Loading…
Exploring the interaction relationship between Beautiful China-SciTech innovation using coupling coordination and predictive analysis: a case study of Zhejiang
Exploring interaction of Beautiful China and SciTech Innovation is an important way to realize economic transformation and sustainable development in China. Existed researches have analyzed the development of ecology or development of SciTech Innovation in China while few have studied the correlatio...
Saved in:
Published in: | Environment, development and sustainability development and sustainability, 2022-10, Vol.24 (10), p.12097-12130 |
---|---|
Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c319t-d4b2d25ab1d47dc894ea3e89b9f1444891806b35a7262352777d4b7a4bd6abca3 |
---|---|
cites | cdi_FETCH-LOGICAL-c319t-d4b2d25ab1d47dc894ea3e89b9f1444891806b35a7262352777d4b7a4bd6abca3 |
container_end_page | 12130 |
container_issue | 10 |
container_start_page | 12097 |
container_title | Environment, development and sustainability |
container_volume | 24 |
creator | Hua, Yi-di Hu, Ke-man Qiu, Lu-yi Dong, Hong-an Ding, Lei Lo, Sio-Long |
description | Exploring interaction of Beautiful China and SciTech Innovation is an important way to realize economic transformation and sustainable development in China. Existed researches have analyzed the development of ecology or development of SciTech Innovation in China while few have studied the correlation between Beautiful China and SciTech innovation. This study takes Zhejiang province as a case and analyzed the integration level of Beautiful Zhejiang and SciTech Innovation with an aim to shed light on policy making. Evaluating index systems of Beautiful Zhejiang and SciTech Innovation with 8 subsystems and 36 indicators are established. The weights of indexes are calculated with more precise accuracy by combing Structure Entropy Method and Mean Squared Deviation Method. Related statistics of 11 cities of Zhejiang province are collected for time period of 2007–2017, and comprehensive development indexes are evaluated. Coupling coordination degree between the two systems is computed, and coupling coordination degree of 2018–2021 is predicted based on Back Propagation Neural Network. The results show as follows. (1) The development of both systems of Beautiful Zhejiang and SciTech Innovation are in a steady upward trend with SciTech Innovation lagging behind Beautiful Zhejiang. The system of Beautiful Zhejiang ranks as Hangzhou > Ningbo > Wenzhou > Shaoxing > Jinhua > Taizhou > Jiaxing > Huzhou > Zhoushan > Lishui > Quzhou. The system of SciTech Innovation ranks as Hangzhou > Ningbo > Jiaxing > Shaoxing > Wenzhou > Taizhou > Jinhua > Huzhou > Zhoushan > Lishui > Quzhou. (2) The integration level of Hangzhou and Ningbo are developing from Barely Balanced stage to Superior Balanced stage in 2007–2017; Wenzhou, Jiaxing, Huzhou, Shaoxing, Jinhua, Quzhou, Zhou Shan, and Taizhou are developing from Slightly Unbalanced stage to Barely Balanced stage; Lishui has the lowest integration level developing from extremely unbalanced stage to barely balanced stage. (3) The integration level based on coupling coordination degree is predicted with the method of Back Propagation Neural Network, and it is found that by 2021 Hangzhou, Ningbo, Wenzhou, Shaoxing and Taizhou will enter the Superior Balanced stage successively while Jiaxing, Huzhou, Jinhua, Quzhou, Zhoushan, and Lishui will remain in the Barely Balanced stage. |
