Evaluation of the k-nearest neighbor method for forecasting the influent characteristics of wastewater treatment plant

doi:10.1007/s11783-015-0825-7

Front. Environ. Sci. Eng.

2016, Vol. 10

Issue (2) : 299-310 https://doi.org/10.1007/s11783-015-0825-7

RESEARCH ARTICLE

Evaluation of the k-nearest neighbor method for forecasting the influent characteristics of wastewater treatment plant

Minsoo KIM¹,Yejin KIM²,Hyosoo KIM³,Wenhua PIAO¹,Changwon KIM^1,^*(

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1. Department of Civil and Environmental Engineering, Pusan National University, Busan 609-735, Republic of Korea
2. Department of Civil and Environmental Engineering, Catholic University of Pusan, Busan 609-757, Republic of Korea
3. EnvironSoft Co., Ltd. 511 Industry-University Co., Bld., Pusan National University, Busan 609-735, Republic of Korea

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Abstract

The k-nearest neighbor (k-NN) method was evaluated to predict the influent flow rate and four water qualities, namely chemical oxygen demand (COD), suspended solid (SS), total nitrogen (T-N) and total phosphorus (T-P) at a wastewater treatment plant (WWTP). The search range and approach for determining the number of nearest neighbors (NNs) under dry and wet weather conditions were initially optimized based on the root mean square error (RMSE). The optimum search range for considering data size was one year. The square root-based (SR) approach was superior to the distance factor-based (DF) approach in determining the appropriate number of NNs. However, the results for both approaches varied slightly depending on the water quality and the weather conditions. The influent flow rate was accurately predicted within one standard deviation of measured values. Influent water qualities were well predicted with the mean absolute percentage error (MAPE) under both wet and dry weather conditions. For the seven-day prediction, the difference in predictive accuracy was less than 5% in dry weather conditions and slightly worse in wet weather conditions. Overall, the k-NN method was verified to be useful for predicting WWTP influent characteristics.

Keywords influent wastewater prediction data-driven model k-nearest neighbor method (k-NN)

Corresponding Author(s): Changwon KIM

Online First Date: 11 December 2015 Issue Date: 01 February 2016

Cite this article:

Minsoo KIM,Yejin KIM,Hyosoo KIM, et al. Evaluation of the k-nearest neighbor method for forecasting the influent characteristics of wastewater treatment plant[J]. Front. Environ. Sci. Eng., 2016, 10(2): 299-310.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-015-0825-7
https://academic.hep.com.cn/fese/EN/Y2016/V10/I2/299

Tab.1 Statistical properties of influent wastewater flow rate and compositions for the N WWTP

Tab.2 RMSE results of the effects by the search range considering the number of NNs in the influent flow rate under the dry and wet weather conditions

Fig.1 Effects of the number of NNs on forecasting the flow rate analyzed using the RMSE based on the DF approach (◆, ●, ▲, █) and the SR approach (◇, ○, △, □) in dry (a) and wet (b) weather conditions

Fig.2 Results for predicting the influent flow rate by using the k-NN method in dry and wet weather conditions

Tab.3 Derivation of appropriate conditions for the search range and the number of NNs to predict influent water qualities (COD, SS, T-N, and T-P)

Fig.3 A comparison of predicted influent qualities (COD, SS, T-N, and T-P) with measured data in dry and wet weather conditions

Fig.4 An evaluation of the accuracy of long-term predictions of influent flow rates and water qualities based on the k-NN method

Fig.5 A comparison of box plots for the application of two approaches in dry and wet weather conditions

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