core is constructed. After the data to be inspected is input into the model, the relationship between the output results and the mean value is analyzed to determine whether there is any abnormality. The test results show that the design model can effectively detect the abnormal power consumption behavior and has high reliability.