# Fuzzy Weighted Clustering Method for Numerical Attributes of Communication Big Data Based on Cloud Computing

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## Abstract

**:**

## 1. Introduction

## 2. Numerical Attribute Sampling and Feature Parameter Extraction of Communication Big Data

#### 2.1. Communication Big Data Numerical Attribute Multi-Dimensional Text Feature Data Sampling

#### 2.2. Communication Big Data Numerical Attribute Linear Programming Processing

## 3. Big Data Fuzzy Weighted Clustering Optimization

## 4. Simulation Experiment Analysis

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 10.**Comparison results of three methods of average energy consumption for successful transmission of a single packet.

Parameter Name | Description or Value |
---|---|

Total node value | 400 |

Spacing between nodes | 50‒100 m |

Queue control | Optimize queue |

Experimental wireless channel model | MICAZE |

Experimental time | Longest 900 s |

Experimental range | 1000 × 1000 m |

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## Share and Cite

**MDPI and ACS Style**

Ding, H.; Sun, C.; Zeng, J.
Fuzzy Weighted Clustering Method for Numerical Attributes of Communication Big Data Based on Cloud Computing. *Symmetry* **2020**, *12*, 530.
https://doi.org/10.3390/sym12040530

**AMA Style**

Ding H, Sun C, Zeng J.
Fuzzy Weighted Clustering Method for Numerical Attributes of Communication Big Data Based on Cloud Computing. *Symmetry*. 2020; 12(4):530.
https://doi.org/10.3390/sym12040530

**Chicago/Turabian Style**

Ding, Haitao, Chu Sun, and Jianqiu Zeng.
2020. "Fuzzy Weighted Clustering Method for Numerical Attributes of Communication Big Data Based on Cloud Computing" *Symmetry* 12, no. 4: 530.
https://doi.org/10.3390/sym12040530