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Pan Lihu, male, Han nationality, born in 1974, Ph.D., professor, senior member of China Computer Society, correspondent member of Software Engineering Committee of China Computer Society. Since 2004, he has taught at the School of Computer Science and Technology of Taiyuan University of Science and Technology. In 2010, he received a Ph.D. from the Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences. Professor Pan is mainly engaged in the research of complex geographic system simulation, artificial intelligence, software engineering and so on. Research theories and methods include the application of software engineering techniques, complexity theory, artificial social methods, economic theory and computer modeling methods to study related issues in the geographical, social and economic fields.
Improving the urban livability status has become the core goal of urban development, and reasonable assessment of the urban livability status and impact is crucial. By combining an objective environment with residents’ subjective cognition, an artificial society (urban livability change artificial society; ULC-AS) is constructed. The ULC-AS includes four types of agents, namely, government, family, resident and safety facility management agency agents, and recognizes dynamic interaction among various agents and between agents and the environment. Taking the Futian District of Shenzhen as an example, this paper examines factors such as migrants, birth policies, and government investment. We simulate the interactions among resident satisfaction changes, relocation decision-making behavior and urban safety livability and analyze the change processes and development trends of urban safety livability under multiple scenarios. Our main result indicates that population change and investment construction are important factors affecting urban safety livability. At present, the population of the Futian District is saturated. Therefore, the government must assess the urban safety livability and increase investment in high-demand areas. Through this method, the goals of urban resource allocation optimization and coordinated urban development can be achieved.
Lihu Pan; Le Zhang; Shipeng Qin; Huimin Yan; Rui Peng; Fen Li. Study on an Artificial Society of Urban Safety Livability Change. ISPRS International Journal of Geo-Information 2021, 10, 70 .
AMA StyleLihu Pan, Le Zhang, Shipeng Qin, Huimin Yan, Rui Peng, Fen Li. Study on an Artificial Society of Urban Safety Livability Change. ISPRS International Journal of Geo-Information. 2021; 10 (2):70.
Chicago/Turabian StyleLihu Pan; Le Zhang; Shipeng Qin; Huimin Yan; Rui Peng; Fen Li. 2021. "Study on an Artificial Society of Urban Safety Livability Change." ISPRS International Journal of Geo-Information 10, no. 2: 70.
Assessment and analysis of ecological carrying capacity are significant issues in regional sustainable development. Large-scale ecological carrying capacity research consume a lot of time and labor costs. In this paper, considering redundant storage, on-demand computing, and multi-scale representation, a block storage and analysis model (BSAM) is proposed to make computation faster. Taking “The Belt and Road Initiative” as an example, the ecological carrying capacity evaluation system (ECCES) was developed. The results show that the problems of low calculation efficiency and high time cost were effectively solved with improved data storage, analysis, and expression approaches used by the ECCES. And the calculation speed is improved with the BSAM. Moreover, in the BSAM, the complexity of the original data is under a more significant impact on computing speed. In contrast, the complexity of an algorithm has a smaller influence on computing speed. Furthermore, the early warning push function and automated report function can generate the ecological carrying capacity states or changes automatically, which can improve the real-time, usability, and convenience of the ecological carrying capacity assessment.
Lihu Pan; Yunkai Li; Yu Dong; Huimin Yan. Research on Block Storage and Analysis Model for Belt and Road Initiative Ecological Carrying Capacity Evaluation System. Communications in Computer and Information Science 2020, 354 -368.
AMA StyleLihu Pan, Yunkai Li, Yu Dong, Huimin Yan. Research on Block Storage and Analysis Model for Belt and Road Initiative Ecological Carrying Capacity Evaluation System. Communications in Computer and Information Science. 2020; ():354-368.
Chicago/Turabian StyleLihu Pan; Yunkai Li; Yu Dong; Huimin Yan. 2020. "Research on Block Storage and Analysis Model for Belt and Road Initiative Ecological Carrying Capacity Evaluation System." Communications in Computer and Information Science , no. : 354-368.
Urban livability is an important factor affecting the sustainable development of modern cities. Safe livability is an important part of urban livability. In view of this, this paper takes security as an example, and based on the actual data of Futian District, Shenzhen City, China, establishes a multi-agent simulation model of urban safe livability. The dynamic interaction feedback mechanism between decision-making behaviors of residents and urban safe livability under the influence of environment and policies has been explored, and residents’ decision-making simulation of the change of urban safe livability is realized. Finally, the main factors influencing urban safe livability are summarized through simulation conclusions. The research can not only provide scientific suggestions for improving the safe livability of Shenzhen, it also provides strong support for the sustainable development of the city.
Lihu Pan; Fenyu Yang; Feiping Lu; Shipeng Qin; Huimin Yan; Rui Peng. Multi-Agent Simulation of Safe Livability and Sustainable Development in Cities. Sustainability 2020, 12, 2070 .
AMA StyleLihu Pan, Fenyu Yang, Feiping Lu, Shipeng Qin, Huimin Yan, Rui Peng. Multi-Agent Simulation of Safe Livability and Sustainable Development in Cities. Sustainability. 2020; 12 (5):2070.
Chicago/Turabian StyleLihu Pan; Fenyu Yang; Feiping Lu; Shipeng Qin; Huimin Yan; Rui Peng. 2020. "Multi-Agent Simulation of Safe Livability and Sustainable Development in Cities." Sustainability 12, no. 5: 2070.