Design and Realization of the Water Resources Carrying Capacity Evaluation Model for Marine Climate Cities
Yao, L. and Zhang, H., 2018. Design and realization of the water resources carrying capacity evaluation model for marine climate cities. In: Ashraf, M.A. and Chowdhury, A.J.K. (eds.), Coastal Ecosystem Responses to Human and Climatic Changes throughout Asia. To improve the living environment of mari...
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| description | Yao, L. and Zhang, H., 2018. Design and realization of the water resources carrying capacity evaluation model for marine climate cities. In: Ashraf, M.A. and Chowdhury, A.J.K. (eds.), Coastal Ecosystem Responses to Human and Climatic Changes throughout Asia. To improve the living environment of marine climate cities and the carrying level of water resources under maritime climate conditions, a water resources balance scheduling and cycle control-based evaluation model was proposed. The water balance model of marine climate cities was constructed using Gauss-Newton iteration and the volume square root particle filter method. According to the importance of density function, the confidence interval of the water resources carrying capacity level was analyzed, and the optimal allocation of the water resources carrying capacity based on the particle swarm optimization algorithm was made. Using the reduction coefficient of water resources retention to mechanically control the carrying capacity, the water resources carrying capacity evaluation of a marine climate city was achieved. In the embedded environment, software development and design of the water resources carrying capacity evaluation model were performed. The software system of the water resources carrying capacity evaluation model includes the water resources flow evaluation system, water resources mechanical evaluation system, and program compiler, connector, debugger, and other subsystems. Under the control of the kernel decompression program, the executable code was generated by the mechanical evaluation program compiled to realize the software development and model optimization design of the water resources carrying capacity evaluation model. The simulation results showed that this evaluation method presented good forecasting performance of the water resources carrying capacity of marine climate cities and that this improved the monitoring and judgment ability of climate in the adjacent areas. By combining climate regulation and artificial intervention, the maritime climate conditions and the cycle control level of water resources can be improved, which promotes a good application value in climate regulation. |
| doi_str_mv | 10.2112/SI82-002.1 |
| format | Article |
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Design and realization of the water resources carrying capacity evaluation model for marine climate cities. In: Ashraf, M.A. and Chowdhury, A.J.K. (eds.), Coastal Ecosystem Responses to Human and Climatic Changes throughout Asia. To improve the living environment of marine climate cities and the carrying level of water resources under maritime climate conditions, a water resources balance scheduling and cycle control-based evaluation model was proposed. The water balance model of marine climate cities was constructed using Gauss-Newton iteration and the volume square root particle filter method. According to the importance of density function, the confidence interval of the water resources carrying capacity level was analyzed, and the optimal allocation of the water resources carrying capacity based on the particle swarm optimization algorithm was made. Using the reduction coefficient of water resources retention to mechanically control the carrying capacity, the water resources carrying capacity evaluation of a marine climate city was achieved. In the embedded environment, software development and design of the water resources carrying capacity evaluation model were performed. The software system of the water resources carrying capacity evaluation model includes the water resources flow evaluation system, water resources mechanical evaluation system, and program compiler, connector, debugger, and other subsystems. Under the control of the kernel decompression program, the executable code was generated by the mechanical evaluation program compiled to realize the software development and model optimization design of the water resources carrying capacity evaluation model. The simulation results showed that this evaluation method presented good forecasting performance of the water resources carrying capacity of marine climate cities and that this improved the monitoring and judgment ability of climate in the adjacent areas. By combining climate regulation and artificial intervention, the maritime climate conditions and the cycle control level of water resources can be improved, which promotes a good application value in climate regulation.