Comprehensive Evaluation of the Stability of Coal Mining Subsidence Based on Fuzzy Matter-Element Theory

Liu, Wen Sheng; Li, Fan Yue; Guo, Xian Tao

doi:10.4028/www.scientific.net/amr.361-363.241

Cited by 2 publications

(2 citation statements)

References 1 publication

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“…In the Water 2023, 15, 2507 9 of 25 evaluation of matter-element, the commonly used matter-element correlation function R = (N, c, v) is used, where R is the basic element; N, c, and v are matter elements, which represent the object, the features of the object, and the quantitative values of the object related to those features. When an object possesses non-single properties or features, a multidimensional matter element is used for representation [64].…”

Section: (2) Matter-element Theorymentioning

confidence: 99%

Evaluation of Water Network Construction Effect Based on Game-Weighting Matter-Element Cloud Model

Zhang

Huang

et al. 2023

Water

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Water network construction is one of the important ways to solve complex water problems at present. It is crucial for the optimal allocation of water resources, flood control, disaster reduction, protection of water ecology, water security, and sustainable urban development. Accordingly, this study formulates an index system for assessing the efficacy of water network construction based on the Driving Force–Pressure–State–Influence–Response (DPSIR) model, taking into account the four dimensions of optimal allocation of water resources, flood control and disaster reduction in river basins, protection of water ecosystems, and intelligent water network management. The proposed index system comprises four key aspects, which are utilized to evaluate the effectiveness of water network construction efforts. Then, the game-weighting method and the matter-element extension method improved by the cloud theory established an evaluation model to evaluate and compare the water network construction effects of the two cities in Henan Province. Finally, the GM (1,1) model was used to evaluate the water network construction effects, and future trends were predicted. The results show the following: (1) On the whole, the effect of water network construction in the two cities is constantly improving; (2) There has been a significant improvement in the intelligent management of water networks. The main reason for this result is that the “Internet +” has promoted the intelligent construction of water networks; (3) The water ecological environment, flood control, and drainage capabilities continued to improve, which has largely guaranteed the basic security bottom line of urban development space; (4) The advancement and utilization of water resources has undergone gradual improvements over time, with key impact metrics centered on water supply safety factors and the development and utilization of water resources. As water supply sources continue to diversify, it is expected that the aforementioned situation will be ameliorated in the future; (5) The predicted value shows that the water network construction of the two cities can basically meet the planned value of each index when the water network construction reaches the planning level. This paper provides help to promote the sustainable use of water resources and ensure the sustainable development of cities.

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Section: (2) Matter-element Theorymentioning

confidence: 99%

Evaluation of Water Network Construction Effect Based on Game-Weighting Matter-Element Cloud Model

Zhang

Huang

et al. 2023

Water

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“…Guo et al (2019) proposed an evaluation model of a goaf expressway with seven evaluation factors based on fuzzy theory, calculated the factor weight by gray correlation method, and applied the model to Wuyun Expressway to prove the reliability of the model. Liu et al (2011) proposed a fuzzy matter-element model which used the AHP and matter-element extension method to identify the risk level of goaf zones. Maria et al (2013) used the calculation method based on material resistance to analyze the sensitivity of goaf roof stability to the variation of roof material properties.…”

Section: Introductionmentioning

confidence: 99%

A novel evaluation method of mining goaf ground activation under high-speed railway load

Ren

He²,

Zou³

et al. 2022

Front. Earth Sci.

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With the continuous improvement of infrastructure, some high-speed railway lines will inevitably cross the goaf ground, and there is less research on the safety of high-speed rail construction in goaf ground. To make a reasonable and accurate safety evaluation of the high-speed railway construction in the mine goaf ground, machine learning combined with numerical simulation is used to evaluate the safety depth of goaf under the impact of high-speed railway load. An optimal algorithm is selected among BP, RBF, and PSO-RBF neural networks based on the accuracy of the predicted height of a caving fracture zone. Numerical models for simulating high-speed railway founded on goaf are set up using the commercial software package FLAC3D, where factors such as subgrade height, train speed, and axle load are investigated in terms of train load disturbance depth and the extent of the caving fracture zone. The results indicate that the PSO-RBF neural network has an error of 2.76% in predicting the height of the caving fracture zone; the depth of train load disturbance is linearly related to the axle weight and roadbed height but is a sinusoidal function of the train speed. Based on the numerical simulation results, a formula for calculating the depth of train load disturbance is proposed, which provides a certain reference value for the construction of high-speed railways in the goaf ground.

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Comprehensive Evaluation of the Stability of Coal Mining Subsidence Based on Fuzzy Matter-Element Theory

Cited by 2 publications

References 1 publication

Evaluation of Water Network Construction Effect Based on Game-Weighting Matter-Element Cloud Model

Evaluation of Water Network Construction Effect Based on Game-Weighting Matter-Element Cloud Model

A novel evaluation method of mining goaf ground activation under high-speed railway load

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