Aplicación de algoritmos de Machine Learning para la segmentación del consumo de agua potable. Caso de estudio en Catamayo, Ecuador

• Published in: 2023 18th Iberian Conference on Information Systems and Technologies (CISTI) pp. 1 - 6
• Main Authors: Olmedo, Amable Tinizaray, Castro, Jose Raul, Reategui, Ruth, Castillo, Tuesman
• Format: Conference Proceeding
• Language: English
• Published: ITMA 20-06-2023
• Subjects: Behavioral sciences; Clustering algorithms; Companies; Data mining; DBSCAN; drinking water consumption; k-Means; Machine learning; Machine learning algorithms; Urban areas
• ISSN: 2166-0727
• DOI: 10.23919/CISTI58278.2023.10211900

The present investigation aims to segment the customers of the drinking water consumption of the water company in the city of Catamayo. The dataset of historical readings of residential category customers' consumption from January to November of 2019 was used. The objective of this investigation is to use data mining (DM) and machine learning (ML) to segment the customers based on their monthly water consumption. The K-Means and DBSCAN algorithms were used as techniques to divide the data into clusters of equal similarity. There are customers who do not belong to the found clusters. Identifying these customers is of great importance for the different technical departments of the company to search for the causes of their different consumption behavior..