我国防止矿井瓦斯事故的地球物理探测技术进展   总被引：3，自引：2，他引：1       下载免费PDF全文

冯宏 《地球物理学进展》2005,20(4):1171-1175

瓦斯事故是煤矿井开采作业面临的第一大灾害,它具有发生突然、动力巨大、伤亡力强、波及面宽等突出特点.瓦斯不均匀地的贮存在煤层中,突出于采动破坏的岩壁段,防止煤矿瓦斯事故是一个典型的地学问题.通过测量岩体物性差异预测瓦斯动力赋存的地质条件,通过测定物性差异体的三维空间位置可确定采矿作业的安全岩体隔离厚度,等等.近十年来地球物理探测技术为防止煤矿瓦斯事故发生发挥着关键作用.  相似文献   

基于A-star算法的矿井事故救援研究     

章冲  李代伟  黄明 《成都信息工程学院学报》2010,(6):264-268

针对井下不同形状巷道几何空间特征,确立以空间点、线、面为基本图元,以巷道中心线作为三维模型构建的基础框架,建立巷道三维模型。采用启发式路径搜索A-star算法,实现了应急救援路线智能快速选择。实践证明,该方法对于矿井事故定位和救援具有一定的实用性。  相似文献   

Positional uncertainty in manually digitized map data     

PAUL V. BOLSTAD  PAUL GESSLER  THOMAS M. LILLESAND 《International journal of geographical information science》2013,27(4):399-412

Digital map coordinates represent the locations of real world entities. As such, differences can exist between the ‘tru’ and digital database coordinates of those entities. This paper reports on a statistical characterization of positional error in manually-digitized and map-registered point data, the relative contribution of point type and operator to digitization error, and the effects of map media type on the positional uncertainty associated with registration.

Manually-digitized point data were collected by four operators from mylar and paper maps. Point locations for a number of different feature types were sampled from United States Geological Survey (USGS) 1:24 000 scale maps. Linear models were used to estimate the variance components due to among-operator, map media, point type and registration effects. The statistical distribution of signed distance deviations for manually-digitized data was leptokurtic relative to a random normal variate. Unsigned deviations averaged 0-054 mm. Squared distance deviations were not different from a Chi-square random variate. Variance components indicate that among-operator differences in positional uncertainty were large and statistically significant, while differences among point type were small and non-significant. Signed distance deviations associated with a first-order afhne followed a normal distribution. Unsigned distance deviations associated with a first-order affinc transformation averaged 0068mm, and squared distance deviations were distributed as a Chi-square. Differences in transformation accuracy were not related to type of map media.  相似文献   

An improved ant colony optimization (I-ACO) method for the quasi travelling salesman problem (Quasi-TSP)     

Jianyi Yang  Ruifeng Ding  Yuan Zhang  Maoqin Cong  Fei Wang 《International journal of geographical information science》2013,27(9):1534-1551

Traveling salesman problem (TSP) and its quasi problem (Quasi-TSP) are typical problems in path optimization, and ant colony optimization (ACO) algorithm is considered as an effective way to solve TSP. However, when the problems come to high dimensions, the classic algorithm works with low efficiency and accuracy, and usually cannot obtain an ideal solution. To overcome the shortcoming of the classic algorithm, this paper proposes an improved ant colony optimization (I-ACO) algorithm which combines swarm intelligence with local search to improve the efficiency and accuracy of the algorithm. Experiments are carried out to verify the availability and analyze the performance of I-ACO algorithm, which cites a Quasi-TSP based on a practical problem in a tourist area. The results illustrate the higher accuracy and efficiency of the I-ACO algorithm to solve Quasi-TSP, comparing with greedy algorithm, simulated annealing, classic ant colony algorithm and particle swarm optimization algorithm, and prove that the I-ACO algorithm is a positive effective way to tackle Quasi-TSP.  相似文献   

A fast clonal selection algorithm for feature selection in hyperspectral imagery     

Yanfei Zhong  Liangpei Zhang 《地球空间信息科学学报》2013,16(3):172-181

Clonal selection feature selection algorithm (CSFS) based on clonal selection algorithm (CSA), a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm (FCSFS) for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager (PHI) and the airborne visible/infrared imaging spectrometer (AVIRIS), respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.  相似文献   

基于卷积神经网络的雷电临近预警模型     

张烨方  冯真祯  刘冰 《气象》2021,(3):373-380

从研究人工智能雷电临近预警模型的目的出发,以卷积神经网络模型为基础,结合多个时间序列的雷达产品(组合反射率、液态水含量、回波顶高)与闪电数据,对雷电临近预报方法进行基于卷积神经网络结构的应用,以福建省2017—2018年雷达、闪电数据为样本完成了模型的训练与预测研究。训练结果显示,15~30 min模型训练样本测试集准确率为0.7985;选取福建省2019年20个雷电过程验证分析表明,15~30 min模型对动力抬升型雷电过程预警TS评分为0.716,夏季局地热雷暴预警TS评分为0.694,与常规采用雷达、闪电阈值控制的雷电预警算法相比,准确率有一定的提高,具有一定的实践意义。  相似文献   

Measuring the accessibility of different household income groups to basic community services in upland Misamis Oriental,Northern Mindanao,Philippines     

