Excel_ESs and transfer matrix. by Qianhong Mao (22305184)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Data sources and descriptions. by Qianhong Mao (22305184)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Coupling coordination types. by Qianhong Mao (22305184)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Results_urban-fringe-rural. by Qianhong Mao (22305184)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Datasets used in the study. by Rajon Banik (12066099)

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IRE1 depletion increases chromosome instability. by Iratxe Zuazo-Gaztelu (21071939)

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Structure diagram of ensemble model. by Hongqi Wang (2208238)

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Fitting formula parameter table. by Hongqi Wang (2208238)

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Test plan. by Hongqi Wang (2208238)

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Fitting surface parameters. by Hongqi Wang (2208238)

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Model generalisation validation error analysis. by Hongqi Wang (2208238)

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Empirical model prediction error analysis. by Hongqi Wang (2208238)

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Fitting curve parameters. by Hongqi Wang (2208238)

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Test instrument. by Hongqi Wang (2208238)

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Empirical model establishment process. by Hongqi Wang (2208238)

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Model prediction error trend chart. by Hongqi Wang (2208238)

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Basic physical parameters of red clay. by Hongqi Wang (2208238)

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BP neural network structure diagram. by Hongqi Wang (2208238)

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Structure diagram of GBDT model. by Hongqi Wang (2208238)

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Model prediction error analysis index. by Hongqi Wang (2208238)

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