Comparing Human and Neural Network Learning of Climate Categories     

Robert Lloyd  Gregory Carbone 《The Professional geographer》1995,47(3):237-250

This study compares how humans and neural networks classify climate types. Human subjects were asked to classify climates from monthly temperature and precipitation patterns. To model their learning process, the same data were used to produce input vectors that trained a pattern associator neural network. Both human subjects and the neural network classified climates accurately after 10 rounds of supervised learning. The neural network successfully modeled the rate of human learning and the ability to learn specific climate categories. Moreover, the neural network weights used to classify climates correspond to distinct visual characteristics in temperature and precipitation. These results suggest that neural networks can model the formation of visual categories.  相似文献   

裂隙各向异性介质波场VSP多分量记录的数值模拟   总被引：5，自引：2，他引：5       下载免费PDF全文

牛滨华  何樵登 《地球物理学报》1995,38(4):519-527

从各向异性介质中最为普遍的裂隙各向异性介质出发，推导了同零井源距ＶＳＰ三分量观测方式相一致的一维三分量波动方程．为了更符合实际观测，引入了坐标旋转，可以模拟井中任意方位的多层各向异性介质的波场响应．用有限元方法进行了波场数值模拟，重点突出了获得凡Ｒ_３×３矩阵剖面的方法，同时对Ｒ_３×３，矩阵剖面进行了一般性的分析解释，事实证明，Ｒ_３×３矩阵剖面含有介质丰富的各向异性信息．  相似文献   

Learning about learning: lessons from public engagement and deliberation on urban river restoration   总被引：1，自引：0，他引：1  

JUDITH PETTS 《The Geographical journal》2007,173(4):300-311

This paper provides a new discussion of how people learn through deliberative processes, drawing upon empirical analysis of a novel public engagement process for urban river restoration. Such critical evaluation is rare and yet will be crucial to both theoretical development and learning about engagement practice, not least in a policy area subject to strong regulatory drivers for public participation. The analysis supports two important learning mechanisms – the use of 'gatekeepers' of knowledge, interests and values, and the privileging of narrative. It provides new evidence of instrumental and communicative learning about shared priorities and criteria for effective river restoration that evolved through the deliberative process and directly informed the restoration scheme. It is important to question whether and how such site or context-specific learning might inform other restoration schemes. Finally, the paper questions the often ignored issue of expert learning, not least the issue of the link between individual and organizational learning.  相似文献   

Deriving rules from activity diary data: A learning algorithm and results of computer experiments   总被引：1，自引：0，他引：1  

Theo A. Arentze  Frank Hofman  Harry J.P. Timmermans 《Journal of Geographical Systems》2001,3(4):325-346

 Activity-based models consider travel as a derived demand from the activities households need to conduct in space and time. Over the last 15 years, computational or rule-based models of activity scheduling have gained increasing interest in time-geography and transportation research. This paper argues that a lack of techniques for deriving rules from empirical data hinders the further development of rule-based systems in this area. To overcome this problem, this paper develops and tests an algorithm for inductively deriving rules from activity-diary data. The decision table formalism is used to exhaustively represent the theoretically possible decision rules that individuals may use in sequencing a given set of activities. Actual activity patterns of individuals are supplied to the system as examples. In an incremental learning process, the system progressively improves on the selection of rules used for reproducing the examples. Computer experiments based on simulated data are performed to fine-tune rule selection and rule value update functions. The results suggest that the system is effective and fairly robust for parameter settings. It is concluded, therefore, that the proposed approach opens up possibilities to derive empirically tested rule-based models of activity scheduling. Follow-up research will be concerned with testing the system on empirical data. Received: 31 January 2001 / Accepted: 13 September 2001  相似文献   

叠前正演模拟与偏移的网络并行计算     

胡光岷  黄德济  常建华  贾雨 《物探化探计算技术》2001,23(4):318-323

在叠前深度偏移和非零炮检距声波方程正演计算过程中包含了大量的可并行计算的成分。作者在本文中提出叠前正演模拟与偏移的网络并行计算算法，并基于TCP／IP协议，将该算法设计成网络并行处理程序，极大地提高了计算效率。实际运算结果证明，本文提出的并行算法和技术路线是切实可行的。  相似文献   

