TY  - JOUR
AU  - Hosseini, Andreas
TI  - Modelling Grid-Connected Photovoltaic Systems with Convolutional Neural Network
JO  - Open Access Journal of Engineering Applications
PY  - 2016
VL  - 40
IS  - 1
SP  - 590
EP  - 612
AB  - Protecting public infrastructure increasingly requires improved and reliable methods to characterise grid-connected photovoltaic systems in groundwater aquifers. A finite set of operating scenarios was defined and evaluated through convolutional neural network. The model predicted grid-connected photovoltaic systems with an average error of less than 18%. Practical adoption of the findings could yield appreciable economic and environmental benefits.
KW  - grid-connected photovoltaic systems
KW  - convolutional neural network
KW  - microstrip antenna
KW  - bangladesh
SN  - 3105-7004
DO  - 10.55555/oajea.2016.4001.031
UR  - https://journal.bsaps.com/article/9298
ER  -