Kniha Spatially Explicit Hyperparameter Optimization for Neural Networks Minrui Zheng

Spatially Explicit Hyperparameter Optimization for Neural Networks

Autor: Minrui Zheng
Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: Springer, Berlin
Dostupnost: Skladem u dodavatele
Odesíláme za 5-8 dnů
3 198
Neural networks as the commonly used machine learning algorithms, such as artificial neural networks...

Informace o knize

Autor
Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2022
Stránek
108
EAN
9789811654015
Enbook ID
41605299
Vydavatel
Hmotnost
207
Rozměry
155 x 235 x 8

Kompletní popis

Neural networks as the commonly used machine learning algorithms, such as artificial neural networks (ANNs) and convolutional neural networks (CNNs), have been extensively used in the GIScience domain to explore the nonlinear and complex geographic phenomena. However, there are a few studies that investigate the parameter settings of neural networks in GIScience. Moreover, the model performance of neural networks often depends on the parameter setting for a given dataset. Meanwhile, adjusting the parameter configuration of neural networks will increase the overall running time. Therefore, an automated approach is necessary for addressing these limitations in current studies. This book proposes an automated spatially explicit hyperparameter optimization approach to identify optimal or near-optimal parameter settings for neural networks in the GIScience field. Also, the approach improves the computing performance at both model and computing levels. This book is written for researchers of the GIScience field as well as social science subjects.

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