</description><identifier>ISSN: 0749-0208</identifier><identifier>EISSN: 1551-5036</identifier><identifier>DOI: 10.2112/SI82-002.1</identifier><language>eng</language><publisher>Fort Lauderdale: The Coastal Education and Research Foundation</publisher><subject>Carrying capacity ; carrying capacity evaluation model ; Cities ; Climate ; Climatic conditions ; Computer programs ; Computer simulation ; Confidence intervals ; Connectors ; Control ; Debugging ; Decompression ; Design ; Design optimization ; Ecosystems ; Evaluation ; Humidity ; Iterative methods ; Marine climate city ; Neural networks ; Particle swarm optimization ; Precipitation ; Resource scheduling ; Science ; Software ; Software development ; Temperature ; Typhoons ; Water balance ; Water resources</subject><ispartof>Journal of coastal research, 2018-09, Vol.82 (sp1), p.12-23</ispartof><rights>Coastal Education and Research Foundation, Inc. 2018</rights><rights>Copyright Allen Press Publishing Services 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-b273t-6da14c3b68d46e5da4cd706673fa39071d481e5eea78384abc09ec80fc458c0b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26542364$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26542364$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,27903,27904,57995,58228</link.rule.ids></links><search><creatorcontrib>Yao, Longqin</creatorcontrib><creatorcontrib>Zhang, Hengquan</creatorcontrib><title>Design and Realization of the Water Resources Carrying Capacity Evaluation Model for Marine Climate Cities</title><title>Journal of coastal research</title><description>Yao, L. and Zhang, H., 2018. Design and realization of the water resources carrying capacity evaluation model for marine climate cities. In: Ashraf, M.A. and Chowdhury, A.J.K. (eds.), Coastal Ecosystem Responses to Human and Climatic Changes throughout Asia. To improve the living environment of marine climate cities and the carrying level of water resources under maritime climate conditions, a water resources balance scheduling and cycle control-based evaluation model was proposed. The water balance model of marine climate cities was constructed using Gauss-Newton iteration and the volume square root particle filter method. According to the importance of density function, the confidence interval of the water resources carrying capacity level was analyzed, and the optimal allocation of the water resources carrying capacity based on the particle swarm optimization algorithm was made. Using the reduction coefficient of water resources retention to mechanically control the carrying capacity, the water resources carrying capacity evaluation of a marine climate city was achieved. In the embedded environment, software development and design of the water resources carrying capacity evaluation model were performed. The software system of the water resources carrying capacity evaluation model includes the water resources flow evaluation system, water resources mechanical evaluation system, and program compiler, connector, debugger, and other subsystems. Under the control of the kernel decompression program, the executable code was generated by the mechanical evaluation program compiled to realize the software development and model optimization design of the water resources carrying capacity evaluation model. The simulation results showed that this evaluation method presented good forecasting performance of the water resources carrying capacity of marine climate cities and that this improved the monitoring and judgment ability of climate in the adjacent areas. By combining climate regulation and artificial intervention, the maritime climate conditions and the cycle control level of water resources can be improved, which promotes a good application value in climate regulation.</description><subject>Carrying capacity</subject><subject>carrying capacity evaluation model</subject><subject>Cities</subject><subject>Climate</subject><subject>Climatic conditions</subject><subject>Computer programs</subject><subject>Computer simulation</subject><subject>Confidence intervals</subject><subject>Connectors</subject><subject>Control</subject><subject>Debugging</subject><subject>Decompression</subject><subject>Design</subject><subject>Design optimization</subject><subject>Ecosystems</subject><subject>Evaluation</subject><subject>Humidity</subject><subject>Iterative methods</subject><subject>Marine climate city</subject><subject>Neural networks</subject><subject>Particle swarm optimization</subject><subject>Precipitation</subject><subject>Resource scheduling</subject><subject>Science</subject><subject>Software</subject><subject>Software development</subject><subject>Temperature</subject><subject>Typhoons</subject><subject>Water balance</subject><subject>Water resources</subject><issn>0749-0208</issn><issn>1551-5036</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kM1LAzEQxYMoWKsX70LAiwir-dpsepS1aqFF8AOPSzY7W1PWTU1Sof71pqx49DQD7zdvHg-hU0quGKXs-nmmWEYIu6J7aETznGY54XIfjUghJhlhRB2ioxBWhFCpRDFCq1sIdtlj3Tf4CXRnv3W0rseuxfEd8JuO4JMQ3MYbCLjU3m9tv0zLWhsbt3j6pbvNcLNwDXS4dR4vtLc94LKzH8kAlzZaCMfooNVdgJPfOUavd9OX8iGbP97Pypt5VrOCx0w2mgrDa6kaISFvtDBNQaQseKv5hBS0EYpCDqALxZXQtSETMIq0RuTKkJqP0fngu_bucwMhVquUvk8vK0Z5QYmQQibqcqCMdyF4aKu1T2n9tqKk2nVZ7bqsUpcVTfDZAK9CdP6PZDIXjEuR9ItBr61zPfxn9QNBEXz8</recordid><startdate>20180901</startdate><enddate>20180901</enddate><creator>Yao, Longqin</creator><creator>Zhang, Hengquan</creator><general>The Coastal Education and Research Foundation</general><general>COASTAL EDUCATION & RESEARCH FOUNDATION, INC. 