Digital Cities Roadmap. Группа авторов

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       Neural Networks—A semi-supervised technique for classification and regression, the Neural networks. Neural Nets is a computing device consisting of highly interrelated processing elements that process data via their dynamic state response. Back Propagation is one of the best-known algorithms in the neural network. Neural networks have few challenges for big data with the growing scale of information. The huge quantity of information makes it difficult for the technique to maintain both reliability and efficiency and also increases the system operating load.

      Resilience can be described as an ability to reach a desired level of reliability or provide a desired level of service or features in the physical systems, Q, immediately after a risk arises.

       1.4.1 Sustainability and Resiliency Conditions

      Most societies choose to be resilient and sustainable [50]. When priorities and plans are formulated separately in order to enhance resilience and sustainability, there are strong risks that the targets may overlap and may also clash. This chapter looks at the principles of safe and durable cities, how increasing environmental and constructed environments and stressors will need different approaches and resources to improve stability and longevity for the environment.

      When their resilience and sustainable strategies align themselves, the best results for communities occur. However, sustainable and resilient advancement must be accomplished before promising future generations are delivered. Challenges include reduction of impacts on environmental systems, management and the time it takes to change current practices and replace existing infrastructure with standard renewal rates. Nevertheless, while the governance potential and sustainability and adaptation strategies are open, intergenerational wealth is undermined by expectations that natural environments (our atmosphere, habitats, and climate) are secure and healthy [1620]. Introduction to sustainability and the resilience of buildings, the dynamic nature of natural systems has not been fully understood through their intricate interrelationships across time and space and their preference for inclination points and threshold values. Many experts face the challenge of developing dangerous model infrastructure that does not involve potential improvements in risk magnitude or frequency, because scientific consensus is not yet formed on this topic. In fact, today’s construction methodology does not take into consideration the harm rates and related impacts on building operation recovery—a critical aspect of resilience.

       1.4.2 Paradigm and Challenges of Sustainability and Resilience

Bar chart depicts natural hazard year wise in US.

      Figure 1.1 Natural hazard year wise in US.

      Natural disasters will affect societies by human loss, relocation, death, property harm and economic impacts. Such consequences and sluggish group rebounder may be amplificated by structural stressors like high unemployment, inadequate services or food shortages. The National Environmental Awareness Centers (NOAA, 2018a) report that 218 extreme weather events happened in the USA between 1980 and 2017 worth at least $1 billion. The degree to which societies have been affected and lost their work from natural disasters is seen in Figure 1.1. The enhancement of construction and infrastructure’s robust and sustainable efficiency will help cities escape major economic loss and long-term consequences.

       1.4.3 Perspectives of Local Community

      There are a number of communities in the United States which recover each year from a dangerous event. Over the last 50 years, an annual average of 40 declarations of presidential hazardous events has been issued (FEMA 2013). Hazardous results are first experienced and first handled in populations. While governments cannot eliminate natural threats, long-term planning and prioritized initiatives that are enforced over time will mitigate their effects. The level of recovery and the eventual outcome would rely on the scope and magnitude of the incident and on the action taken by government to mitigate harm, preserve properties, react in a timely and organized manner and restore government functionality within a given time period. Such activities collectively assess the strength of a group.

      Resilience provides a holistic solution to risk handling catastrophic incidents, as well as environmental problems, through structures that allow new generations the same opportunities to prosper. Communities will move for a more socially and economically equitable and prosperous environment by resolving skill differences and essential threats through a systemic integrated and systematic strategy [2935]. Approaches include: introduction into City planning and network projects with adaptability, resilience and regeneration, utilizing a framework methodology that tackles multi-scale connections and dependency and methodologies that resolve the complexity of the potential severity of hazards (Table 1.2).

      Table 1.2 Planning for community resilience [55].

Planning steps Key activities
1. Form a collaborative Planning Team Identify resilience leader for the communityIdentify team members, and their roles and responsibilitiesIdentify key public and private stakeholders for all phases of planning and implementation
2. Understand the situation Social DimensionsIdentify and characterize functions and dependencies of social institutions, including business, industry, and financial
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