Regional ecosystem health assessment using the GA-BPANN model: a case study of Yunnan Province, China

Background: Regional ecosystem health assessments are the basis for the sustainable development of society. However, an ecosystem is a complex integration of ecosystem mosaics and subsystems that influence each other, making it difficult to evaluate them using traditional assessment methods of linea...
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Autor*in:	Yuze Li [verfasserIn] Yuanxiang Wu [verfasserIn] Xiaoguang Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Neural network model regional ecosystem health assessment Yunnan province

Übergeordnetes Werk:	In: Ecosystem Health and Sustainability - American Association for the Advancement of Science (AAAS), 2016, 8(2022), 1
Übergeordnetes Werk:	volume:8 ; year:2022 ; number:1

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1080/20964129.2022.2084458

Katalog-ID:	DOAJ043387292

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callnumber-first	Q - Science
author	Yuze Li
spellingShingle	Yuze Li misc QH540-549.5 misc Neural network model misc regional ecosystem health assessment misc Yunnan province misc Ecology Regional ecosystem health assessment using the GA-BPANN model: a case study of Yunnan Province, China
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topic_title	QH540-549.5 Regional ecosystem health assessment using the GA-BPANN model: a case study of Yunnan Province, China Neural network model regional ecosystem health assessment Yunnan province
topic	misc QH540-549.5 misc Neural network model misc regional ecosystem health assessment misc Yunnan province misc Ecology
topic_unstemmed	misc QH540-549.5 misc Neural network model misc regional ecosystem health assessment misc Yunnan province misc Ecology
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title	Regional ecosystem health assessment using the GA-BPANN model: a case study of Yunnan Province, China
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title_full	Regional ecosystem health assessment using the GA-BPANN model: a case study of Yunnan Province, China
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title_sort	regional ecosystem health assessment using the ga-bpann model: a case study of yunnan province, china
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title_auth	Regional ecosystem health assessment using the GA-BPANN model: a case study of Yunnan Province, China
abstract	Background: Regional ecosystem health assessments are the basis for the sustainable development of society. However, an ecosystem is a complex integration of ecosystem mosaics and subsystems that influence each other, making it difficult to evaluate them using traditional assessment methods of linear and explicit functions. We introduce a back-propagation neural network model optimized by a genetic algorithm to evaluate ecosystem health in 16 districts in Yunnan Province.Result: (1) The model required fewer inputs to evaluate complex and nonlinear systems, avoided the need for subjective weights, and performed well in this practical application to regional ecosystem health assessment. (2) The ecosystem health in Yunnan Province was increasing, and there was a significant positive spatial autocorrelation during 2000–2020, showing that districts with high Ecosystem Health cluster together and the ecological protection policy of the region has produced a diffusion effect, leading to continuous improvement of the ecological health of the surrounding areas. High-low outlier areas of ecosystem health should be paid more attention, because of the increasing instability of local health levels. Conclusion: This study provides a methodological exploration for assessing spatial mosaics of different ecosystems at a regional scale.
abstractGer	Background: Regional ecosystem health assessments are the basis for the sustainable development of society. However, an ecosystem is a complex integration of ecosystem mosaics and subsystems that influence each other, making it difficult to evaluate them using traditional assessment methods of linear and explicit functions. We introduce a back-propagation neural network model optimized by a genetic algorithm to evaluate ecosystem health in 16 districts in Yunnan Province.Result: (1) The model required fewer inputs to evaluate complex and nonlinear systems, avoided the need for subjective weights, and performed well in this practical application to regional ecosystem health assessment. (2) The ecosystem health in Yunnan Province was increasing, and there was a significant positive spatial autocorrelation during 2000–2020, showing that districts with high Ecosystem Health cluster together and the ecological protection policy of the region has produced a diffusion effect, leading to continuous improvement of the ecological health of the surrounding areas. High-low outlier areas of ecosystem health should be paid more attention, because of the increasing instability of local health levels. Conclusion: This study provides a methodological exploration for assessing spatial mosaics of different ecosystems at a regional scale.
abstract_unstemmed	Background: Regional ecosystem health assessments are the basis for the sustainable development of society. However, an ecosystem is a complex integration of ecosystem mosaics and subsystems that influence each other, making it difficult to evaluate them using traditional assessment methods of linear and explicit functions. We introduce a back-propagation neural network model optimized by a genetic algorithm to evaluate ecosystem health in 16 districts in Yunnan Province.Result: (1) The model required fewer inputs to evaluate complex and nonlinear systems, avoided the need for subjective weights, and performed well in this practical application to regional ecosystem health assessment. (2) The ecosystem health in Yunnan Province was increasing, and there was a significant positive spatial autocorrelation during 2000–2020, showing that districts with high Ecosystem Health cluster together and the ecological protection policy of the region has produced a diffusion effect, leading to continuous improvement of the ecological health of the surrounding areas. High-low outlier areas of ecosystem health should be paid more attention, because of the increasing instability of local health levels. Conclusion: This study provides a methodological exploration for assessing spatial mosaics of different ecosystems at a regional scale.
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title_short	Regional ecosystem health assessment using the GA-BPANN model: a case study of Yunnan Province, China
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Regional ecosystem health assessment using the GA-BPANN model: a case study of Yunnan Province, China

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