Marc Elgin M. Delgado  Frank Canters 《Singapore journal of tropical geography》2011,32(2):168-184

Improving household accessibility to basic community services can help reduce poverty in upland areas. In this study, spatial analysis with GIS was used to measure the accessibility of different household income groups to community services in the landlocked upland municipality Claveria in Northern Mindanao, the Philippines. Important community services were identified through villagers' participation in a matrix‐scoring activity. Travel information was derived from key informant interviews while the geographical coordinates of sample households and important services were collected using GPS receivers. The Flowmap GIS software (version 7.2) was used to compute accessibility to services along the road network by habal‐habal (two‐wheel motorcycle). Outcomes from the participatory data gathering activities revealed that agricultural, educational and health facilities, as well as government services are important to the community to achieve sustainable livelihoods. Because local people perceive accessibility in terms of monetary costs, rather than distance, road distance measurements were converted into fare costs. Results of the accessibility analysis show that higher‐income household groups generally incur lower mean one‐way travel costs to reach important community services than poorer households. However, almost all households spend more than the daily per capita poverty threshold for the province to reach basic community services. A scenario to improve accessibility to services in the study area was investigated to emphasize the potential of GIS‐based accessibility analysis in rural service planning.  相似文献   

云岭隧道围岩监测免疫智能正演反分析     

王晓睿  王元汉  刘晓南 《地球科学》2008,33(5):699-705

深埋长隧道中大变形、高应力、复杂的工程地质环境和长期使用需要使得对隧道围岩的稳定性分析成为决定深埋长大隧道工程成败的关键问题.利用位移反分析法分析确定围岩参数是目前研究的一个重点, 用以处理隧道围岩物理力学参数与量测信息之间的非线性关系, 对围岩二次支护方案进行判断、调整.而人工智能在识别、表达与处理这种复杂的非线性关系方面表现了极强的能力.通过对十漫高速公路云岭隧道围岩变形进行监控测量, 结合生物仿真系统和快速拉格朗日分析软件(FLAC) 进行正演分析, 利用神经网络的高度非线性、网络推理和网络耦合能力, 通过数值分析软件获得神经网络训练所需要的输出向量, 以可自适应调节的免疫算法为搜索工具对参数进行全局空间搜寻, 寻找最佳网络结构, 利用量测信息反分析寻找最佳参数, 得出结果再通过正向计算进行验证.通过智能反演分析, 改进了原勘测资料中的建议值, 调整了支护方案, 得到满意结论.表明本文所提反演分析对隧道围岩稳定性评价及信息化设计的实际意义.   相似文献   

Neural network modelling of planform geometry of headland-bay beaches     

G. Iglesias  I. Lpez  A. Castro  R. Carballo 《Geomorphology》2009,103(4):577-587

The shoreline of beaches in the lee of coastal salients or man-made structures, usually known as headland-bay beaches, has a distinctive curvature; wave fronts curve as a result of wave diffraction at the headland and in turn cause the shoreline to bend. The ensuing curved planform is of great interest both as a peculiar landform and in the context of engineering projects in which it is necessary to predict how a coastal structure will affect the sandy shoreline in its lee. A number of empirical models have been put forward, each based on a specific equation. A novel approach, based on the application of artificial neural networks, is presented in this work. Unlike the conventional method, no particular equation of the planform is embedded in the model. Instead, it is the model itself that learns about the problem from a series of examples of headland-bay beaches (the training set) and thereafter applies this self-acquired knowledge to other cases (the test set) for validation. Twenty-three headland-bay beaches from around the world were selected, of which sixteen and seven make up the training and test sets, respectively. As there is no well-developed theory for deciding upon the most convenient neural network architecture to deal with a particular data set, an experimental study was conducted in which ten different architectures with one and two hidden neuron layers and five training algorithms – 50 different options combining network architecture and training algorithm – were compared. Each of these options was implemented, trained and tested in order to find the best-performing approach for modelling the planform of headland-bay beaches. Finally, the selected neural network model was compared with a state-of-the-art planform model and was shown to outperform it.  相似文献   

Modeling unusual eruptive behavior of Mt. Etna,Italy, by means of event bush     

Boris Behncke  Cyril A. Pshenichny 《Journal of Volcanology and Geothermal Research》2009

One of the best-studied volcanoes of the world, Mt. Etna in Sicily, repeatedly exhibits eruptive scenarios that depart from the behavior commonly considered typical for this volcano. Episodes of intense explosive activity, pyroclastic flows, dome growth and cone collapse pose a variety of previously underestimated threats to human lives in the summit area of the volcano. However, retrospective analysis of these events shows that they were likely caused by the same very sets of premises and starting conditions as “normal” eruptions, yet combined in an unexpected, probably unique, way. To cope with such unexpected consequences, we involve an approach of artificial intelligence developed specially for needs of the geosciences, the event bush. Scenarios inferred from the event bush fit the observed ones and allow to foresee other low-probability events that may occur at the volcano. Application of the event bush provides a more impartial vision of volcanic phenomena and may serve as an intermediary between expert knowledge and numerical assessment, e.g., by means of Bayesian Belief Networks.  相似文献