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Policy Scenario Cellular Automata/证据
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Policy Scenario Cellular Automata

Policy Scenario Cellular Automata (PSCA) combines cellular automata simulation with structured scenario analysis to evaluate how alternative policy decisions reshape spatially distributed systems over time. Each scenario encodes a different set of transition rules or constraints, and the model iterates to reveal divergent spatial outcomes — enabling direct, visual comparison of policy consequences at the local and system level.

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源记录

引文逐字复制自方法源记录。这些引文不代表任何层级的验证。

Policy Scenario Cellular Automata — Scenario-driven grid-based simulation for policy impact analysis
分类方法记录 · process-pipeline / simulation
  • Clarke, K. C., Hoppen, S., & Gaydos, L. (1997). A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, 24(2), 247–261. · DOI 10.1068/b240247
  • Batty, M. (2005). Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. MIT Press. ISBN 978-0262025836. · ISBN 978-0262025836
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Same method familyAgent-Based Modelingmachine-suggested · Relational suggestion, not evidence.Same method familyCellular Automatamachine-suggested · Relational suggestion, not evidence.Same method familyDiscrete-Event Simulationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPolicy Scenario Analysismachine-suggested · Relational suggestion, not evidence.Same method familySystem Dynamicsmachine-suggested · Relational suggestion, not evidence.

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