基于局部聚类的网络Voronoi图生成方法研究

提出一种将网络约束下的Voronoi和空间聚类相结合的方法,通过构造局部的聚类分析方法对网络边进行加权,根据实际的点过程性质可以把权重定义为加权或者乘权,进行标准化后与道路段本身长度融合进行计算,依此生成网络Voronoi图,以期理解城市街道的空间特性。以武汉市江汉区为例,对城市网格管理系统产生的城市事件进行算法验证,结果表明,该方法提供了一种灵活的网络约束下的服务区域划分工具,可用于基于网络空间点过程影响下的服务区划分,也可用于系统性地定量刻画城市管理的动态特性。     

面向地学应用的不确定数据聚类算法比较研究

不确定数据聚类分析已成为空间数据挖掘领域的一个研究热点。近年来,在传统划分与基于密度的聚类算法基础上,一系列不确定数据聚类算法相继被提出。虽然这些算法在地学领域的应用已经得到了广泛关注,然而其实际应用的有效性尚缺乏客观的评价。为此,选取当前具有代表性的6种算法进行实验对比分析。首先,设计40组包含预设模式的模拟数据进行测试。进而,采用亚洲气候数据集对6种方法识别气候区的能力进行比较分析,以Kppen-Geiger气候分类结果为基准对各种方法的实际应用效果进行评价。借助准确率和召回率对各种方法的聚类质量定量度量后,发现:1)对于同类型聚类算法,采用相对熵距离的算法聚类质量总体优于采用期望距离和模糊距离函数的算法;2)采用相对熵距离的划分算法聚类质量优于基于密度的算法,其中采用相对熵距离的KMedoids-KL算法的聚类质量最好。     

城郊聚落景观的集聚特征分析方法选择研究

高度集聚是城郊聚落景观最明显的空间格局特征,是郊区城市化的直观反映。针对目前景观集聚程度研究空间计算方法缺乏筛选、不具可比性等问题,通过4种集聚空间算法在不同角度分析典型区域的城郊聚落景观集聚特征,并在西安市长安区作以简单应用。结果表明:1景观聚集度适于区分出同类连续大斑块和不同类破碎小斑块,核密度适于宏观上集聚组团的识别,空间关联算法适于空间定位具体要素点的集聚特征,Ripley’s L函数适于识别空间距离以确定搜索半径;2根据核密度计算结果,从研究区聚落景观中提取出3个大型组团,分别命名为"政府商业中心聚落组团""沣渭新区聚落组团"和"旅游度假区聚落组团",其划分模式符合研究区各经济板块的未来发展方向。     

基于机器学习的贫困地区识别算法对比——以陕西省为例

以传统社会经济指标为主导的贫困识别依赖于详尽的普查抽查数据,收集和处理不同质量和数量的普查抽查数据来研究区域贫困需要耗费大量的人力物力和时间,难以快速动态地监测贫困状态。然而时间分辨率高且客观易获取的夜间灯光数据可以在一定程度上弥补统计数据的劣势,即时地反映地表社会经济现象。机器学习算法能够从这些数据中学习出规律和模式,从中挖掘出潜在信息来识别贫困地区。基于陕西省NPP-VIIRS夜间灯光数据,通过构造多维统计变量,利用逻辑回归、支持向量机、K近邻、随机森林、决策树和梯度提升树6种监督分类算法识别贫困地区。结果表明从夜间灯光数据提取的多维特征能够更好的应用于贫困地区的识别,6种算法都能够准确的识别贫困地区,分类结果在空间上具有相似性,且表现出一定的地域性,分类准确度达到76.82%~83.20%。根据混淆矩阵进一步对比各个算法的特点,认为随机森林算法在误差偏移和分类精度等方面综合表现最佳。     

Reservoir Characterization Using Multi-component Seismic Data in a Novel Hybrid Model Based on Clustering and Deep Neural Network

Natural Resources Research - Effective use of the difference between longitudinal and converted shear waves in reservoir sensitivity analysis is a key component to reduce the multi-solution problem...     

A Novel Intelligent ELM-BBO Technique for Predicting Distance of Mine Blasting-Induced Flyrock

Natural Resources Research - Blasting is an economical technique for rock breaking in hard rock excavation. One of its complex undesired environmental effects is flyrock, which may result in human...     

Mapping of Regional-scale Multi-element Geochemical Anomalies Using Hierarchical Clustering Algorithms

Natural Resources Research - Mapping of multi-element geochemical anomalies is the basic goal of stream sediment sampling in worldwide, and especially at 1:100,000 scale in Iran. In the central...     

Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network

Natural Resources Research - Ground vibration (PPV) is one of the hazard effects induced by blasting operations in open-pit mines, which can affect the surrounding structures, particularly the...     

