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今天小编为大家带来《区块链技术对供应链金融的影响
———基于三方博弈、动态演化博弈的视角》一文。
欢迎您的访问！
Share interests, spread happiness，
increase knowledge, and leave beautiful.
Dear, this is the LearingYard Academy!
Today, the editor brings the "
The impact of blockchain technology on supply chain finance-- Based on the perspective of three-party game and dynamic evolutionary game".
Welcome to visit！
1 内容摘要（Content summary）
今天小编将从“思维导图、精读内容、知识补充”三个板块，解读分享《区块链技术对供应链金融的影响—基于三方博弈、动态演化博弈的视角》一文的第三章中银行期望收益函数代码计算部分。
Today, I will read and share the part of the bank's expected return function code calculation in Chapter 3 of the article "The Impact of Blockchain Technology on Supply Chain Finance-Based on the Perspective of Three-Party Game and Dynamic Evolutionary Game" from the three sections of "Thinking Guide, Intensive Reading, and Knowledge Supplementation".
2 思维导图（Mind mapping）
3 精读内容（Intensive reading content）
3.1计算银行实施区块链技术时的期望收益函数
3.1 Calculating the Expected Benefit Function when Banks Implement Blockchain Technology
采用Mathematica软件根据上述两方动态演化博弈支付矩阵计算：
Mathematica software was used to calculate the payment matrix based on the above two-party dynamic evolutionary game:
3.2计算银行采用传统模式时的期望收益函数
3.2 Calculate the expected return function when the bank adopts the traditional model
采用Mathematica软件根据上述两方动态演化博弈支付矩阵计算，共分为以下两种情况：
Mathematica software is used to calculate the payment matrix based on the above two-party dynamic evolutionary game, which is divided into the following two cases:
1.δＬ－αＬ－αｉＬ≥０：
2.δＬ－αＬ－αｉＬ≥０：
4 知识补充（Knowledge supplement）
演化博弈中的复制动态方程可以用哪些软件进行计算？（What software can be used to compute the replicated dynamic equations in an evolutionary game? ）
1.MATLAB 和 Octave:MATLAB是一个强大的数值计算和可视化软件，适用于求解微分方程。Octave是一个与MATLAB兼容的开源软件，可以用于执行相似的数值计算。
1.MATLAB and Octave:MATLAB is a powerful numerical computation and visualization software for solving differential equations.Octave is an open source software compatible with MATLAB that can be used to perform similar numerical computations.
2.Python:使用Python的科学计算库，如NumPy和SciPy，可以进行数值计算和求解微分方程。使用Matplotlib或其他绘图库可以可视化结果。
2.Python:Numerical calculations and solving differential equations can be performed using Python's scientific computing libraries such as NumPy and SciPy. Results can be visualized using Matplotlib or other plotting libraries.
3.R:R语言是一种统计计算和图形化的语言，也可用于解决微分方程。包括deSolve包等可以用于求解微分方程的扩展包。
3.R:R is a statistical computing and graphing language that can also be used to solve differential equations. Extension packages that can be used to solve differential equations, such as the deSolve package, are included.
4.C++ 和 Fortran:对于更高性能的计算，你可以使用C++或Fortran编写求解微分方程的程序。一些数值计算库，如Boost和Eigen（对C++而言）或LAPACK（对Fortran而言），可以帮助实现高效的求解算法。
4. C++ and Fortran:For higher performance computing, you can write programs to solve differential equations in C++ or Fortran. Some numerical computation libraries, such as Boost and Eigen (for C++) or LAPACK (for Fortran), can help to implement efficient solving algorithms.
5.Mathematica 和 Maple:Mathematica和Maple是符号计算软件，它们可以用于解析求解微分方程。
5. Mathematica and Maple: Mathematica and Maple are symbolic computation programs that can be used to solve differential equations analytically.
6.Julia:Julia是一种高性能科学计算语言，可以用于求解微分方程，并具有易于学习和使用的语法。
6. Julia: Julia is a high-performance scientific computing language that can be used to solve differential equations and has an easy-to-learn and use syntax.
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参考资料：Dpeel翻译
参考文献：
楼永,常宇星,郝凤霞.区块链技术对供应链金融的影响——基于三方博弈、动态演化博弈的视角[J].中国管理科学,2022,30(12):352-360.
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文字|Wei
排版|Wei
审核|许江越