The multivariable inverse artificial neural network combined with GA and PSO to improve the performance of solar parabolic trough collector
This work focused on presenting a multivariate inverse artificial neural network (ANNim) by
develo** two functions coupled to metaheuristic algorithms to increase a parabolic trough …
develo** two functions coupled to metaheuristic algorithms to increase a parabolic trough …
[HTML][HTML] Inverse artificial neural network control design for a double tube heat exchanger
This work focused on a new developed and experimentally tested non-linear control
approach to control a double tube heat exchanger's output cold water temperature. The …
approach to control a double tube heat exchanger's output cold water temperature. The …
Implementation of Deep Neural Networks for performance prediction and optimization of a porous volumetric solar receiver considering mechanical safety
The volumetric solar receiver is a major component of concentrating solar thermal systems.
Proper selection of design and operating parameters is necessary to obtain the best receiver …
Proper selection of design and operating parameters is necessary to obtain the best receiver …
Improvement of the classical artificial neural network simulation model of the parabolic trough solar collector outlet temperature and thermal efficiency using the …
The outlet temperature and the thermal efficiency predictions of the PTSC are essential
parameters in the solar thermal power system. Therefore, it is crucial to have a prediction …
parameters in the solar thermal power system. Therefore, it is crucial to have a prediction …
Artificial neural network modeling and sensitivity analysis for soiling effects on photovoltaic panels in Morocco
In the present work, an Artificial Neural Network (ANN) methodology for studying and
modeling the soiling effect on solar photovoltaic (PV) glass is presented. To perform the …
modeling the soiling effect on solar photovoltaic (PV) glass is presented. To perform the …
Dimensions and analysis of uncertainty in industrial modeling process
Robust and e cient modeling of industrial processes is vital in realizing stable and
economical process design, operation, and control. However, inherent uncertainty of the …
economical process design, operation, and control. However, inherent uncertainty of the …
Temperature estimation for photovoltaic array using an adaptive neuro fuzzy inference system
Module temperature is an important parameter of photovoltaic energy systems since their
performance is affected by its variation. Several cooling controllers require a precise …
performance is affected by its variation. Several cooling controllers require a precise …
[PDF][PDF] Analysis of transfer functions and normalizations in an ANN model that predicts the transport of energy in a parabolic trough solar collector
abstract Artificial neural network model was developed to obtain the fluid outlet temperature
of the parabolic trough collector (PTC) with a grooved absorber tube. To improve the …
of the parabolic trough collector (PTC) with a grooved absorber tube. To improve the …
Applications of artificial neural networks in concentrating solar power systems
Concentrating solar power (CSP) systems are one of the growing solutions to increased
demands for renewable electricity generation. This growth implies the global capacity of …
demands for renewable electricity generation. This growth implies the global capacity of …
Multivariate inverse artificial neural network to analyze and improve the mass transfer of ammonia in a Plate Heat Exchanger-Type Absorber with NH3/H2O for solar …
This work presents a numerical approach to compute optimal operating conditions that
maximize the absorption flux into a heat exchanger designed for absorption refrigeration …
maximize the absorption flux into a heat exchanger designed for absorption refrigeration …