Abstract: Fluid stream management systems and methods are described. An exemplar fluid stream management system includes a neural network connected to a cascading treatment processor. The neural network calculates an initial distant flow condition attribute value for a distant fluid treatment facility. The cascading treatment processor using hydrological information and the initial distant flow condition attribute value computes a predicted modified contribution value for the distant fluid treatment facility. The cascading treatment processor instructs multiple fluid flow controllers, each of which controls the operation of a flow-directing device such that a sum of the predicted modified total load value and a real time total load value of the distant fluid treatment facility is minimized. The real time total load value of the distant fluid treatment facility is based upon real time measurements obtained from one or more of the distant fluid treatment facility sensors.

Abstract: Fluid stream management systems and methods relating thereto are described. The fluid management system includes a neural network, which comprises: (i) an input layer that is communicatively coupled to one or more fluid facility sensors and/or one or more pre-processing flow sensors such that one or more of the flow condition attribute values are received the neural network; (ii) one or more intermediate layers, which are configured to constrain one or more of the flow condition attribute values to arrive at modified flow condition attribute values; (iii) an output layer, which transmits, one or more modified flow condition attribute values to a downstream control device. This control device and other computation devices perform certain calculations that ultimately inform a flow controller, which in turn, instructs a flow-directing device regarding management of fluid streams.

Abstract: Fluid stream management systems and methods are described. An exemplar fluid stream management system includes a neural network connected to a cascading treatment processor. The neural network calculates an initial distant flow condition attribute value for a distant fluid treatment facility. The cascading treatment processor using hydrological information and the initial distant flow condition attribute value computes a predicted modified contribution value for the distant fluid treatment facility. The cascading treatment processor instructs multiple fluid flow controllers, each of which controls the operation of a flow-directing device such that a sum of the predicted modified total load value and a real time total load value of the distant fluid treatment facility is minimized. The real time total load value of the distant fluid treatment facility is based upon real time measurements obtained from one or more of the distant fluid treatment facility sensors.