利用一种新的神经网络模型识别点状地图符号   总被引：1，自引：0，他引：1  

黄文骞 《武汉大学学报(信息科学版)》1996,(1)

着重讨论了用一种新的神经网络模型识别点状地图符号的过程，主要包括网络的结构特点和学习算法以及学习训练过程，并验证了用该网络进行点状地图符号识别的有效性。  相似文献   

A minimalistic approach for evapotranspiration estimation using the Prophet model     

A. T. M. Sakiur Rahman  Takahiro Hosono  Ozgur Kisi  Boateng Dennis  A. H. M. Rahmatullah Imon 《水文科学杂志》2020,65(12):1994-2006

ABSTRACT

This study aimed to evaluate the potential of the recently introduced Prophet model for estimating reference evapotranspiration (ETo). A comparative study was conducted for benchmarking the model results with support vector regression (SVR) and temperature-based empirical models (Thornthwaite and Hargreaves) in southern Japan. The performance of the Prophet, SVR and temperature-based empirical models was evaluated by Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R²). The results indicate that temperature-based Prophet and SVR models have greater accuracy than the empirical models. The Prophet model with sole input of relative humidity, sunshine hours or windspeed showed acceptable accuracy (NSE > 0.80; R² > 0.80), while SVR models with similar inputs showed greater errors. Accuracy improved with increasing number of input parameters, giving excellent performance (NSE > 0.95; R² > 0.95) with all input parameters. Hence, the Prophet model is a new promising approach for modelling ETo with limited input variables.  相似文献   

星载合成孔径雷达海洋遥感与大数据     

李晓明  黄冰清  贾童  覃婷婷 《南京气象学院学报》2020,12(2):191-203

星载合成孔径雷达以其全天候、全天时、不受云雨影响的工作特性在空间对海观测中起到了重要作用，又以其高空间分辨率、多极化、多成像模式的特点展示了其在海洋动力要素反演和海洋多尺度动力过程研究中独特的魅力.起步于20世纪70年代末的星载合成孔径雷达技术，迎来了发展的"黄金时期"，大数据和机器学习又赋予了星载合成孔径雷达海洋遥感更强大的生命力.本文首先阐述了星载合成孔径雷达大数据的5"V"特性，进而以高分辨率海面风场反演、海洋内波中尺度动力过程观测两类典型案例，阐述了大数据、机器学习等现代信息科学技术与卫星海洋遥感结合，实现海洋环境参数高精度反演和海洋动力过程科学深层次认知的研究.最后，展望了星载合成孔径雷达海洋遥感与大数据的发展前景.  相似文献   

Multiobjective analysis of chaotic dynamic systems with sparse learning machines     

Abedalrazq F. Khalil  Mac McKeeMariush Kemblowski  Tirusew AsefaLuis Bastidas 《Advances in water resources》2006

Sparse learning machines provide a viable framework for modeling chaotic time-series systems. A powerful state-space reconstruction methodology using both support vector machines (SVM) and relevance vector machines (RVM) within a multiobjective optimization framework is presented in this paper. The utility and practicality of the proposed approaches have been demonstrated on the time series of the Great Salt Lake (GSL) biweekly volumes from 1848 to 2004. A comparison of the two methods is made based on their predictive power and robustness. The reconstruction of the dynamics of the Great Salt Lake volume time series is attained using the most relevant feature subset of the training data. In this paper, efforts are also made to assess the uncertainty and robustness of the machines in learning and forecasting as a function of model structure, model parameters, and bootstrapping samples. The resulting model will normally have a structure, including parameterization, that suits the information content of the available data, and can be used to develop time series forecasts for multiple lead times ranging from two weeks to several months.  相似文献   

建筑物立面激光点云的定位     

郭英  卢秀山  王冬 《测绘学院学报》2006,(1)

车载式近景目标3维测量系统,采用激光扫描仪获取建筑物立面点云。激光点云仅具有扫描仪坐标系下的坐标,不便于其他数据融合进行3维建模。文中根据系统的特点和要求,通过建立相应的坐标系,利用已有或优化的坐标转换模型确定坐标系之间的坐标转换关系。依据基准点与载体平台GPS接收机之间同步观测数据将激光点云在扫描仪坐标系下的坐标经过多次坐标转换,得到基准点所在当地坐标系下的坐标。使系统实现了满足精度要求的建筑物立面激光点云的定位工作。  相似文献