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城市模型的回顾与展望—访谈Michael Batty(下)

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2015-08-17

I=采访者

刘伦  剑桥大学土地经济系博士研究生



龙瀛  北京市城市规划设计研究院高级工程师,城市规划工学博士,剑桥大学国家公派访问学者


 

B=Mike Batty 

英国皇家科学院院士,英国伦敦大学学院(UCL)巴特莱特规划学院教授

高级空间分析中心(Centre for Advanced SpatialAnalysis)主任


 

 

I: As you mentioned in our previous seminar, cities are becoming more complex so fast that it poses a major challenge for urban simulation. How do you think can we tackle with this challenge? To develop models in small pieces, and on different levels of sophistication, or other approaches?

您在此前的研讨会上曾经提到,城市模拟面临的一项主要挑战是城市的复杂性正在快速提高,您认为我们应如何应对这项挑战?是构建针对特定问题或领域的模型,还是构建一系列不同复杂度的模型,还是其他途径?

 

B: That is a very good question. The cities are becoming more complex, faster than our ability to keep up with them. I think we can tackle it certainly, and we are tackling it. And there is the move to get better and better data, the move to actually develop different sorts of models of the system. Models by their very nature are simple and they have to be. That is the definition of model. They have to be relatively simple or pick out certain aspects, which are important to the complexity. So if things are getting more complex, there might be more aspects to pick out, to embody in one or more models. So that has to be an issue.

这是个很好的问题。我认为我们可以解决这个问题,而且我们已经正在解决,我们正在通过各种方式提高数据质量,也正在扩展模型的种类。模型的本质是追求简单的,它们必须如此,因为这正是模型的定义。所以,如果模拟对象变得更加复杂,模型可能就需要将模拟对象划分为更多方面。

 

Developing models in small pieces, yes. I think that is a reasonably good strategy. That is not in line with what I was saying earlier on that some of the newer models are from a problem perspective and are picking the best and the most appropriate from these other main-style models. And building them on different levels of sophistication, yes. I think all of those things are things that need to be done in terms of dealing with complexity.

开发模型和不同复杂度的模型是相当好的策略。我认为这些都是应对日益提高的复杂性所需的工作。

 

The other issue, of course, is that our ability to predict is on the extreme scrutiny. It is under a lot of attention. It is quite clear we sort of know that we can’t predict the future, but we are trying to predict conditionally. And this I think is we’ve yet to get to grips with what prediction means in social systems. We are learning a lot at present time about predictability. And I think there are some other things happening too. We are getting more opportunities to experiment in cities, in limited kinds of ways, because things can be done in a very short term and make an impact and can see how population respond. So I think there are some new opportunities being posed by information technology on this, by the

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