Adoption of K-means clustering algorithm in smart city security analysis and mythical experience analysis of urban image.

ABSTRACT:

Objective

An information security evaluation model based on the K-Means Clustering (KMC) +  Decision Tree (DT) algorithm is constructed, aiming to assess its value in evaluating smart city (SC) security. Additionally, the impact of SCs on individuals' mythical experiences is investigated.

Methods

An information security analysis model based on the combination of KMC and DT algorithms is established. A total of 38 SCs are selected as the research objects for practical analysis. The practical feasibility of the model is assessed using the receiver operating characteristic (ROC) curve, and its performance is compared with that of the Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM) classification m

SUBMITTER: Han H 

PROVIDER: S-EPMC11892831 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature