scholarly journals Risk Early Warning Evaluation of Coal Mine Water Inrush Based on Complex Network and Its Application

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yanhui Li ◽  
Jianbiao Bai ◽  
Wei Yan ◽  
Xiangyu Wang ◽  
Bowen Wu ◽  
...  
Keyword(s):  
Coal Mine ◽  
Early Warning ◽  
Evaluation System ◽  
Evaluation Model ◽  
Water Inrush ◽  
Geological Structure ◽  
Assessment System ◽  
General Level ◽  
Mining Conditions ◽  
Complex Dependence

As one of the five major coal mine disasters, the water inrush disaster poses a serious threat to the safety of the country and people, so the prevention work for that becomes very important. However, there is no perfect assessment system that can better solve the complex dependence relationships among disaster-causing factors of water inrush disasters. This study applied the knowledge of Complex Networks to research water inrush disaster, and based on that, the early warning evaluation system that combined ANP and Cloud model was established in order to solve the complex dependence problem and prevent the occurrence of water inrush. Moreover, this evaluation model was applied to the example Y coal mine to verify its superiority and feasibility. The results showed that the main cloud of goal was located at the yellow-strong warning level, and the first-level indicators were, respectively, at that the yellow-strong level of mining conditions, the yellow-strong warning level of hydrological factors, between the yellow-strong warning level and purple-general level of the geological structure, and among the blue-slightly weak warning level, purple-general level, and yellow-strong level of the human factor. The prediction results were consistent with the actual situation of the coal water inrush disaster in Y mine, which further proved that this early warning evaluation model is reliable. In response to the forecast results, the authors put forward relative improvements necessary to strengthen the prevention ability to disaster-causing factors among hydrological factors, mining conditions, and geological structure, which should comprehensively increase knowledge, technology, and management of workers to avoid leaving out disaster-causing factors. Meanwhile, the warning evaluation model also provides the relevant experience basis for other types of early warning assessment networks.

scholarly journals Multistage identification method for real-time abnormal events of streaming data

2019 ◽  
Vol 15 (12) ◽  
pp. 155014771989454
Author(s):  
Hao Luo ◽  
Kexin Sun ◽  
Junlu Wang ◽  
Chengfeng Liu ◽  
Linlin Ding ◽  
...  
Keyword(s):  
Real Time ◽  
Coal Mine ◽  
Early Warning ◽  
Sliding Window ◽  
Geological Structure ◽  
Streaming Data ◽  
Event Monitoring ◽  
Monitoring Method ◽  
Identification Method ◽  
Abnormal Events

With the development of streaming data processing technology, real-time event monitoring and querying has become a hot issue in this field. In this article, an investigation based on coal mine disaster events is carried out, and a new anti-aliasing model for abnormal events is proposed, as well as a multistage identification method. Coal mine micro-seismic signal is of great importance in the investigation of vibration characteristic, attenuation law, and disaster assessment of coal mine disasters. However, as affected by factors like geological structure and energy losses, the micro-seismic signals of the same kind of disasters may produce data drift in the time domain transmission, such as weak or enhanced signals, which affects the accuracy of the identification of abnormal events (“the coal mine disaster events”). The current mine disaster event monitoring method is a lagged identification, which is based on monitoring a series of sensors with a 10-s-long data waveform as the monitoring unit. The identification method proposed in this article first takes advantages of the dynamic time warping algorithm, which is widely applied in the field of audio recognition, to build an anti-aliasing model and identifies whether the perceived data are disaster signal based on the similarity fitting between them and the template waveform of historical disaster data, and second, since the real-time monitoring data are continuous streaming data, it is necessary to identify the start point of the disaster waveform before the identification of the disaster signal. Therefore, this article proposes a strategy based on a variable sliding window to align two waveforms, locating the start point of perceptual disaster wave and template wave by gradually sliding the perceptual window, which can guarantee the accuracy of the matching. Finally, this article proposes a multistage identification mechanism based on the sliding window matching strategy and the characteristics of the waveforms of coal mine disasters, adjusting the early warning level according to the identification extent of the disaster signal, which increases the early warning level gradually with the successful result of the matching of 1/ N size of the template, and the piecewise aggregate approximation method is used to optimize the calculation process. Experimental results show that the method proposed in this article is more accurate and be used in real time.