doi_str_mv | 10.1007/s10668-021-01936-6 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2713854070</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2713854070</sourcerecordid><originalsourceid>FETCH-LOGICAL-c319t-d4b2d25ab1d47dc894ea3e89b9f1444891806b35a7262352777d4b7a4bd6abca3</originalsourceid><addsrcrecordid>eNp9kc1u1DAUhSMEEqXwAqwssXbxT2In7OioLUiVuqCVqm6sG_um8SjEqZ0MzNP0VfFMKnXHysfy-c617imKz5ydccb018SZUjVlglPGG6moelOc8EpLKhpdvc1a1ppWdXX_vviQ0pYxwRqhTorni7_TEKIfH8ncI_HjjBHs7MNIIg5wEKn3E2lx_oM4knOEZfbdMpBN70egv6y_RdtncAy7o50s6ZBmwzINqwjRZevxDUZHpojO5xE7zFcY9smnbwSIhYQkzYvbk9CRhx63HsbHj8W7DoaEn17O0-Lu8uJ284Ne31z93Hy_plbyZqaubIUTFbTcldrZuikRJNZN23S8LMu64TVTraxACyVkJbTWGdFQtk5Ba0GeFl_W3CmGpwXTbLZhifl7yQidl1eVTLPsEqvLxpBSxM5M0f-GuDecmUMRZi3C5CLMsQijMiRXKE2HPWN8jf4P9Q9gF4-1</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2713854070</pqid></control><display><type>article</type><title>Exploring the interaction relationship between Beautiful China-SciTech innovation using coupling coordination and predictive analysis: a case study of Zhejiang</title><source>International Bibliography of the Social Sciences (IBSS)</source><source>ABI/INFORM Global (ProQuest)</source><source>Business Source Ultimate</source><source>Springer Nature</source><creator>Hua, Yi-di ; Hu, Ke-man ; Qiu, Lu-yi ; Dong, Hong-an ; Ding, Lei ; Lo, Sio-Long</creator><creatorcontrib>Hua, Yi-di ; Hu, Ke-man ; Qiu, Lu-yi ; Dong, Hong-an ; Ding, Lei ; Lo, Sio-Long</creatorcontrib><description>Exploring interaction of Beautiful China and SciTech Innovation is an important way to realize economic transformation and sustainable development in China. Existed researches have analyzed the development of ecology or development of SciTech Innovation in China while few have studied the correlation between Beautiful China and SciTech innovation. This study takes Zhejiang province as a case and analyzed the integration level of Beautiful Zhejiang and SciTech Innovation with an aim to shed light on policy making. Evaluating index systems of Beautiful Zhejiang and SciTech Innovation with 8 subsystems and 36 indicators are established. The weights of indexes are calculated with more precise accuracy by combing Structure Entropy Method and Mean Squared Deviation Method. Related statistics of 11 cities of Zhejiang province are collected for time period of 2007–2017, and comprehensive development indexes are evaluated. Coupling coordination degree between the two systems is computed, and coupling coordination degree of 2018–2021 is predicted based on Back Propagation Neural Network. The results show as follows. (1) The development of both systems of Beautiful Zhejiang and SciTech Innovation are in a steady upward trend with SciTech Innovation lagging behind Beautiful Zhejiang. The system of Beautiful Zhejiang ranks as Hangzhou > Ningbo > Wenzhou > Shaoxing > Jinhua > Taizhou > Jiaxing > Huzhou > Zhoushan > Lishui > Quzhou. The system of SciTech Innovation ranks as Hangzhou > Ningbo > Jiaxing > Shaoxing > Wenzhou > Taizhou > Jinhua > Huzhou > Zhoushan > Lishui > Quzhou. (2) The integration level of Hangzhou and Ningbo are developing from Barely Balanced stage to Superior Balanced stage in 2007–2017; Wenzhou, Jiaxing, Huzhou, Shaoxing, Jinhua, Quzhou, Zhou Shan, and Taizhou are developing from Slightly Unbalanced stage to Barely Balanced stage; Lishui has the lowest integration level developing from extremely unbalanced stage to barely balanced stage. (3) The integration level based on coupling coordination degree is predicted with the method of Back Propagation Neural Network, and it is found that by 2021 Hangzhou, Ningbo, Wenzhou, Shaoxing and Taizhou will enter the Superior Balanced stage successively while Jiaxing, Huzhou, Jinhua, Quzhou, Zhoushan, and Lishui will remain in the Barely Balanced stage.</description><identifier>ISSN: 1387-585X</identifier><identifier>EISSN: 1573-2975</identifier><identifier>DOI: 10.1007/s10668-021-01936-6</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Back propagation ; Back propagation networks ; Coordination ; Coupling ; Earth and Environmental Science ; Ecology ; Economic analysis ; Economic Geology ; Economic Growth ; Entropy ; Environment ; Environmental Economics ; Environmental Management ; Innovations ; Integration ; Neural networks ; Policy making ; Statistical analysis ; Subsystems ; Sustainable Development ; Transformation</subject><ispartof>Environment, development and sustainability, 2022-10, Vol.24 (10), p.12097-12130</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2021</rights><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-d4b2d25ab1d47dc894ea3e89b9f1444891806b35a7262352777d4b7a4bd6abca3</citedby><cites>FETCH-LOGICAL-c319t-d4b2d25ab1d47dc894ea3e89b9f1444891806b35a7262352777d4b7a4bd6abca3</cites><orcidid>0000-0001-6726-7808</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2713854070/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2713854070?