Narrow Results

Urban Park green space is an essential carrier and form of urban recreation space, playing an important role in improving the ecological environment and enhancing the image of the city. With the process of urbanization and the continuous improvement of residents’ living standards, urban park construction has become increasingly important to meet people’s growing needs for a better life. However, the evaluation indicators for urban park green space in China mostly consider macroscopic levels, such as the area, number and per capita green area of parks. This cannot fully reflect the level of park green space services. Accessibility can reflect the convenience of residents to reach the park, provide guidance for the reasonable layout of parks and have various evaluation methods relying on geographic information technology. Therefore, it is necessary to quantitatively study the layout and accessibility of park green space. Taking the central urban area of Nanjing as the research object, this paper summarizes existing research and focuses on evaluating the accessibility of park green space while analyzing the layout of parks from multiple perspectives, combined with the existing pressure appraisal of park green space services. Relevant data on Nanjing, including overall planning and statistical yearbooks, were collected and analyzed using geographic information system (GIS) tools, network analysis and Thiessen polygon theory to analyze the service pressure, demand and accessibility of park green space in the central urban area under different transportation methods. Based on the results, targeted optimization strategies are proposed.

Expansion of renewable energy development causes concerns which traditional land-use planning may have limited capacity to address adequately. The complexity and multiplicity of scales, criteria and actors involved in decision-making processes requires a holistic approach that captures the variety in stakeholder interests. Reaching consensus across interests ensures democratic and cost-effective decision-making processes. The Consensus-based Siting (ConSite) tool suite was developed for optimal siting of onshore wind-power plants and routing of high-voltage power lines considering stakeholder interests. ConSite is based on the operational steps of spatial multi-criteria decision analysis using a bottom-up holistic approach. Its spatially explicit graphical user interface allows for a high level of stakeholder involvement and includes inherent capabilities of scenario modelling. ConSite thereby helps to structure decision problems, balance conflicting interests and identify relevant decision strategies based on risk assessment and trade-off analysis. ConSite visualises the spatial consequences of implementing various decision strategies and balancing site-specific conflict levels with energy production potential.

In classical artificial intelligence and machine learning fields, the aim is to teach a certain program to find the most convenient and efficient way of solving a particular problem. However, these approaches are not suitable for simulating the evolution of human intelligence, since intelligence is a dynamically changing, volatile behavior, which greatly depends on the environment an agent is exposed to. In this paper, we present several models of what should be considered, when trying to simulate the evolution of intelligence of agents within a given environment. We explain several types of entropies, and introduce a dominant function model. By unifying these models, we explain how and why our ideas can be formally detailed and implemented using object-oriented technologies. The difference between our approach and that described in other papers also — approaching evolution from the point of view of entropies — is that our approach focuses on a general system, modern implementation solutions, and extended models for each component in the system.