The atmospheric model of neural networks based on the improved Levenberg-Marquardt algorithm
نویسندگان
چکیده
Abstract Traditional atmospheric models are based on the analysis and fitting of various factors influencing space atmosphere density. Neural network do not specifically analyze polynomials each factor in model, but use large data sets for construction. Two traditional model algorithms analyzed, main affecting identified, an neural networks containing is proposed. According to simulation error, Levenberg-Marquardt algorithm used iteratively realize rapid weight correction, optimal obtained. The simulated calculated with networks, its average error rate lower than that such as DTM2013 MSIS00 model. At same time, calculation complexity significantly simplified
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*This research was carried out as part of NWO research project 611-304-019, 'Address: Free University, Department of Economics and Econometrics, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands. E-mail: [email protected].
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ژورنال
عنوان ژورنال: Baltic Astronomy
سال: 2021
ISSN: ['2543-6376']
DOI: https://doi.org/10.1515/astro-2021-0003