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,777,781,11669,12828,27905,27906,33204,36041,44344,74644</link.rule.ids></links><search><creatorcontrib>Hua, Yi-di</creatorcontrib><creatorcontrib>Hu, Ke-man</creatorcontrib><creatorcontrib>Qiu, Lu-yi</creatorcontrib><creatorcontrib>Dong, Hong-an</creatorcontrib><creatorcontrib>Ding, Lei</creatorcontrib><creatorcontrib>Lo, Sio-Long</creatorcontrib><title>Exploring the interaction relationship between Beautiful China-SciTech innovation using coupling coordination and predictive analysis: a case study of Zhejiang</title><title>Environment, development and sustainability</title><addtitle>Environ Dev Sustain</addtitle><description>Exploring interaction of Beautiful China and SciTech Innovation is an important way to realize economic transformation and sustainable development in China. Existed researches have analyzed the development of ecology or development of SciTech Innovation in China while few have studied the correlation between Beautiful China and SciTech innovation. This study takes Zhejiang province as a case and analyzed the integration level of Beautiful Zhejiang and SciTech Innovation with an aim to shed light on policy making. Evaluating index systems of Beautiful Zhejiang and SciTech Innovation with 8 subsystems and 36 indicators are established. The weights of indexes are calculated with more precise accuracy by combing Structure Entropy Method and Mean Squared Deviation Method. Related statistics of 11 cities of Zhejiang province are collected for time period of 2007–2017, and comprehensive development indexes are evaluated. Coupling coordination degree between the two systems is computed, and coupling coordination degree of 2018–2021 is predicted based on Back Propagation Neural Network. The results show as follows. (1) The development of both systems of Beautiful Zhejiang and SciTech Innovation are in a steady upward trend with SciTech Innovation lagging behind Beautiful Zhejiang. The system of Beautiful Zhejiang ranks as Hangzhou > Ningbo > Wenzhou > Shaoxing > Jinhua > Taizhou > Jiaxing > Huzhou > Zhoushan > Lishui > Quzhou. The system of SciTech Innovation ranks as Hangzhou > Ningbo > Jiaxing > Shaoxing > Wenzhou > Taizhou > Jinhua > Huzhou > Zhoushan > Lishui > Quzhou. (2) The integration level of Hangzhou and Ningbo are developing from Barely Balanced stage to Superior Balanced stage in 2007–2017; Wenzhou, Jiaxing, Huzhou, Shaoxing, Jinhua, Quzhou, Zhou Shan, and Taizhou are developing from Slightly Unbalanced stage to Barely Balanced stage; Lishui has the lowest integration level developing from extremely unbalanced stage to barely balanced stage. (3) The integration level based on coupling coordination degree is predicted with the method of Back Propagation Neural Network, and it is found that by 2021 Hangzhou, Ningbo, Wenzhou, Shaoxing and Taizhou will enter the Superior Balanced stage successively while Jiaxing, Huzhou, Jinhua, Quzhou, Zhoushan, and Lishui will remain in the Barely Balanced stage.</description><subject>Back propagation</subject><subject>Back propagation networks</subject><subject>Coordination</subject><subject>Coupling</subject><subject>Earth and Environmental Science</subject><subject>Ecology</subject><subject>Economic analysis</subject><subject>Economic Geology</subject><subject>Economic Growth</subject><subject>Entropy</subject><subject>Environment</subject><subject>Environmental Economics</subject><subject>Environmental Management</subject><subject>Innovations</subject><subject>Integration</subject><subject>Neural networks</subject><subject>Policy making</subject><subject>Statistical