Machine Learning-Driven Condition Monitoring and Performance Optimization of Thrust Bearings: State-Of-The-Art Review, Challenges, And Future Perspectives

Abstract

Data visualization has become an essential component of modern data analytics, enabling users to identify patterns, trends, correlations, and anomalies within large datasets. Scatter plots are among the most effective visualization techniques for representing relationships between numerical variables. This research presents the design and development of interactive 2D and 3D scatter plot visualizations using D3.js and Three.js technologies. D3.js is employed to construct dynamic two-dimensional scatter plots with interactive features such as zooming, filtering, and tooltips, while Three.js is utilized to render three-dimensional scatter plots using WebGL for enhanced spatial representation. The proposed approach demonstrates how multidimensional datasets can be effectively visualized and explored through modern web-based technologies. Experimental analysis indicates that D3.js offers superior simplicity and responsiveness for two-dimensional data representation, whereas Three.js provides greater depth perception and multidimensional exploration capabilities. The integration of these technologies creates a scalable framework for scientific, business, and analytical applications.