-
-
Available Formats
- Options
- Availability
- Priced From ( in USD )
-
Available Formats
-
- Immediate download
- $16.00
- Add to Cart
Customers Who Bought This Also Bought
-
4581 -- Experimental Evaluation of CO2 -Based Demand-Cont...
Priced From $16.00 -
4592 (RP-623) -- Water Solubility and Clathrate Hydrates ...
Priced From $16.00 -
4584 -- Methods for the Quantification of Driving Rain on...
Priced From $16.00 -
4573 -- Chilled Ceilings in Parallel with Dedicated Outdo...
Priced From $16.00
About This Item
Full Description
This study investigates task-blind and task-specific training methods to determine appropriate radial basis functionbased neural network architectures. These neural nets identify system behavior of air-cooled chiller condensers by grouping dominant features (clustering) of measured chiller performance data. Task-specific clustering proved superior but more computationally demanding than task-blind methods in learning a difficult task of fan operation for an air-cooled chiller. Seven measured variables were selected as relevant for the operation of two variable-speed and multiple fixed-speed condenser fans. All neural network architectures investigated successfully learned the functional seven-input/four-output mapping. Process control logic post-processes the noisy neural network control signal and evaluates operational and temporal constraints. The neurocontroller trained on the measured data set exhibits roughly similar performance compared to manufacturer-provided control, while offering reduced development time and efforts.
Units: Dual