Cloud model-clustering analysis based evaluation for ventilation system of underground metal mine in alpine region

Yan, Fang; Dong, Longjun; Huang, Rui; Cao, Rihong; Ge, Jike; Xu, Kaili

doi:10.1007/s11771-021-4646-5

Cited by 20 publications

(10 citation statements)

References 42 publications

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“…In the research on combining with other algorithms, Liu, Q. et al combined the standard genetic algorithm with the particle swarm algorithm, the improved algorithm is specially reserved for the excellent individuals, and the particle swarm algorithm further optimizes the excellent individuals; the experiment found that the combination of the two algorithms can effectively improve the performance of the algorithm [7]. Yan, F. et al proposed a new hybrid algorithm, the algorithm combines the genetic algorithm with the adaptive particle swarm algorithm and adjusts the selection strategy reasonably, at the same time, the operation operator of the genetic algorithm and the particle update rule of the adaptive particle swarm optimization algorithm are integrated, and the design method of the fitness function is improved; the experimental results show that the improved algorithm greatly improves the solution efficiency of the optimization problem [8].…”

Section: Literature Reviewmentioning

confidence: 99%

Mathematical Modeling Method of the Improved Genetic Algorithm for Random Power Fluctuation

Zhu

2022

International Transactions on Electrical Energy Systems

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In order to solve the problem that the traditional genetic algorithm has a slow search speed and is easy to fall into the local optimal solution, a mathematical modeling method of an improved genetic algorithm in random power fluctuation is proposed. Drawing on the idea of a genetic algorithm (GA) and using the randomness and stability trend of cloud droplets of the normal cloud model, the author proposes a new genetic algorithm, cloud genetic algorithm (CGA). CGA is implemented by the Y-condition cloud generator of the normal cloud model to realize the cross operation, and the basic cloud generator realizes the mutation operation. Finally, the power function optimization experiment and the IIR digital filter optimization design are carried out, and the standard GA, NQGA, CAGA, and LARES algorithms are carried out compared. The experimental results show that the IIR digital filter designed by CGA has the smallest maximum ripple (Ap) in the passband, which is 0.342, and the largest minimum attenuation (As) in the stopband, which is 34.27. It can be observed that the overall performance is better. The validity of the algorithm is proved, and it has a certain reference and application value.

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Section: Literature Reviewmentioning

confidence: 99%

Mathematical Modeling Method of the Improved Genetic Algorithm for Random Power Fluctuation

Zhu

2022

International Transactions on Electrical Energy Systems

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“…Li DY and others are the basis of cloud computing, reasoning, and control, and it is a model for the transformation of uncertainty between qualitative concepts and quantitative descriptions [27][28][29]. It is widely used in risk assessment, data mining, and performance evaluation and so on [30][31][32][33]. Let O be a quantitative set represented by a numerical value.…”

mentioning

confidence: 99%

Research on Measurement and Application of China’s Regional Logistics Development Level under Low Carbon Environment

Guo

et al. 2021

Processes

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To solve the problem of fuzziness and randomness in regional logistics decarbonization evaluation and accurately assess regional logistics decarbonization development, an evaluation model of regional logistics decarbonization development is established. First, the evaluation index of regional logistics decarbonization development is constructed from three dimensions: low-carbon logistics environment support, low-carbon logistics strength and low-carbon logistics potential. Second, the evaluation indexes are used as cloud model variables, and the cloud numerical characteristic values and cloud affiliation degrees are determined according to the cloud model theory. The entropy weight method is used to determine the index weights, and the comprehensive determination degree of the research object affiliated to the logistics decarbonization level is calculated comprehensively. Finally, Beijing-Tianjin-Hebei region is used as an example for empirical evidence, analyzing the development logistics decarbonization and its and temporal variability in Beijing, Tianjin and Hebei provinces and cities. The results of the study show that the development logistics decarbonization in Beijing, Tianjin and Hebei Province has been improved to different degrees during 2013–2019, but the development is uneven. Developing to 2019, the three provinces and cities of Beijing, Tianjin and Hebei still have significant differences in terms of economic environment, logistics industry scale, logistics industry inputs and outputs, and technical support.

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“…It is based on the uncertainty (randomness and fuzziness) of a human-defined concept and describes the connotation of an uncertain concept quantitatively through three digital characteristics [18]: Ex (Expectation), En (Entropy), and He (Hyper-Entropy). To date, the cloud model has been widely applied in many aspects, solving decision-making programs associated with various uncertainties [19][20][21][22][23], evaluation of water resources' carrying capacity [24], or classification and clustering [25,26]. It is also applied in the research of spatiotemporal distribution of random variables in many places in China.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Distribution of Drought Based on the Standardized Precipitation Index and Cloud Models in the Haihe Plain, China

Zhang

Anderson

et al. 2022

Water

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The Haihe Plain is the largest component of the agriculturally vital North China Plain, and it is characterized by serious water shortage and frequent droughts, which lead to crop reduction and have adverse effects on agriculture and ecology. We used daily precipitation data from 1955–2017; the region’s spatiotemporal characteristics of drought were analyzed by using the standardized precipitation index (SPI), drought probability, and Mann–Kendall test for seasonal scale including two main crops growth seasons for the region’s main crops. Furthermore, a cloud algorithm model was established to analyze the dispersion and instability of the SPI. The annual drought frequency is 28.57%; the SPI for spring has an increasing tendency, while summer shows a significant decreasing trend (p < 0.05); the Haihe Plain has had a tendency towards drought over the last 63 years. The SPI in northwest is the smallest and increases gradually toward the south; the severity of drought in dry years increased from southeast to northwest. The cloud model shows that the SPI randomness of each site decreased significantly and tended to be stable and uniform. The deterministic and stable SPI of each station is stronger in dry years, and the randomness and instability are stronger in wet years. The inter-annual differences of the characteristic values of the SPI cloud model are bigger than the differences among sites, and the inter-annual randomness and inhomogeneity of the SPI are higher.

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Cloud model-clustering analysis based evaluation for ventilation system of underground metal mine in alpine region

Cited by 20 publications

References 42 publications

Mathematical Modeling Method of the Improved Genetic Algorithm for Random Power Fluctuation

Mathematical Modeling Method of the Improved Genetic Algorithm for Random Power Fluctuation

Research on Measurement and Application of China’s Regional Logistics Development Level under Low Carbon Environment

Spatiotemporal Distribution of Drought Based on the Standardized Precipitation Index and Cloud Models in the Haihe Plain, China

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