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Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics

It aims to improve the construction of ecological civilization and promote the common development of urban and ecology. Firstly, contemporary ecological ethics is explored, and its principles and characteristics are summarized. Then, the technique of convolutional neural network (CNN) image in a dee...

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Autor principal: Cheng, Haiyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956423/
https://www.ncbi.nlm.nih.gov/pubmed/35341192
http://dx.doi.org/10.1155/2022/8925205
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author Cheng, Haiyan
author_facet Cheng, Haiyan
author_sort Cheng, Haiyan
collection PubMed
description It aims to improve the construction of ecological civilization and promote the common development of urban and ecology. Firstly, contemporary ecological ethics is explored, and its principles and characteristics are summarized. Then, the technique of convolutional neural network (CNN) image in a deep learning model is analyzed. Finally, deep convolutional neural networks (DCNN) are used to analyze and model the spatial characteristics of contemporary cities based on ecological ethics. According to the investigations, rural residential areas are more consistent with ecological ethics than urban residential areas when compared with the ecological characteristics of farmland and forest, and the highest ecological eigenvalues of the two areas are about 8 and 6. In the analysis of urban space, the maximum value of ecological eigenvalues of an airport is 9, and that of a stadium is 8. However, the scope of their construction that is consistent with ecological ethics is very small. Moreover, the eigenvalues of ecological ethics in the urban business circle of casinos are not only very low (the highest values are about 5 and 3), but also consistent with the construction norms of ecological ethics. The work of urban spatial philosophy is optimized based on the adoption of the DCNN model of deep learning in ecological ethics, which not only provides the reference for future ecological urban planning but also contributes to the common development of urban and ecology.
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spelling pubmed-89564232022-03-26 Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics Cheng, Haiyan Comput Intell Neurosci Research Article It aims to improve the construction of ecological civilization and promote the common development of urban and ecology. Firstly, contemporary ecological ethics is explored, and its principles and characteristics are summarized. Then, the technique of convolutional neural network (CNN) image in a deep learning model is analyzed. Finally, deep convolutional neural networks (DCNN) are used to analyze and model the spatial characteristics of contemporary cities based on ecological ethics. According to the investigations, rural residential areas are more consistent with ecological ethics than urban residential areas when compared with the ecological characteristics of farmland and forest, and the highest ecological eigenvalues of the two areas are about 8 and 6. In the analysis of urban space, the maximum value of ecological eigenvalues of an airport is 9, and that of a stadium is 8. However, the scope of their construction that is consistent with ecological ethics is very small. Moreover, the eigenvalues of ecological ethics in the urban business circle of casinos are not only very low (the highest values are about 5 and 3), but also consistent with the construction norms of ecological ethics. The work of urban spatial philosophy is optimized based on the adoption of the DCNN model of deep learning in ecological ethics, which not only provides the reference for future ecological urban planning but also contributes to the common development of urban and ecology. Hindawi 2022-03-18 /pmc/articles/PMC8956423/ /pubmed/35341192 http://dx.doi.org/10.1155/2022/8925205 Text en Copyright © 2022 Haiyan Cheng. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Cheng, Haiyan
Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics
title Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics
title_full Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics
title_fullStr Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics
title_full_unstemmed Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics
title_short Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics
title_sort contemporary urban space philosophy in china using lightweight deep learning model-under ecological ethics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956423/
https://www.ncbi.nlm.nih.gov/pubmed/35341192
http://dx.doi.org/10.1155/2022/8925205
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