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Air-cooled Data Centers absorb heat in central room air conditioners or air handlers and most commonly reject the heat through cooling towers to ambient air. The energy efficiency of the overall cooling system is determined by the energy efficiency of its components, its thermodynamic design and layout, and the protocol for its control, operation and its operational set points. The current work is...
The critical environmental parameters affecting plant growth in the greenhouse are temperature, relative humidity, carbon dioxide, nutrition, availability of water, and the growing media. From these factors, temperature is of primary importance to most growers because it is responsible for determining the reaction rates of various metabolic processes involved in plant growth, and also regulating temperature...
The γ' precipitate size of IN738LC is predicted using a Levenberg-Marquard backpropagation neural network in matlab toolbox. A cast polycrystalline Ni based super alloy IN738LC (a gas turbine material) is considered and the γ' precipitate size is described as a function of 5 variables (solutionizing temperature, solutionizing duration, ageing temperature, ageing duration, and cooling method (furnace...
A slab surface temperature prediction model of the continuous casting based on the variable-metric chaos optimization neural network is presented to solve the problem which the slab surface temperatures can not be measured continuously directly for plentiful inhalator, water film and ferric oxide on the slab surface in the secondary cooling zone. The model is shown to fit the actual data precisely...
As a heat load prediction method in district cooling and heating systems, the efficiency of a layered neural network has been shown, but there is a drawback that its prediction becomes less accurate in periods when the heat load is non-stationary. In this paper, we propose a new heat load prediction method superior to existing methods by using a recurrent neural network to deal with the dynamic variation...
Because there is a couple between the heating layer and the cooling one of the boiler in a PCT-II process control system, tuning the PID parameters is quite difficult and takes a long time to control the temperatures of the boiler besides some steady-state error. In this paper a decoupling control method based on the neural network is presented. The algorithm adopts tandem structure with the PID controller...
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