Enhanced Ramer-Douglas-Peucker Algorithm for Efficient 2D Line Simplification

The Ramer-Douglas-Peucker (RDP) algorithm is a potent method frequently used to simplify lines and curves while maintaining their essential properties. This recursive method is invaluable in several disciplines, including geographic information systems, mapping, and data analysis. It is excellent at condensing important information and removing unimportant details. The time series visualization and data reduction is one of its major applications. Time series datasets can have many data points, which can make complex processing and storage limitations. Although the traditional RDP approach works well for smaller datasets, it could have trouble keeping up with the needs of bigger ones. Researchers have improved the RDP approach by utilizing parallel computing and adding dynamic epsilon values to overcome this issue. With the help of the dynamic epsilon feature, the algorithm is more adaptable because it may change the distance threshold following the peculiarities of the dataset. This improved version, called Enhanced RDP (ERDP), has shown remarkably improved performance. During testing, ERDP significantly decreased processing time and could exclude up to 96.88% of data points without materially impairing the results' accuracy. In addition, statistical testing with a Wilcoxon-Signed Rank Test showed a clear distinction between the traditional RDP approach and ERDP's computational efficiency, with the latter regularly surpassing the former. This improvement demonstrates how the technique can be modified to meet the changing demands of data processing. It is a priceless tool for streamlining complicated datasets, especially in the context of time series research.