Objectives of this study were to identify the hotspot for displacement of the on-line water quality sensors, in order to detect illicit discharge of untreated wastewater. A total of twenty-six water quality parameters were measured in sewer networks of the industrial complex located in Daejeon city as a test-bed site of this study. For the water qualities measured on a daily basis by 2-hour interval, the self-organizing maps(SOMs), one of the artificial neural networks(ANNs), were applied to classify the catchments to the clusters in accordance with patterns of water qualities discharged, and to determine the hotspot for priority sensor allocation in the study. The results revealed that the catchments were classified into four clusters in terms of extent of water qualities, in which the grouping were validated by the Euclidean distance and Davies-Bouldin index. Of the on-line sensors, total organic carbon(TOC) sensor, selected to be suitable for organic pollutants monitoring, would be effective to be allocated in D and a part of E catchments. Pb sensor, of heavy metals, would be suitable to be displaced in A and a part of B catchments.

This study aimed to examine the applicability of Self-organizing Map(SOM) method for synoptic climatology studies over the Republic of Korea through a case study on classification of winter atmospheric pressure patterns. When SOM was conducted using spatial range 10~70°N, 80~180°E, 4×3 map size, linear initialization, batch training algorithm and neighborhood function ep(Epanechnikov function) for the case study, classified atmospheric pressure patterns showed the best result. The classified atmospheric patterns were similar to surface weather charts of Korea Meteorological Administration(KMA). Also all input vectors were classified into one atmospheric pressure pattern(node) so it is possible to analyse time series and characteristics of climatic elements according to atmospheric pressure patterns. Therefore, SOM method might be appropriate for the studies on synoptic climatology over the Republic of Korea.