Flood Pattern Detection Using Sliding Window Technique

Abstract

Patterns could be discovered from historical data and can be used to recommend decisions suitable for a typical situation in the past. In this study, the sliding window technique was used to discover flood patterns that relate hydrological data consisting of river water levels and rainfall measurements. Unique flood occurrence patterns were obtained at each location. Based on the discovered flood occurrence patterns, mathematical flood prediction models were formulated by employing the regression technique. Experimental results showed that the mathematical flood prediction models were able to produce good prediction on the flood occurrences. Results from this study proved that sliding window technique was able to detect patterns from temporal data. It is also considered a sound approach to adopt in predicting the flood occurrence patterns as it requires no prior knowledge as compared to other approaches when dealing with temporal data.