Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Morphological and molecular studies of Sphaerospermopsis torques-reginae (Cyanobacteria, Nostocales) from South American water blooms

Sphaerospermopsis torques-reginae (Komarek) Werner, Laughinghouse IV, Fiore & Sant'Anna comb. nov. was originally described as Anabaena torques-reginae Komarek from planktonic populations of Cuban eutrophic environments, characterized by twisted trichomes with spherical akinetes adjacent to the heterocytes. Recently, using molecular analyses, all planktonic Anabaena Bory ex Bornet & Flahault morphospecies were transferred into the genus Dolichospermum (Ralfs ex Bornet & Flahault) Wacklin el al., including Dolichospermum torques-reginae (Komarek) Wacklin et al. However, by a polyphasic characterization of strains of Anabaena reniformis Lemmermann and Aphanizomenon aphanizomenoides (Forti) Horecka & Komarek (=Anabaena aphanizomenoides Forti), these planktonic species were reclassified into Sphaerospermopsis Zapomelova et al. Our study's main objective was to characterize morphologically and molecularly cyanobacterial populations identified as Dolichospermum torques-reginae, observed in different aquatic ecosystems in South America. The 16S rRNA gene of two Dolichospermum torques-reginae strains (ITEP-024 and ITEP-026) was sequenced and phylogenetically analyzed for the first time. The morphological and phylogenetic analyses demonstrated the affiliation of the studied populations with the genus Sphaerospermopsis and, consequently, were denominated as Sphaerospermopsis torques-reginae. Furthermore, geographic distribution, ecology, and toxicity of the species are discussed. It was observed in different aquatic environments, natural and artificial, tropical and subtropical in Brazil, temperate in Argentina, and tropical in Colombia, suggesting a wide distribution in South America. It normally occurred in dense freshwater blooms, although it was also found in water with low salinity. Sphaerospermopsis torques-reginae toxic blooms have been reported in tropical water bodies in northeastern Brazil.