Next generation prediction model for daily solar radiation on horizontal surface using a hybrid neural network and simulated annealing method

Energy Conversion and Management

Volumn 153, Issue , 2017, Pages 671-682

  Mousavi, Seyyed Mohammad ^a   Mostafavi, Elham S ^b,c   Jiao, Pengcheng ^d  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

^c MONTANA STATE UNIVERSITY   (United States)

^d UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Artificial intelligence; Artificial neural network; Daily solar radiation; Meteorological parameters; Simulated annealing

Indexed keywords

ARTIFICIAL INTELLIGENCE; COUPLINGS; FORECASTING; LEARNING SYSTEMS; NEURAL NETWORKS; NEXT GENERATION NETWORKS; RADIATION; SENSITIVITY ANALYSIS; SIMULATED ANNEALING; SUPPORT VECTOR MACHINES;

CALCULATION PROCEDURE; DAILY SOLAR RADIATIONS; GENERATION PREDICTIONS; HYBRID NEURAL NETWORKS; MACHINE LEARNING MODELS; METEOROLOGICAL PARAMETERS; SIMULATED ANNEALING METHOD; SOLAR RADIATION MODEL;

SOLAR RADIATION;

EID: 85033552052     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2017.09.040     Document Type: Article

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