Evaluation and Prediction of City Sustainability Using MCDM and Stochastic Simulation Methods
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Index System
2.3. Study Methods
2.3.1. Research Framework
2.3.2. Evaluation Methods
2.3.3. Stochastic Prediction
3. Results
3.1. Evaluation Results
3.2. Prediction Results
4. Discussion, Conclusions, and Future Work
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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City | Population | Area (km2) | Annual Average Temperature (°C) | Annual Rainfall (mm) | Per-Capita GDP (USD) * |
---|---|---|---|---|---|
Shenyang | 7,339,000 | 12,860 | 8.8 | 967.9 | 10,131.47 |
Dalian | 5,956,000 | 12,574 | 12.0 | 380.2 | 14,762.59 |
Anshan | 3,457,000 | 9255 | 11.0 | 861.0 | 6138.89 |
Fushun | 2,148,000 | 11,272 | 7.4 | 1048.2 | 6322.00 |
Benxi | 1,500,000 | 8411 | 8.9 | 821.7 | 6776.99 |
Dandong | 2,379,000 | 15,290 | 9.9 | 1008.8 | 4728.97 |
Jinzhou | 3,022,000 | 10,047 | 10.7 | 629.9 | 5102.92 |
Yingkou | 2,328,000 | 5242 | 10.3 | 546.1 | 7172.74 |
Fuxin | 1,889,000 | 10,355 | 8.6 | 579.7 | 3476.87 |
Liaoyang | 1,786,000 | 4736 | 10.0 | 831.4 | 5474.44 |
Panjin | 1,301,000 | 4065 | 9.6 | 747.5 | 10,675.65 |
Tieling | 2,999,000 | 12,985 | 8.7 | 894.2 | 3365.85 |
Chaoyang | 3,411,000 | 19,698 | 10.0 | 543.0 | 3678.15 |
Huludao | 2,805,000 | 10,414 | 9.8 | 744.1 | 3839.00 |
Subsystem | Criterion (Code) | Unit | Property |
---|---|---|---|
Economy | GDP per capita (C1) | Yuan | Benefit |
Proportion of GDP generated by the service industry (C2) | % | Benefit | |
Ratio of profits, taxes, and interests to average assets of industrial enterprises above designated size (C3) | % | Benefit | |
Retail sales of consumer goods per capita (C4) | Yuan | Benefit | |
Amount of foreign investment actually utilized per capita (C5) | USD | Benefit | |
Growth rate of total export-import volume (C6) | % | Benefit | |
Per capita investment in fixed assets (C7) | Yuan | Benefit | |
Natural growth rate of population (C8) | ‰ | Benefit | |
Society | Registered urban unemployment rate (C9) | % | Cost |
Ratio of per capita income of urban and rural households (C10) | % | Cost | |
Per capita disposable income of urban households (C11) | Yuan | Benefit | |
Beds of medical institutions per 10,000 population (C12) | Unit | Benefit | |
Coverage rate of basic person insurance (C13) | % | Benefit | |
Per capita area of paved roads (C14) | m2 | Benefit | |
Investment in environmental protection as a proportion of DGP (C15) | % | Benefit | |
Environment | Per capita park green area (C16) | m2 | Benefit |
Per industrial enterprise waste water discharged (C17) | 10,000 tons | Cost | |
Per industrial enterprise SO2 emissions (C18) | Ton | Cost | |
Per industrial enterprise smoke and dust emissions (C19) | Ton | Cost | |
Ratio of industrial solid wastes comprehensively utilized (C20) | % | Benefit | |
