Wastewater pipe condition rating model using K- Nearest Neighbors

Risk-based assessment in pipe conditions mainly focuses on prioritizing the most critical assets by evaluating risk of failure. This paper's goal is to classify a comprehensive rating model which obtained based series pipe, external, and hydraulic characteristics that are identified for proposed methodology. The traditional manual method assessing sewage structural takes long time. By building an automated process using K-Nearest Neighbors (K-NN), this study presents effective technique automate identification defect repair data. First, we performed Shapiro Wilks Test 1240 data from Dept. Engineering & Environmental Services, Shreveport, Louisiana Phase 3 with 12 variables determine if factors could be incorporated into final rating. We then developed statistically significant Shapiro-Wilks Test. classification allows recognizing worst condition wastewater pipes need replaced immediately. built according industry-accepted used guidelines estimate overall condition. Finally, validation purposes, applied small portion US collection system Louisiana.