标题： 伊朗及邻国创新模式的测量：使用STL和动态时间规整的时间序列相似性方法 显示英文标题

标题： Measuring Innovation Patterns in Iran and Neighboring Countries: A Time Series Similarity Approach Using STL and Dynamic Time Warping

摘要： 创新正变得越来越重要，成为国家发展战略的关键因素，但衡量和比较各国的创新表现仍然是一个方法论上的挑战。 这项研究设计了一种新的时间序列相似性方法，将季节性-趋势分解（STL）与快速动态时间规整（DTW）相结合，通过与地区同行的比较来研究伊朗的创新趋势。 由于全球创新指数数据的数据可用性限制，研究中使用研发支出占GDP的比例作为代理指标，并明确指出其局限性。 基于世界银行指标和基于自动编码器的缺失值填补技术，研究比较了国与国之间的相似性，并确定了与伊朗创新路径最契合的主题领域。 研究结果表明，贫困和健康指标与伊朗的研发支出表现出最强的统计相似性，而沙特阿拉伯、阿曼和科威特显示出最相似的国家间接近度。 启示在于，伊朗的创新更内在地与社会发展动态相关，而不是传统的经济或基础设施驱动因素，这对STI政策具有区域特定的意义。 显示英文摘要

摘要： Innovation is becoming ever more pivotal to national development strategies but measuring and comparing innovation performance across nations is still a methodological challenges. This research devises a new time-series similarity method that integrates Seasonal-Trend decomposition (STL) with Fast Dynamic Time Warping (DTW) to examine Irans innovation trends by comparison with its regional peers. Owing to data availability constraints of Global Innovation Index data , research and development spending as a proportion of GDP is used as a proxy with its limitations clearly noted. Based on World Bank indicators and an Autoencoder based imputation technique for missing values, the research compares cross-country similarities and determines theme domains best aligned with Irans innovation path. Findings indicate that poverty and health metrics manifest the strongest statistical similarity with R and D spending in Iran, while Saudi Arabia, Oman, and Kuwait show the most similar cross country proximity. Implications are that Iranian innovation is more intrinsically connected with social development dynamics rather than conventional economic or infrastructure drivers, with region-specific implications for STI policy.