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and Realization of the Water Resources Carrying Capacity Evaluation Model for Marine Climate Cities</title><author>Yao, Longqin ; Zhang, Hengquan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b273t-6da14c3b68d46e5da4cd706673fa39071d481e5eea78384abc09ec80fc458c0b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Carrying capacity</topic><topic>carrying capacity evaluation model</topic><topic>Cities</topic><topic>Climate</topic><topic>Climatic conditions</topic><topic>Computer programs</topic><topic>Computer simulation</topic><topic>Confidence intervals</topic><topic>Connectors</topic><topic>Control</topic><topic>Debugging</topic><topic>Decompression</topic><topic>Design</topic><topic>Design optimization</topic><topic>Ecosystems</topic><topic>Evaluation</topic><topic>Humidity</topic><topic>Iterative methods</topic><topic>Marine climate city</topic><topic>Neural networks</topic><topic>Particle swarm optimization</topic><topic>Precipitation</topic><topic>Resource scheduling</topic><topic>Science</topic><topic>Software</topic><topic>Software development</topic><topic>Temperature</topic><topic>Typhoons</topic><topic>Water balance</topic><topic>Water resources</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yao, Longqin</creatorcontrib><creatorcontrib>Zhang, Hengquan</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aluminium Industry Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology 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Design and realization of the water resources carrying capacity evaluation model for marine climate cities. In: Ashraf, M.A. and Chowdhury, A.J.K. (eds.), Coastal Ecosystem Responses to Human and Climatic Changes throughout Asia. To improve the living environment of marine climate cities and the carrying level of water resources under maritime climate conditions, a water resources balance scheduling and cycle control-based evaluation model was proposed. The water balance model of marine climate cities was constructed using Gauss-Newton iteration and the volume square root particle filter method. According to the importance of density function, the confidence interval of the water resources carrying capacity level was analyzed, and the optimal allocation of the water resources carrying capacity based on the particle swarm optimization algorithm was made. Using the reduction coefficient of water resources retention to mechanically control the carrying capacity, the water resources carrying capacity evaluation of a marine climate city was achieved. In the embedded environment, software development and design of the water resources carrying capacity evaluation model were performed. The software system of the water resources carrying capacity evaluation model includes the water resources flow evaluation system, water resources mechanical evaluation system, and program compiler, connector, debugger, and other subsystems. Under the control of the kernel decompression program, the executable code was generated by the mechanical evaluation program compiled to realize the software development and model optimization design of the water resources carrying capacity evaluation model. The simulation results showed that this evaluation method presented good forecasting performance of the water resources carrying capacity of marine climate cities and that this improved the monitoring and judgment ability of climate in the adjacent areas. By combining climate regulation and artificial intervention, the maritime climate conditions and the cycle control level of water resources can be improved, which promotes a good application value in climate regulation.</abstract><cop>Fort Lauderdale</cop><pub>The Coastal Education and Research Foundation</pub><doi>10.2112/SI82-002.1</doi><tpages>12</tpages></addata></record> |
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| subjects | Carrying capacity carrying capacity evaluation model Cities Climate Climatic conditions Computer programs Computer simulation Confidence intervals Connectors Control Debugging Decompression Design Design optimization Ecosystems Evaluation Humidity Iterative methods Marine climate city Neural networks Particle swarm optimization Precipitation Resource scheduling Science Software Software development Temperature Typhoons Water balance Water resources |
| title | Design and Realization of the Water Resources Carrying Capacity Evaluation Model for Marine Climate Cities |
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