人口统计数据空间化的一种方法

人口空间分布信息在环境健康风险诊断、自然灾害损失评估和现场抽样调查比较等地理学和相关学科研究中占有重要的地位。目前随着对地观测技术和地理信息科学的飞速发展, 如何精确地进行人口数据空间化成为了研究的难点和热点。针对采用传统方法解决人口空间化问题所遇到的困难和不足, 设计了遗传规划(genetic programming, GP)、遗传算法(genetic algorithms, GA) 和GIS 相结合的方法, 以GIS 确定量化影响因子权重, 以GP 建立模型结构, 以GA 优化模型参数, 成功建立研究区-山西省和顺县的人口数据格网分布表面。实验证明与传统建模方法(如逐步回归分析模型和重力模型)相比, 所提方法建模过程更为智能化与自动化, 模型结构更为灵活多样, 而且数据拟合精度更高。     

Data-based modelling approach for variable density flow and solute transport simulation in a coastal aquifer

Data-based models, namely artificial neural network (ANN), support vector machine (SVM), genetic programming (GP) and extreme learning machine (ELM), were developed to approximate three-dimensional, density-dependent flow and transport processes in a coastal aquifer. A simulation model, SEAWAT, was used to generate data required for the training and testing of the data-based models. Statistical analysis of the simulation results obtained by the four models show that the data-based models could simulate the complex salt water intrusion process successfully. The selected models were also compared based on their computational ability, and the results show that the ELM is the fastest technique, taking just 0.5 s to simulate the dataset; however, the SVM is the most accurate, with a Nash-Sutcliffe efficiency (NSE) ≥ 0.95 and correlation coefficient R ≥ 0.92 for all the wells. The root mean square error (RMSE) for the SVM is also significantly less, ranging from 12.28 to 77.61 mg/L.     

LA‐ICP‐MS Analysis of Small Samples: Carbonate Reference Materials and Larval Fish Otoliths

This article proposes a methodology to analyse the composition of very small carbonate samples such as larval fish otoliths. The chemical composition of otoliths, which are carbonate structures in the inner ear, is often used to explore population dynamics in fishes. Recent advances in laser ablation‐inductively coupled plasma‐mass spectrometry have suggested its potential application to this field. In this study, analyses were performed using a 193 nm ArF Resonetics LA system, coupled to an Agilent 7700X‐ICP‐MS, with the following ablation parameters: a beam diameter of 5 μm, energy of 3 mJ, 2.7 J cm^?2, laser repetition rate of 10 Hz and translation speed of 2.5 μm s^?1. NIST SRM 610 glass was used as the primary calibration material. Performing this protocol, characterisation of a USGS GP‐4 reference material was achieved with suitable precision and accuracy, but the USGS MACS‐3 reference material appeared more heterogeneous under the ablation conditions tested. Calibration was performed using two different beam diameters (5 and 11 μm). Capelin (Mallotus villosus) otoliths measuring between 10 and 20 μm in diameter were tested. Even though a smaller beam diameter and lower energy were used compared with those normally employed to analyse larger otoliths, the method was successful.     

基于GP服务的地块辅助审查系统研究

基于GP服务的土地地块辅助审查系统为山东省国土资源部门实行城乡增减挂钩项目和耕地保护项目提供了高效、科学的技术辅助手段。该系统以土地规划、现状空间数据为基础,基于GP服务,利用地理信息技术实现土地地块核查的科学化和自动化,直观显示地块统计结果,提高地块核查的准确率,减少人工操作的误差。该文对基于GP服务的土地地块辅助审查系统的数据准备、框架设计、系统技术流程及应用进行了详细阐述。     

基于高斯过程的高分辨率遥感图像变化检测

本文首先通过理论分析,探讨了高斯过程分类器在高分辨率遥感图像变化检测应用中的优势与不足,并针对高斯过程分类器的不足给出了相应的解决方法;其次,提出了一种基于空间上下文相关的高斯过程变化检测方法;最后,通过多个高分辨率遥感实验数据集上的实验设计与分析,验证了高斯过程分类器在高分辨率遥感图像变化检测中的应用能力,并证明了本文提出的解决方法的有效性.     

基于语义的GP服务多层次发现算法

随着云技术的飞速发展,"一切资源皆服务"成为可能,"数字地球"的实现也不例外。观测技术的快速发展使数据资源变得很丰富,但数据利用率低是普遍存在的现象,如何完成空间数据信息的再加工是亟待解决的问题,在云时代,具有数据处理功能的服务是解决此问题的方法之一,如何描述、发现和集成数据处理服务,从云端服务池中发现最优的服务是其关键所在。为了提高服务的查全率和查准率,引入了本体的概念,服务的语义描述很大程度上提高了空间数据处理服务的应用范围,缓解了非专业用户和专业人员之间的沟通障碍。本文分析了相关领域服务匹配算法的优缺点,结合GP服务自身的特点,提出了本体的GP服务的多层次发现算法:通过包含关系和线索关系完成服务间隐含关系的挖掘,主要是父子关系和前驱后继关系的表述;扩展传统本体表达模型,增加包含和线索关系,为服务的查找做准备;服务的多层次查找,第一次筛选主要针对服务预处理中包含和线索关系的表达查找,第二次筛选利用神经网络的突触原理,结合传统的服务匹配算法,完成服务的准确查找。经试验证明,此方法大大地提高了服务的查准率和查全率,具有重要的实践意义。     

基于 AO 的基本农田划定方法研究

如何在二调数据基础上对基本农田数据进行划分,是二调数据的一个重要应用。本文通过利用ARC-MAP空间叠置分析工具,设计了一整套基本农田划区定界计算流程,利用AO研发了一套基本农田划区定界软件,并成功地应用在长兴、常山等县市的基本农田划区定界工作中。     

洪水超定量模型的广义Pareto分布及其应用

为了扩大洪水信息,提高洪水模拟精度,研究超定量洪水频率分析模型。介绍了洪水超定量模型的基本理论,假设超定量洪水年发生次数服从Poisson分布,超定量洪水系列服从广义Pareto(GP)分布,给出年最大超定量洪水分布和超定量洪水重现期的计算方法,提出通过模型拟合优度检验来综合确定超定量系列阈值的方法。将超定量模型应用在海河流域小觉站洪峰频率分析中,结果表明:通过模型拟合优度检验确定超定量系列阈值的方法有效且可靠,洪水超定量系列年平均发生次数服从Poisson分布,GP分布洪峰设计值略大于P-Ⅲ分布洪峰设计值,应用在水利工程设计及风险分析中是偏安全的。     

GP服务在环境地理信息公共服务平台空间分析中的应用

随着Web Services技术的兴起,面向服务的平台架构被放在十分重要的位置。针对环境信息服务而言,环境信息服务的时效性要求检测结果能提供给多个部门进行分析处理,以往基于单机的模式无法满足实际需要,有必要发展基于Web Services的环境地理信息公共服务平台。本文结合环境地理信息公共服务平台,探讨GP服务在平台空间分析中的应用。     

A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

Developing a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation (R), Nash–Sutcliffe efficiency coefficient (E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.