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In bygone days, the way to deal with traditional villages in developing new cities in China was often to overturn them and replace the original environment with the built-up urban environment, causing constructive destruction to the traditions and cultures. According to the new village transformation requirements, the planning and construction of villages must be shaped with their own cultural and humanistic characteristics of the habitat requirements. It does not favor demolishing large constructions by implementing a different environment. A traditional village is an essential spatial framework to retain the "mark" of the local characteristics of the new city. It can be an essential element in shaping the individual characteristics of the village by realizing the diversity of spatial forms and regional cultural connotations of the new village. Therefore, this paper proposes a new village transformation model based on traditional villages' social, economic, and spatial patterns, combined with a new particle swarm optimization (PSO) algorithm named multi-objective particle swarm optimization (MOPSO). The model transforms the village based on the required optimum resource allocation with the global solution. The experiment shows that the proposed model suits village renovation and modernization. The work is a step toward the advancements and betterment of rural development. [ABSTRACT FROM AUTHOR]

The continuation of human civilization is inseparable from the development and construction of rural areas, and infrastructure is the core of rural development. China has been building large-scale rural infrastructure in recent years. Rural infrastructure building, for example, is huge in both quantity and scope, but it is beset by challenges in its current construction and development, and it urgently requires suitable leadership. Planning assessment, as a technical method, can identify problems in regional development and is a powerful tool for evaluating the impact of planning and construction and promoting the development of complete new areas. This paper is aimed at the planning evaluation of rural construction and the evaluation of rural construction and guides the planning and implementation of the next step of rural construction, to assist China's supervision and inspection of rural construction effect and promote rural construction and development into a good track. In view of the low accuracy and efficiency of the current evaluation model of rural planning and the problem that a single neural network easily produces local extreme value, the neural network method is improved, and the application of LM-BP neural network in the evaluation model of rural planning is proposed. Input sample elements are five factors affecting rural construction, including industrial construction, population distribution, and utilization rate of large-scale facilities, construction of public facilities, and promotion effect of supporting policies. Output sample is the evaluation result. On this foundation, the LM-BP neural network was used to convert the training into a least square problem, and the LM method was used to redefine the number of hidden layer nodes, resulting in the construction of a rural planning evaluation model based on the LM-BP neural network. This approach is used to determine the outcomes of rural planning evaluations. The experimental results show that the designed evaluation model has a small evaluation error, has the advantage of high accuracy compared with similar models, and is a reliable evaluation model for rural planning. [ABSTRACT FROM AUTHOR]

Based on the background of the reconstruction project from Changqing Chenzhuang-Pingyin section of G220 east-deep line in China, a special tunnel structure and construction plan was carried out according to the construction measures of the shallow-buried small spacing tunnel passing underneath cultural relic buildings, and a comprehensive deformation control scheme of "CRD construction method single-arm excavation + surface grouting prereinforcement + advanced large pipe shed presupport" was put forward. The results of numerical simulation and on-site construction monitoring showed that the overall deformation of aqueduct foundation generally increases first, then decreases and increases again, and finally tends to be stable. The effects of surface grouting prereinforcement and advance large pipe shed presupport are obvious. The comprehensive deformation control scheme can ensure the safety of the existing construction and meet the safety prevention and control requirements. [ABSTRACT FROM AUTHOR]

Since the financial crisis in 2008, innovation has gradually become the orientation of global economic development and the strategic choice for China's urban development. With the transformation of the urban development mode from factor-driven and capital-driven to innovation-driven, many innovation spaces have begun to emerge in cities, which attract academic attention. A large number of studies on the relation between innovation activities and geographic space mainly focus on the phenomena at the regional level, and the city is only regarded as a target of innovation activities agglomeration. The study on the distribution of innovation space within the city is insufficient. In particular, there is a lack of studies on the spatial-temporal evolution of urban innovation space distribution. However, the study on the spatial-temporal evolution characteristics of urban innovation space distribution can provide planning countermeasures for the construction of innovative cities in China. Taking Nanjing as an empirical area, the spatial-temporal evolution of urban innovation space distribution was studied through methods such as average nearest neighbor, standard deviational ellipse, kernel density estimation, and exploratory spatial data analysis based on the data of high-tech enterprises identified from 2008 to 2019. The results showed the following: (1) the distribution of urban innovation space has significant spatial agglomeration characteristics, and the degree of agglomeration continued to rise; (2) regardless of the macro- or microperspective, the distribution of urban innovation space has shown the characteristic of diffusion at the initial, but the trend of polarization in recent years is significant; and (3) the distribution of urban innovation space exhibited diverse agglomeration modes and evolution trends in different regions, and it can be divided into three categories: grouped, banded, and scattered. [ABSTRACT FROM AUTHOR]