使用四叉树数据结构的选区划界现代方法
A Modern Approach to Electoral Delimitation using the Quadtree Data Structure
AI总结：
针对现有选区划界存在的效率低、不公正划分和议席人口比例不均等问题，提出基于四叉树数据结构的计算模型，通过递归细分地理空间优化人口标准，实现选区自动划分，在算法复杂度和边界可视化上表现高效。
摘要：
议会和立法机构选区的边界通过称为划界的过程来划定，该过程确保所有公民获得公平和平等的代表权。由于现有的法律和宪法规定，当前的划界工作存在诸多缺点，即效率低下、不公正划分（gerrymandering）以及议席与人口比例不均。现有方法为每个州分配议席，但对其在州内的实际形状和位置未作说明。本研究的主要目的是研究和分析现有划界算法的性能，并进一步提出一种具有优势的潜在解决方案，即使用基于四叉树数据结构的计算模型，通过优化目标人口标准来自动化选区划分过程。本文提出了一种使用四叉树数据结构的选举划界方法，该方法用于划分二维地理空间，通过以与节点关联的人口作为参数值，将其递归细分为四个象限或区域。四叉树利用地理空间的象限模式来表示选区，这不仅记录了已分配选区的数量，还保存了它们的位置特定信息。对所提出算法的性能进行了分析，并与现有技术进行了评估，结果表明，在算法复杂度和边界可视化方面，该算法是政治选区划分过程的高效解决方案。
英文摘要：
The boundaries of electoral constituencies for assembly and parliamentary seats are drafted using a process referred to as delimitation, which ensures fair and equal representation of all citizens. The current delimitation exercise suffers from a number of drawbacks viz. inefficiency, gerrymandering and an uneven seat-to-population ratio, owing to existing legal and constitutional dictates. The existing methods allocate seats to every state but remain silent about their actual shape and location within the state. The main purpose of this research is to study and analyse the performance of existing delimitation algorithms and further propose a potential solution, along with its merits, that involves using a computational model based on the quadtree data structure to automate the districting process by optimizing objective population criteria. The paper presents an approach to electoral delimitation using the quadtree data structure, which is used to partition a two-dimensional geographical space by recursively subdividing it into four quadrants or regions on the basis of population as a parameter value associated with the node. The quadtree makes use of a quadrant schema of the geographical space for representing constituencies, which not only keeps count of the allocated constituencies but also holds their location-specific information. The performance of the proposed algorithm is analysed and evaluated against existing techniques and proves to be an efficient solution in terms of algorithmic complexity and boundary visualisation to the process of political districting.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
