【阅】本周阅读摘选2024-06-17 → 2024-06-23

Posted by Cao Zihang on June 24, 2024 Word Count:
本周阅读摘选
2024-06-17 → 2024-06-23
目录

学术相关

An adaptive simulation based decision support approach to respond risk propagation in new product development projects1

Estimating digital product trade through corporate revenue data2

Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives3

EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities4

技术技巧

前端丨10个超好看的 404 页面

Python丨前端py-window-styles

为Python应用添加Windows风格UI样式

支持PySide/PyQt

应用预设样式极其方便

image-20240626173223602

Python丨itertools

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# 累加
itertools.accumulate

# 连接多个列表/迭代器
itertools.chain

# 多个迭代器的组合 (积)
itertools.product

# 基于T/F筛选
itertools.compress
itertools.filterfalse

# 基于T/F舍弃/保留元素
itertools.dropwhile
itertools.takewhile

# 分组
itertools.groupby

# 切片
itertools.islice

# 元素组合
itertools.combinations
itertools.combinations_with_replacement

# 元素排列
itertools.permutations

# 计数器
itertools.count

# 循环
itertools.cycle

# 类似于map函数
itertools.starmap

# 生成重复n次m元素的迭代器
itertools.repeat

# 构建迭代器副本
itertools.tee

# 长zip
itertools.zip_longest
  1. Liu, S., Ding, R., & Wang, L. (2024). An adaptive simulation based decision support approach to respond risk propagation in new product development projects. Decision Support Systems, 114270. https://doi.org/10.1016/j.dss.2024.114270 

  2. Stojkoski, V., Koch, P., Coll, E., & Hidalgo, C. A. (2024). Estimating digital product trade through corporate revenue data. Nature Communications, 15(1), 5262. https://doi.org/10.1038/s41467-024-49141-z 

  3. Gao, C., Lan, X., Li, N., Yuan, Y., Ding, J., Zhou, Z., Xu, F., & Li, Y. (2023). Large language models empowered agent-based modeling and simulation: A survey and perspectives (No. arXiv:2312.11970). arXiv. https://doi.org/10.48550/arXiv.2312.11970 

  4. Li, N., Gao, C., Li, M., Li, Y., & Liao, Q. (2024). EconAgent: Large language model-empowered agents for simulating macroeconomic activities (No. arXiv:2310.10436; Version 4). arXiv. https://doi.org/10.48550/arXiv.2310.10436