analysis</subject><subject>Subsystems</subject><subject>Sustainable Development</subject><subject>Transformation</subject><issn>1387-585X</issn><issn>1573-2975</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>8BJ</sourceid><sourceid>M0C</sourceid><recordid>eNp9kc1u1DAUhSMEEqXwAqwssXbxT2In7OioLUiVuqCVqm6sG_um8SjEqZ0MzNP0VfFMKnXHysfy-c617imKz5ydccb018SZUjVlglPGG6moelOc8EpLKhpdvc1a1ppWdXX_vviQ0pYxwRqhTorni7_TEKIfH8ncI_HjjBHs7MNIIg5wEKn3E2lx_oM4knOEZfbdMpBN70egv6y_RdtncAy7o50s6ZBmwzINqwjRZevxDUZHpojO5xE7zFcY9smnbwSIhYQkzYvbk9CRhx63HsbHj8W7DoaEn17O0-Lu8uJ284Ne31z93Hy_plbyZqaubIUTFbTcldrZuikRJNZN23S8LMu64TVTraxACyVkJbTWGdFQtk5Ba0GeFl_W3CmGpwXTbLZhifl7yQidl1eVTLPsEqvLxpBSxM5M0f-GuDecmUMRZi3C5CLMsQijMiRXKE2HPWN8jf4P9Q9gF4-1</recordid><startdate>20221001</startdate><enddate>20221001</enddate><creator>Hua, Yi-di</creator><creator>Hu, Ke-man</creator><creator>Qiu, Lu-yi</creator><creator>Dong, Hong-an</creator><creator>Ding, Lei</creator><creator>Lo, Sio-Long</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7U6</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AO</scope><scope>8BJ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>KR7</scope><scope>L.-</scope><scope>L6V</scope><scope>M0C</scope><scope>M7S</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-6726-7808</orcidid></search><sort><creationdate>20221001</creationdate><title>Exploring the interaction relationship between Beautiful China-SciTech innovation using coupling coordination and predictive analysis: a case study of Zhejiang</title><author>Hua, Yi-di ; Hu, Ke-man ; Qiu, Lu-yi ; Dong, Hong-an ; Ding, Lei ; Lo, Sio-Long</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-d4b2d25ab1d47dc894ea3e89b9f1444891806b35a7262352777d4b7a4bd6abca3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Back propagation</topic><topic>Back propagation networks</topic><topic>Coordination</topic><topic>Coupling</topic><topic>Earth and Environmental Science</topic><topic>Ecology</topic><topic>Economic analysis</topic><topic>Economic Geology</topic><topic>Economic Growth</topic><topic>Entropy</topic><topic>Environment</topic><topic>Environmental Economics</topic><topic>Environmental Management</topic><topic>Innovations</topic><topic>Integration</topic><topic>Neural networks</topic><topic>Policy making</topic><topic>Statistical analysis</topic><topic>Subsystems</topic><topic>Sustainable Development</topic><topic>Transformation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hua, Yi-di</creatorcontrib><creatorcontrib>Hu, Ke-man</creatorcontrib><creatorcontrib>Qiu, Lu-yi</creatorcontrib><creatorcontrib>Dong, Hong-an</creatorcontrib><creatorcontrib>Ding, Lei</creatorcontrib><creatorcontrib>Lo, Sio-Long</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>ProQuest Pharma Collection</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>International Bibliography of the Social Sciences</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global (ProQuest)</collection><collection>Engineering Database</collection><collection>Environmental Science Database</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><jtitle>Environment, development and sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hua, Yi-di</au><au>Hu, Ke-man</au><au>Qiu, Lu-yi</au><au>Dong, Hong-an</au><au>Ding, Lei</au><au>Lo, Sio-Long</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploring the interaction relationship between Beautiful China-SciTech innovation using coupling coordination and predictive analysis: a case study of Zhejiang</atitle><jtitle>Environment, development and sustainability</jtitle><stitle>Environ Dev Sustain</stitle><date>2022-10-01</date><risdate>2022</risdate><volume>24</volume><issue>10</issue><spage>12097</spage><epage>12130</epage><pages>12097-12130</pages><issn>1387-585X</issn><eissn>1573-2975</eissn><abstract>Exploring interaction of Beautiful China and SciTech Innovation is an important way to realize economic transformation and sustainable development in China. Existed researches have analyzed the development of