Per capita area of afforestation (C21) | Hectare | Benefit |
City | Evaluation Score | Growth Rate * | Average Score ** | Average Ranking *** | ||||||
---|---|---|---|---|---|---|---|---|---|---|
2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | ||||
Shenyang | 0.511 | 0.531 | 0.552 | 0.574 | 0.59 | 0.568 | 0.554 | 0.72% | 0.554 | 2 |
Dalian | 0.491 | 0.552 | 0.579 | 0.607 | 0.596 | 0.555 | 0.529 | 0.63% | 0.559 | 1 |
Anshan | 0.404 | 0.467 | 0.461 | 0.505 | 0.457 | 0.471 | 0.48 | 1.27% | 0.464 | 5 |
Fushun | 0.391 | 0.375 | 0.405 | 0.474 | 0.432 | 0.474 | 0.452 | 1.02% | 0.429 | 9 |
Benxi | 0.365 | 0.406 | 0.428 | 0.471 | 0.491 | 0.454 | 0.441 | 1.27% | 0.436 | 8 |
Dandong | 0.388 | 0.468 | 0.475 | 0.515 | 0.525 | 0.458 | 0.528 | 2.34% | 0.48 | 4 |
Jinzhou | 0.297 | 0.341 | 0.39 | 0.453 | 0.429 | 0.44 | 0.454 | 2.62% | 0.401 | 11 |
Yingkou | 0.368 | 0.424 | 0.48 | 0.474 | 0.453 | 0.418 | 0.475 | 1.79% | 0.441 | 7 |
Fuxin | 0.313 | 0.326 | 0.373 | 0.392 | 0.44 | 0.41 | 0.405 | 1.53% | 0.38 | 14 |
Liaoyang | 0.352 | 0.395 | 0.401 | 0.465 | 0.501 | 0.492 | 0.505 | 2.56% | 0.445 | 6 |
Panjin | 0.423 | 0.459 | 0.483 | 0.516 | 0.518 | 0.504 | 0.517 | 1.57% | 0.489 | 3 |
Tieling | 0.354 | 0.382 | 0.442 | 0.484 | 0.444 | 0.444 | 0.414 | 1.00% | 0.423 | 10 |
Chaoyang | 0.303 | 0.405 | 0.375 | 0.432 | 0.424 | 0.432 | 0.413 | 1.85% | 0.398 | 12 |
Huludao | 0.306 | 0.363 | 0.394 | 0.433 | 0.459 | 0.421 | 0.409 | 1.71% | 0.397 | 13 |
City | Increase in the Prediction Scores | ||
---|---|---|---|
Minimum | Average | Maximum | |
Shenyang | 2.17% | 17.81% | 33.45% |
Dalian | 0.53% | 12.75% | 24.96% |
Anshan | 7.26% | 17.76% | 28.26% |
Fushun | 14.34% | 17.08% | 19.83% |
Benxi | 15.06% | 23.48% | 31.89% |
Dandong | 11.40% | 29.88% | 48.35% |
Jinzhou | 11.26% | 23.18% | 35.10% |
Yingkou | 8.24% | 31.26% | 54.28% |
Fuxin | 13.55% | 29.53% | 45.49% |
Liaoyang | 9.41% | 16.75% | 24.08% |
Panjin | −9.12% | 26.47% | 62.05% |
Tieling | 14.92% | 26.06% | 37.19% |
Chaoyang | 6.02% | 20.69% | 35.35% |
Huludao | 20.10% | 25.13% | 30.15% |
Shenyang | Dalian | Anshan | Fushun | Benxi | Dandong | Jinzhou |
11.5 | 9.5 | 7.5 | 4.5 | 5.5 | 13.5 | 6.5 |
Yingkou | Fuxin | Liaoyang | Panjin | Tieling | Chaoyang | Huludao |
10.5 | 3.5 | 8.5 | 12.5 | 2.5 | 0.5 | 1.5 |
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Yi, P.; Li, W.; Li, L. Evaluation and Prediction of City Sustainability Using MCDM and Stochastic Simulation Methods. Sustainability 2018, 10, 3771. https://doi.org/10.3390/su10103771
Yi P, Li W, Li L. Evaluation and Prediction of City Sustainability Using MCDM and Stochastic Simulation Methods. Sustainability. 2018; 10(10):3771. https://doi.org/10.3390/su10103771
Chicago/Turabian StyleYi, Pingtao, Weiwei Li, and Lingyu Li. 2018. "Evaluation and Prediction of City Sustainability Using MCDM and Stochastic Simulation Methods" Sustainability 10, no. 10: 3771. https://doi.org/10.3390/su10103771