ORELM: A Novel Machine Learning Approach for Prediction of Flyrock in Mine Blasting

Blast-induced flyrock is a hazardous and undesirable phenomenon that may occur in surface mines, especially when blasting takes place near residential areas. Therefore, accurate prediction of flyrock distance is of high significance in the determination of the statutory danger area. To this end, there is a practical need to propose an accurate model to predict flyrock. Aiming at this topic, this study presents two machine learning models, including extreme learning machine (ELM) and outlier robust ELM (ORELM), for predicting flyrock. To the best of our knowledge, this is the first work that investigates the use of ORELM model in the field of flyrock prediction. To construct and verify the proposed ELM and ORELM models, a database including 82 datasets has been collected from the three granite quarry sites in Malaysia. Additionally, artificial neural network (ANN) and multiple regression models were used for comparison. According to the results, both ELM and ORELM models performed satisfactorily, and their performances were far better compared to the performances of ANN and multiple regression models.

     

基于支持向量机的扎龙湿地遥感分类研究

湿地遥感分类是实现湿地动态监测、管理与利用的重要手段之一.由于湿地具有独特的生态环境,获取实测样本点相对困难,因此,研究小样本、高精度的湿地遥感分类方法十分必要.以扎龙国家级自然保护区为研究区,采用支持向量机方法进行了研究区湿地遥感分类研究,初步剖析了样本数量与特征维度对分类结果的影响,并同传统的最大似然分类方法进行了...     

Forecasting Copper Prices Using Hybrid Adaptive Neuro-Fuzzy Inference System and Genetic Algorithms

Natural Resources Research - An accurate forecasting model for the price volatility of minerals plays a vital role in future investments and decisions for mining projects and related companies. In...     

基于遥感和机器学习的内陆水体水深反演技术

文章主要根据机器学习算法（随机森林算法和极端梯度提升算法）和遥感水深反演的原理,利用Sentinel_2多光谱卫星数据和无人船实测水深数据,对内陆水体——梅州水库建立了随机森林（RF）、极端梯度提升（XGBoost）和支持向量机（SVM）水深反演模型,并对反演结果进行对比分析。结果表明：1）RF的训练精度为97%,测试精度为0.80;XGBoost模型的训练精度为97%,测试精度为0.79;SVM的训练精度为90%,测试精度为0.78。说明了在水深预测方面RF模型和XGBoost模型比SVM模型表现更好,对各个区段的水深值较为敏感。2）根据运行时间考察各个模型的效率,其中RF模型从读取数据至输出结果耗时3.92 s;XGBoost模型4.26 s;SVM模型6.66 s。因此,在反演精度和效率上RF模型优于XGBoost模型优于SVM模型,且RF模型的预测结果图细节更加丰富,轮廓更加分明;XGBoost模型次之,但总体效果也较好;SVM模型表现最差。由此可知,机器学习水深反演模型获得的水深结果精度明显提高,解决了传统水深反演模型精度不高的问题。     

A wind shift: Integrating curriculum for education for sustainable development

Abstract:  For seven years, trainee teachers in the Pre-Service Secondary Teacher Education Programme at Massey University College of Education, Albany campus, have integrated their curriculum areas to model the processes school students could follow in environmental education and education for sustainable development using Motutapu, an island adjoining Rangitoto in the Hauraki Gulf Marine Park, as the context for their actions. Evaluation of the programme indicates that it is empowering to learn about connections between subject areas and the potential for school students to have a hand in creating a sustainable future and to participate in real world concerns.     

一种面向对象分类的特征分析方法

特征分析是面向对象分类成功的先决条件,通常采用试错方式进行。由于时间和成果要求等条件限制,通常不可能测试所有的特征,致使所选取特征常常并不是最佳特征,从而导致分类效果不理想。该文采用SaT特征分析方法,从大量特征集中准确提取特有特征,而且能获取相关联的阈值;通过其计算分离度值,可以实时地比较特征分类质量。实例验证表明,该方法能大大提高面向对象分类方法的精度和速度。     

Modeling the Influence of Groundwater Exploitation on Land Subsidence Susceptibility Using Machine Learning Algorithms

Natural Resources Research - Groundwater over-exploitation in arid and semiarid environments has led to many land subsidence cases. Immense economic losses incurred from land subsidence occurrences...     

空间负载平衡探讨

设计、应用合理的空间负载平衡算法是当前分布式地理信息系统研究的一个重要方向。该文介绍了空间负载平衡的基本概念,给出了空间负载平衡的基本算法和改进算法及其空间应用研究现状。对于各种算法进行对比讨论,分析其优劣,指出存在的问题和未来研究的方向。     

A New Magnitude-Frequency Relation for Earthquakes and a Classification of Relation Types

Summary. In this paper some aspects of the deviations of frequency distributions of earthquakes from a linear trend are considered. For recurrence curves with inflexions, the formula
is proposed as a magnitude-frequency relation, with critical magnitude M _cr. Comparison with actual data shows better agreement than other formulae. The slope of the frequency graph is considered in the most general case to be a function of M and some parameters p ₁, p ₂, …. A classification of the types of magnitude-frequency relation is given and all known types of relations N : M and N: K ( K = log E , E = seismic energy) are summarized.