ecology or development of SciTech Innovation in China while few have studied the correlation between Beautiful China and SciTech innovation. This study takes Zhejiang province as a case and analyzed the integration level of Beautiful Zhejiang and SciTech Innovation with an aim to shed light on policy making. Evaluating index systems of Beautiful Zhejiang and SciTech Innovation with 8 subsystems and 36 indicators are established. The weights of indexes are calculated with more precise accuracy by combing Structure Entropy Method and Mean Squared Deviation Method. Related statistics of 11 cities of Zhejiang province are collected for time period of 2007–2017, and comprehensive development indexes are evaluated. Coupling coordination degree between the two systems is computed, and coupling coordination degree of 2018–2021 is predicted based on Back Propagation Neural Network. The results show as follows. (1) The development of both systems of Beautiful Zhejiang and SciTech Innovation are in a steady upward trend with SciTech Innovation lagging behind Beautiful Zhejiang. The system of Beautiful Zhejiang ranks as Hangzhou > Ningbo > Wenzhou > Shaoxing > Jinhua > Taizhou > Jiaxing > Huzhou > Zhoushan > Lishui > Quzhou. The system of SciTech Innovation ranks as Hangzhou > Ningbo > Jiaxing > Shaoxing > Wenzhou > Taizhou > Jinhua > Huzhou > Zhoushan > Lishui > Quzhou. (2) The integration level of Hangzhou and Ningbo are developing from Barely Balanced stage to Superior Balanced stage in 2007–2017; Wenzhou, Jiaxing, Huzhou, Shaoxing, Jinhua, Quzhou, Zhou Shan, and Taizhou are developing from Slightly Unbalanced stage to Barely Balanced stage; Lishui has the lowest integration level developing from extremely unbalanced stage to barely balanced stage. (3) The integration level based on coupling coordination degree is predicted with the method of Back Propagation Neural Network, and it is found that by 2021 Hangzhou, Ningbo, Wenzhou, Shaoxing and Taizhou will enter the Superior Balanced stage successively while Jiaxing, Huzhou, Jinhua, Quzhou, Zhoushan, and Lishui will remain in the Barely Balanced stage.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10668-021-01936-6</doi><tpages>34</tpages><orcidid>https://orcid.org/0000-0001-6726-7808</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1387-585X |
ispartof | Environment, development and sustainability, 2022-10, Vol.24 (10), p.12097-12130 |
issn | 1387-585X 1573-2975 |
language | eng |
recordid | cdi_proquest_journals_2713854070 |
source | International Bibliography of the Social Sciences (IBSS); ABI/INFORM Global (ProQuest); Business Source Ultimate; Springer Nature |
subjects | Back propagation Back propagation networks Coordination Coupling Earth and Environmental Science Ecology Economic analysis Economic Geology Economic Growth Entropy Environment Environmental Economics Environmental Management Innovations Integration Neural networks Policy making Statistical analysis Subsystems Sustainable Development Transformation |
title | Exploring the interaction relationship between Beautiful China-SciTech innovation using coupling coordination and predictive analysis: a case study of Zhejiang |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T01%3A09%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Exploring%20the%20interaction%20relationship%20between%20Beautiful%20China-SciTech%20innovation%20using%20coupling%20coordination%20and%20predictive%20analysis:%20a%20case%20study%20of%20Zhejiang&rft.jtitle=Environment,%20development%20and%20sustainability&rft.au=Hua,%20Yi-di&rft.date=2022-10-01&rft.volume=24&rft.issue=10&rft.spage=12097&rft.epage=12130&rft.pages=12097-12130&rft.issn=1387-585X&rft.eissn=1573-2975&rft_id=info:doi/10.1007/s10668-021-01936-6&rft_dat=%3Cproquest_cross%3E2713854070%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c319t-d4b2d25ab1d47dc894ea3e89b9f1444891806b35a7262352777d4b7a4bd6abca3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2713854070&rft_id=info:pmid/&rfr_iscdi=true |