篇名 |
A Survey on Cloud Model
|
---|---|
並列篇名 | A Survey on Cloud Model |
作者 | Peng Sun、Ruizhe Zhang、Xiwei Qiu |
英文摘要 | To tackle the uncertainties in life, a model that can efficiently convert qualitative concepts and quantitative values is essential. This model is referred to as a qualitative-quantitative uncertainty model. The conventional membership function provides a fixed membership degree that is incompatible with the fuzziness and randomness of qualitative concepts when a certain element of the theoretical domain is inputted. To address this issue, Academician Li introduced the cloud model, which is a qualitative-quantitative uncertainty model created for converting between qualitative and quantitative values. Unlike the traditional membership function, the cloud model generates a set of random numbers with a stable tendency that better captures the fuzziness and randomness of the qualitative concept when an element of the theoretical domain is inputted. In this paper, the background and fundamental concepts of cloud models are initially presented. Afterwards, we delve into the advancements of cloud models in various fields such as controller, data mining, and reliability. Through these discussions, the paper showcases the significant role that cloud models can play in resolving qualitative and quantitative conversion issues across different domains. The three numerical characteristics of cloud models are then described in detail, as well as cloud generator, virtual cloud and other cloud model related algorithms. Finally, some statistical properties of cloud models are discussed, as well as the current problems and future research directions.
|
起訖頁 | 1159-1167 |
關鍵詞 | Fuzzy sets、Cloud model、Cloud generators、Conditional cloud、Virtual cloud |
刊名 | 網際網路技術學刊 |
期數 | 202309 (24:5期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
|
QR Code | |
該期刊 上一篇
| Security Threat Early Warning of Distance Education System Based on Blockchain |
該期刊 下一篇
| Multiscale Convolutional Attention-based Residual Network Expression Recognition |