人工智能在冰雹识别及临近预报中的初步应用   总被引：1，自引：0，他引：1       下载免费PDF全文

张文海  李磊 《气象学报》2019,77(2):282-291

基于广东10部S波段多普勒天气雷达的三维拼图资料,利用机器学习技术开发了一种冰雹识别和临近预报的人工智能算法。算法设计时以雷达回波反射率的垂直和水平扫描数据为基础训练集,将冰雹云的雷达反射率扫描数据作为正样本,将其他雷达反射率扫描数据作为负样本,通过贝叶斯分类法对正、负样本数据集进行机器学习,训练人工智能识别冰雹云内在规律的能力。训练时以广东省2008-2013和2015-2016年的数据作为训练集,使用了2014年广东省12次冰雹过程的数据做检验。对比检验的结果表明,人工智能法比传统的概念模型法击中率高9个百分点。研究结果表明了人工智能对冰雹这类非线性强天气过程具有较强的识别能力。   相似文献   

A neurocomputing approach to the forecasting of monthly maximum temperature over Kolkata, India using total ozone concentration as predictor     

Syam Sundar De  Goutami Chattopadhyay  Bijoy Bandyopadhyay  Suman Paul 《Comptes Rendus Geoscience》2011,343(10):664-676

The association between the monthly total ozone concentration and monthly maximum temperature over Kolkata (22.56° N, 88.30° E), India, has been explored in this paper. For this, the predictability of monthly maximum temperature based on the total ozone as predictor is investigated using Artificial Neural Network. The presence of persistence and similar cyclic patterns are revealed through autocorrelation and cross-correlation coefficients. Common cycles of length 12 and 6 have been identified through periodogram. Hence, a predictive model has been generated by Artificial Neural Network in the form of Multi Layer Perceptron (MLP) using scaled conjugate gradient learning with sigmoid non-linearity. After training and testing the network, an MLP with total ozone of month n as predictor and maximum temperature of month (n + 1) as the target output is found as the best model. Performance of the model has been judged statistically. Finally, the MLP model has been compared with linear and non-linear regressions and the efficiency of MLP has been established over the regression models.  相似文献   

NNFFC-adaptive output feedback trajectory tracking control for a surface ship at high speed     

Li-Jun Zhang  Xue Qi 《Ocean Engineering》2011,38(13):1430-1438

An adaptive output feedback controller based on neural network feedback-feedforward compensator (NNFFC) which drives a surface ship at high speed to track a desired trajectory is designed. The tracking problem of the surface ship at low speed has been widely investigated. However, the coupling interactions among the forces from each degree of freedom (DOF) have not been considered in general. Furthermore, the influence of the hydrodynamic damping is also simplified into a linear form or neglected. On the contrary, coupling interactions and the nonlinear characteristics of the hydrodynamic damping can never be neglected in high speed maneuvering situation. For these reasons, the influence of the nonlinear hydrodynamic damping on the tracking precision is considered in this paper. Since the hydrodynamic coefficients of the surface ship at high speed are very difficult to be accurately estimated as a prior, it will be compensated by NNFFC as an unknown part of the tracking dynamics system. The stability analysis will be given by the Lyapunov theory. It indicates that the proposed control scheme can guarantee that all the signals in the closed-loop system are uniformly ultimately bounded (UUB), and numerical simulations can illustrate the excellent tracking performance of the surface ship at high speed under the proposed control scheme.  相似文献   

基于GIS和BP神经网络的区域农村贫困空间模拟分析——一种区域贫困程度测度新方法   总被引：5，自引：0，他引：5  

曾永明  张果 《地理与地理信息科学》2011,27(2):70-75

基于区域农村贫困程度测定方式不完善及缺乏地理视角的现状,选取四川省36个国家级扶贫县为实证对象,构建自然社会经济全面耦合的农村贫困测度指标体系,分析区域农村贫困的影响机制,并运用GIS与BP神经网络模拟区域自然致贫指数、社会致贫指数和经济消贫指数的空间分布格局。在此基础上,提出了全面表征区域农村贫困程度的区域扶贫压力指数——一种新的区域农村贫困测度方法,为国家扶贫政策文件《财政扶贫资金管理办法》中关于财政扶贫资金基于区域农村贫困程度分配提供实践基础。  相似文献   

盆地基底岩性的综合地球物理预测方法——以松辽盆地滨北地区基底岩性预测为例   总被引：3，自引：2，他引：1       下载免费PDF全文

李成立  崔瑞华  刘益中 《地球物理学报》2011,54(2):491-498

预测盆地基岩岩性不仅对于研究盆地的深部地质结构及盆地的形成演化具有重要的意义,而且也对基岩风化壳油气藏的勘探具有一定的指导作用.本文通过对盆地重、磁异常成因的综合分析,提出了一系列盆地基底岩性综合预测研究的综合地球物理资料处理解释方法技术.指出在地震构造界面的约束下采用重力剥皮技术可以较为可靠地获取基底岩性重力异常并分...  相似文献   

