Prediction of sulphide build-up in filled sewer pipes.

摘要: Millions of dollars are being spent worldwide on the repair and maintenance sewer networks wastewater treatment plants. The production emission hydrogen sulphide has been identified as a major cause corrosion odour problems in networks. Accurate prediction build-up system helps engineers asset managers to appropriately formulate strategies for optimal management reliability analysis. This paper presents novel methodology model predict steady state condition filled pipes. proposed is developed using data-driven technique called evolutionary polynomial regression (EPR) it involves most effective parameters problem. EPR hybrid technique, combining genetic algorithm least square. It shown that can provide better compared with conventional models.