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assignmentutor-lab™ 为您的留学生涯保驾护航 在代写运筹学operational research方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写运筹学operational research代写方面经验极为丰富，各种代写运筹学operational research相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• Advanced Probability Theory 高等概率论
• Advanced Mathematical Statistics 高等数理统计学
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|运筹学作业代写operational research代考|Three-Way Decisions Based on the S-VULVs

By using the LF based on S-VULVs, we explore algorithm which contains the following steps for examining the $3 \mathrm{WD}$ rules. Basically, these explorations that Combination the LF based on S-VULVs and the 3WD for S-VULVs are also presented in this section. For solving this algorithm, we have revised the information about actions and state and related to probability vectors, which is stated by $A_{A C}=$ $\left{\chi_{P_{A C}}, \chi_{B_{A C}}, \chi_{N_{A C}}\right}, \Omega_{S}=\left{\mathcal{F}{B}, \sim \mathcal{F}{B}\right}$ and $\mathcal{D}=\left{\operatorname{Pr}\left(\mathcal{F}{B} \mid[\mathrm{r}]\right), \operatorname{Pr}\left(\sim \mathcal{F}{B} \mid[\mathrm{r}]\right)\right}$ with a condition that is $\operatorname{Pr}\left(\mathcal{F}{B} \mid[r]\right)+\operatorname{Pr}\left(\sim \mathcal{F}{B} \mid[r]\right)=1$. Then the steps of the algorithm are summarized as follows:
Step 1: By using the equations of Table 2, we examine the LFs.
Step 2: By using Eq. (55), we aggregate the decision matrix which is constructed by decision experts.

Step 3: By using Eqs. (34), (35), and (36), we examine the expected losses $Y_{E L}\left(\chi_{j_{A C}} \mid[r]\right), j=P, B, N .$
Step 4: By using Eqs. (37), (38), and (39), we examine the expected values.
When the expected values if failed to find the relationships between any two expected losses. For these kinds of issues, we explore the notions of accuracy function, which are stated in Eqs. (40), (41), and (42).

Step 5: By using Eq. (43), Eq. (44), and Eq. (45), we examine the three-way decision rules.
Step 6: The end.

## 统计代写|运筹学作业代写operational research代考|Neutrosophic Sets

A neutrosophic set (NS) $A$ on the universe of discourse $X$ is expressed as follows:
$$A=\left{\left\langle x, T_{A}(x), I_{A}(x), F_{A}(x)\right\rangle: x \in X\right}$$
where $\left.T_{A}, I_{A}, F_{A}: X \rightarrow\right]^{-} 0,1^{+}\left[\right.$and ${ }^{-} 0 \leq T_{A}(x)+I_{A}(x)+F_{A}(x) \leq 3^{+}[12]$.
Note that the image of an element in $\mathrm{NS}$ is a standard or non-standard subsets of $]^{-} 0,1^{+}$. In some practical applications, standard or non-standard subsets of ]$^{-} 0,1^{+}[$may not be easy modeling of problems. Therefore the concept of singlevalued neutrosophic set (SVN-set) was introduced by Wang et al. [15] as follows.
Let $X$ be a non-empty set and generally its element is denoted as $x$. A singlevalued neutrosophic set ( $S V N$-set) $A$ is identified by three functions $T_{A}, I_{A}$, and $F_{A}$ from $X$ to $[0,1]$ and they called as truth-membership, indeterminacy-membership, falsity-membership functions, respectively. Formally, $X$ may be continuous or discrete.

• If $X$ is continuous, representation of an $S V N$-set $A$ is expressed as follows:
$$A=\int_{X}\left\langle T_{A}(x), I_{A}(x), F_{A}(x)\right\rangle / x, \text { for all } x \in X$$
• If $X$ is a crisp set, an $S V N$-set $A$ can be written as follows:
$$A=\sum_{x}\left\langle T_{A}(x), I_{A}(x), F_{A}(x)\right\rangle / x, \text { for all } x \in X$$
Here $0 \leq T_{A}(x)+I_{A}(x)+F_{A}(x) \leq 3$ for all $x \in X$.

## 统计代写|运筹学作业代写operational research代考|Three-Way Decisions Based on the S-VULVs

$\operatorname{Pr}(\mathcal{F} B \mid[r])+\operatorname{Pr}(\sim \mathcal{F} B \mid[r])=1$. 然后算法的步骤总结如下:

## 统计代写|运筹学作业代写operational research代考|Neutrosophic Sets

$\backslash$ left 的分隔符缺失或无法识别

• 如果 $X$ 是连续的，表示一个 $S V N$-放 $A$ 表示如下:
$$A=\int_{X}\left\langle T_{A}(x), I_{A}(x), F_{A}(x)\right\rangle / x, \text { for all } x \in X$$
• 如果 $X$ 是一个清晰的集合，一个 $S V N$-放 $A$ 可以写成如下:
$$A=\sum_{x}\left\langle T_{A}(x), I_{A}(x), F_{A}(x)\right\rangle / x, \text { for all } x \in X$$
这里 $0 \leq T_{A}(x)+I_{A}(x)+F_{A}(x) \leq 3$ 对所有人 $x \in X$.

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

assignmentutor™您的专属作业导师
assignmentutor™您的专属作业导师