Artificial neural network forward modelling and inversion of electrokinetic logging data     

N. Ardjmandpour  C. Pain  J. Singer  J. Saunders  E. Aristodemou  J. Carter 《Geophysical Prospecting》2011,59(4):721-748

An artificial neural network method is proposed as a computationally economic alternative to numerical simulation by the Biot theory for predicting borehole seismoelectric measurements given a set of formation properties. Borehole seismoelectric measurements are simulated using a finite element forward model, which solves the Biot equations together with an equation for the streaming potential. The results show that the neural network method successfully predicts the streaming potentials at each detector, even when the input pressures are contaminated with 10% Gaussian noise. A fast inversion methodology is subsequently developed in order to predict subsurface material properties such as porosity and permeability from streaming potential measurements. The predicted permeability and porosity results indicate that the method predictions are more accurate for the permeability predictions, with the inverted permeabilities being in excellent agreement with the actual permeabilities. This approach was finally verified by using data from a field experiment. The predicted permeability results seem to predict the basic trends in permeabilities from a packer test. As expected from synthetic results, the predicted porosity is less accurate. Investigations are also carried out to predict the zeta potential. The predicted zeta potentials are in agreement with values obtained through experimental self potential measurements.  相似文献   

Neural-network predictability experiments for nearshore sandbar migration     

L. Pape  B.G. Ruessink 《Continental Shelf Research》2011,31(9):1033-1042

Cross-shore migratory behavior of nearshore sandbars is commonly studied with nearshore bathymetric-evolution models that represent underlying processes of hydrodynamics and sediment transport. These models, however, struggle to reproduce natural cross-shore sandbar behavior on timescales of a few days to weeks and have uncertain skill on longer scales of months to years. One particular concern for the use of models on prediction timescales that far exceed the timescale of the modeled processes is the exponential accumulation of errors in the nonlinear model equations. The relation between cross-shore sandbar migration, sandbar location and wave height has previously been demonstrated to be weakly nonlinear on timescales of several days, but it is unknown how this nonlinearity affects the predictability of long-term (months to years) cross-shore sandbar behavior. Here we study the role of nonlinearity in the predictability of sandbar behavior on timescales of a few days to several months with data-driven neural network models. Our analyses are based on over 5600 daily-observed cross-shore sandbar locations and daily-averaged wave forcings from the Gold Coast, Australia, and Hasaki, Japan. We find that neural network models are able to hindcast many aspects of cross-shore sandbar behavior, such as rapid offshore migration during storms, slower onshore return during quiet periods, seasonal cycles and annual to interannual offshore-directed trends. Although the relation between sandbar migration, sandbar location and wave height is nonlinear, sandbar behavior can be hindcasted accurately over the entire lifespan of the sandbars at the Gold Coast. Contrastingly, it is difficult to hindcast the long-term offshore-directed trends in sandbar behavior at Hasaki because of exponential accumulation of errors over time. Our results further reveal that during periods with low-wave conditions it becomes increasingly difficult to predict sandbar locations, while during high waves predictions become increasingly accurate.  相似文献   

基于MATLAB神经网络方法的多层砖房震害预测   总被引：1，自引：0，他引：1       下载免费PDF全文

姜伟  马令勇  刘功良 《地震工程学报》2011,33(2):155-158

提出利用MATLAB人工神经网络工具箱建立基于贝叶斯正则算法的BP神经网络模型,以地震区多层砖房震害调查数据为因子的震害预测方法.神经网络模型输入震害因子包括建筑的层数、施工质量、房屋整体性等,输出值为建筑物在地震作用下的破坏程度.结果表明,本方法可以对多层砖房的震害样本进行预测并达到较理想的效果.  相似文献   

浅谈新疆测震台网传输链路的改造     

袁顺 《内陆地震》2011,(4):373-378

要做到IP到台站有很多种方式可选,根据新疆测震台网各台站的现状列举了7类不同的数据传输方式,这些数据传输方式在新疆测震台网中均得到应用,也都达到IP到台站的目的.分别对这些数据传输链路的原理及优缺点进行阐述,并结合目前各台站具体情况作链路适用性的相关分析,希望能够对其他省局台网的台站通信链路设计、改造起到参考.  相似文献   

聊古1井在不同取水模式下气体观测效果的对比分析     

李月强  王华  刘保华  连凯旋  崔娜  孙丕锋  冯恩国  赵杰锋 《中国地震》2011,27(2):192-198

为解决聊古1井断流问题,聊城地震水化试验站先后引进、开发了人工激发引流观测技术和潜水泵变频稳流抽水技术.对天然自流观测系统、人工激发引流观测系统和潜水泵变频稳流抽水观测系统等3种不同取水模式下产出的气体观测数据进行一致性分析.结果表明,人工激发引流观测系统下气体观测动态特征年变比较明显,潜水泵变频稳流抽水观测系统下气体观测动态特征与天然自流状态下的动态特征基本一致.  相似文献