An early warning method for water inrush in Dongjiahe coal mine based on microseismic moment tensor

2020 ◽  
Vol 27 (10) ◽  
pp. 3133-3148
Author(s):  
Ke Ma ◽  
Xing-ye Sun ◽  
Chun-an Tang ◽  
Su-jian Wang ◽  
Fu-zhen Yuan ◽  
...  
Keyword(s):  
Coal Mine ◽  
Early Warning ◽  
Moment Tensor ◽  
Water Inrush

scholarly journals Application of Directional Borehole Grouting Technology to Structural Complex Foor Reinforcement in Deep Underground Coal Mine

2018 ◽  
Author(s):  
Qiqing Wang ◽  
Wenping Li
Keyword(s):  
Coal Seam ◽  
Coal Mine ◽  
Water Conservation ◽  
Water Inrush ◽  
Geological Structure ◽  
Directional Drilling ◽  
Rock Stratum ◽  
Factors Affecting ◽  
Mining Depth ◽  
Complex Structural

Water inrush from coal floor constitutes one of the main disasters in mine construction and mine production, which always brings high risks and losses to the coal mine safe production. As the mining depth of coal fields in North China gradually increased, especially in the complicated structural region, the threat posed by limestone karstic water of coal floor to the safe stoping of mines has become increasingly prominent. In this paper, the Taoyuan coalmine was taken as an example, for which, the directional borehole grouting technology was utilized to reinforce the coal seam floor prior to mining. Also, the factors affecting the grouting effect were analyzed. These were the geological structure, the crustal stress and the range of slurry diffusion. The layout principle of grouting drilling was put forward and the directional drilling structure was designed. The water level observations in the end hole indicated that the target stratum was accurate and reliable. The effect of grouting was validated through the audio frequency electric perspective method and the holedrilling in the track trough. The results demonstrated that the effect of grouting in third limestone and the rock stratum above the third limestone of coal seam floor was apparent. Simultaneously, no water inrush occurred following the actual mining of the working face, which further demonstrated that the grouting reinforcement effect was apparent. The research findings were of high significance for the prevention and control of floor water disaster and water conservation in deep complex structural areas.

scholarly journals A multiaxial evaluation of the headache patient

2014 ◽  
pp. 39-45
Author(s):  
Eric Magnoux ◽  
Gregorio Zlotnik ◽  
LaFerrière Justine
Keyword(s):  
Evaluation System ◽  
Evaluation Method ◽  
Functional Disability ◽  
Evaluation Model ◽  
Medical Problem ◽  
Assessment System ◽  
Medical Community ◽  
Primary Headaches ◽  
Headache Disorders ◽  
Headache Patient

Background: Primary headaches are considered a complex medical problem. They usually appear as isolated episodes but can progress into chronic headaches entailing significant functional disability for the patient. With the objective of upgrading the quality of care given to headache patients, there have been several proposals to integrate the wide array of variables which influence headache experiences into a systemized evaluation model. Such a system should prevent key elements from being overlooked, aid diagnosis and facilitate treatment plans. However, as of yet, no such model has been widely adopted. Method: In the present paper, we propose integrating The International Classification of Headache Disorders (ICDH) into a multiaxial assessment system similar to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) which is used in psychiatry. The contents of the different axes found in the DSM cover many of the fundamental clinical variables which have been supported by the medical literature for the past twenty years. Our discussion focuses mainly on chronic headache and migraine since they are clinically relevant to this form of evaluation. We believe our proposed model could be applied generally to all headache types. Conclusion: Headache disorders require an evaluation method flexible enough to reflect the multiple dimensions influencing the course of the disease. In order to achieve a systemized, widely accessible evaluation, we propose a headache patient evaluation structure that is familiar and generally accepted by the medical community. Implementing such a system would be beneficial as it could lead towards building a more uniform evaluation system, facilitate student learning and communication among practitioners, all of which are important steps for improving patient care.

scholarly journals Research and application of coal and gas outburst early warning system based on gas geological features

2021 ◽  
Vol 329 ◽  
pp. 01086
Author(s):  
Yunlong Zou
Keyword(s):  
Coal Seam ◽  
Coal Mine ◽  
Early Warning ◽  
Early Warning System ◽  
Coal Mines ◽  
Warning System ◽  
Geological Structure ◽  
Gas Outburst ◽  
Coal And Gas Outbursts ◽  
Gas Disasters

The geological structure of coal mines has always been a dangerous object of attention in coal mine outburst prevention work. In order to realize coal mine safety information management and early warning of gas disasters, comprehensive use of gas geological theory, coal mine disaster warning theory, computer information technology and other analysis methods, considering the influence of geological structure, coal seam occurrence parameters, and gas parameters, an early warning indicator system for identifying the risk of coal and gas outbursts reflecting the geological characteristics of gas has been constructed. The coal and gas outburst risk identification and early warning system is constructed using the principle of multi-index step-by-step identification and extreme value determination, and it is applied on-site in the 3303 Measure Lane in the East Shaft Area of Sihe Mine. The research results show that the constructed early warning system can provide accurate early warning for the area (belt) affected by the geological structure by 10m, and can provide accurate early warning of coal and gas outbursts based on the outburst signs of gas geology such as the thickness of soft layers and changes in coal seam thickness. This technology provides effective support for coal mines to effectively prevent gas disasters and ensure coal mine production safety.

