Data-mining approach to investigate sedimentation features in combined sewer overflows | Journal of Hydroinformatics | IWA Publishing

Skip to Main Content

Data-mining approach to investigate sedimentation features in combined sewer overflows

Journal of Hydroinformatics (2012) 14 (3): 613-627.

This article has been cited by the following articles in journals that are participating in CrossRef Cited-by Linking.

Prediction of water quality parameters using evolutionary computing-based formulations

M. Najafzadeh
A. Ghaemi
S. Emamgholizadeh

International Journal of Environmental Science and Technology (2019) 16 (10): 6377.

Simple flowmeter device for LID systems: From laboratory procedure to full-scale implementation

Patrizia Piro
Marco Carbone
Francesco Morimanno
Stefania Anna Palermo

Flow Measurement and Instrumentation (2019) 65: 240.

Optimized expressions to evaluate the flow discharge in main channels and floodplains using evolutionary computing and model classification

Abdolreza Zahiri
Mohammad Najafzadeh

International Journal of River Basin Management (2018) 16 (1): 123.

Comparison of mathematical methods for the evaluation of wastewater settleability by settling column tests

Marco Carbone
Nadia Penna
Patrizia Piro

Environmental Technology (2017) 38 (6): 671.

Comparison between CFD and Surface Overflow Rate Models to Predict Particulate Matter Separation in Unit Operations for Combined Sewer Overflows

M. Carbone
G. Garofalo
P. Piro

Journal of Environmental Engineering (2014) 140 (12): 04014041.