scholarly journals Improving the Sustainability of Open Government Data

2019 ◽  
Vol 11 (8) ◽  
pp. 2388 ◽  
Author(s):  
Jiang ◽  
Shao ◽  
Liou ◽  
Shao ◽  
Shi
Keyword(s):  
Evaluation System ◽  
Evaluation Model ◽  
Influential Factors ◽  
Assessment System ◽  
Open Government ◽  
Political Values ◽  
Open Government Data ◽  
Network Process ◽  
Government Work ◽  
Government Data

In the context of big data, opening government data to society for development and utilization would improve the transparency of government work and promote harmonious social development. Improving the sustainability of open government data (OGD) is an important and challenging issue, and has received the attention of multiple governments. The goals of this study are to construct a new evaluation model for the sustainability of OGD that explores the main influential factors and amends the priorities. We used a combination of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and the Analytical Network Process (ANP) method known as DANP to construct an influential network relationship map (INRM) of the evaluation system and calculate the criterion weights. The INRM and weights can help decision makers understand the complex assessment system and set priorities for improving OGD. The results demonstrate that the improvement priorities of dimensions have the following order: impact (D4), use (D3), data (D2), and environment (D1). Economic, social, and political values are the three critical factors for improvement of the sustainability of OGD. Some implications for management are also provided.

scholarly journals Application of Tennessee Value-Added Assessment System in The Quality Management of Clinical Bedside Teaching Base

2020 ◽  
Author(s):  
Qingyu Jiang ◽  
Yuanxi Wu ◽  
Yingchao Liu
Keyword(s):  
Education Reform ◽  
Evaluation System ◽  
Evaluation Model ◽  
Value Added ◽  
Teaching Quality ◽  
Assessment System ◽  
Bedside Teaching ◽  
Evaluation Indexes ◽  
A Value ◽  
Foreign Countries

Abstract Background: Compared with foreign countries, China's education evaluation system mostly adopts the method of simple comparison of students' average scores, and the evaluation results are relatively simple; It is a top-down, one-way and appraisal evaluation system, which not only can not form information feedback network, but also can not fully mobilize the enthusiasm and initiative of the evaluation subject and the evaluation object. As a value-added evaluation model, TVAAS can provide multi-dimensional information and has been widely used in foreign countries. Therefore, we need to learn from the Tennessee value-added evaluation model system, and a series of domestic studies have proved that value-added evaluation should be an important part of school evaluation. Results: The evaluation indexes of grade 2016 students were significantly better than that of grade 2015 students, and there was statistical differences between the two groups’ evaluation indexes (P < 0.05). Conclusion: To a certain extent, "Tennessee Value-Added Assessment System" can objectively evaluate the growth rate of teaching quality of clinical bedside teaching bases, and evaluate the correlation between relevant education reform measures and teaching quality improvement scientifically, which is proposed for further popularization and application.

Intelligent system of English composition scoring model based on improved machine learning algorithm

2020 ◽  
pp. 1-11
Author(s):  
Jie Liu ◽  
Lin Lin ◽  
Xiufang Liang
Keyword(s):  
Machine Learning ◽  
Evaluation System ◽  
Intelligent System ◽  
Learning Algorithm ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Assessment System ◽  
English Composition ◽  
Region Extraction ◽  
Constraint Model

The online English teaching system has certain requirements for the intelligent scoring system, and the most difficult stage of intelligent scoring in the English test is to score the English composition through the intelligent model. In order to improve the intelligence of English composition scoring, based on machine learning algorithms, this study combines intelligent image recognition technology to improve machine learning algorithms, and proposes an improved MSER-based character candidate region extraction algorithm and a convolutional neural network-based pseudo-character region filtering algorithm. In addition, in order to verify whether the algorithm model proposed in this paper meets the requirements of the group text, that is, to verify the feasibility of the algorithm, the performance of the model proposed in this study is analyzed through design experiments. Moreover, the basic conditions for composition scoring are input into the model as a constraint model. The research results show that the algorithm proposed in this paper has a certain practical effect, and it can be applied to the English assessment system and the online assessment system of the homework evaluation system algorithm system.

Fuzzy Comprehensive Evaluation of Human Performance Management

2013 ◽  
Vol 756-759 ◽  
pp. 715-719
Author(s):  
Huan Cheng Zhang ◽  
Ya Feng Yang ◽  
Feng Li ◽  
Li Nan Shi
Keyword(s):  
Performance Management ◽  
Evaluation System ◽  
Human Performance ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Assessment Process ◽  
College Performance ◽  
Performance Evaluation System ◽  
Comprehensive Evaluation Model

In the College, performance evaluation system is directly related to the harmonious development of the school. Taking into account the factors in the evaluation system is fuzzy, so this paper uses fuzzy comprehensive evaluation model. But the model is too subjective, so this paper combines neural network and data envelopment analysis method, which ensures that fuzzy comprehensive evaluation model is reasonable and scientific, and good school development and teacher self-interest. The performance assessment process, not only enables the combination of qualitative and quantitative analysis, but also fair and reasonably reflect the achievements of teachers, while this method is easy to use, wide application, and can be well applied in practice.

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