小型局域网络系统的扩展设计     

王灵  杨明 《成都信息工程学院学报》1997,(1)

采用混合方式的网络拓扑结构和内部网桥技术，以低廉的投资实现了一个网络覆盖范围较大、能跨越多栋办公大楼的小型局域网络。该网络电缆距离的延伸较长，布线灵活，网段间隔离性好，不仅可以提高网络传输效率，易于检测判断故障，而且运行安全可靠，是一种有效的计算机小型局域网络设计／改造方案  相似文献   

企鹅珍珠贝人工苗生长的初步观察   总被引：3，自引：0，他引：3  

梁飞龙  毛勇  余祥勇 《广东海洋大学学报》2001,21(1):6-9

为了解企鹅珍珠贝生长规律，观察了壳高2.5～5.0mm的出池幼苗，按月测量其生长参数和成活率，以及环境因子。结果表明，企鹅珍珠贝生长最快的月份为7～11月和次年4～6月，壳长，壳高和壳宽月均增加量分别为3.8～13.0mm、4.7～11.2mm、2.3～3.8mm，月成活率97.8%～98.6%。企鹅珍珠贝生长最慢月份是11月至次年3月。  相似文献   

Neural network prediction of nitrate in groundwater of Harran Plain, Turkey   总被引：2，自引：0，他引：2  

M. Irfan Yesilnacar  Erkan Sahinkaya  Muhsin Naz  Bestamin Ozkaya 《Environmental Geology》2008,56(1):19-25

Monitoring groundwater quality by cost-effective techniques is important as the aquifers are vulnerable to contamination from the uncontrolled discharge of sewage, agricultural and industrial activities. Faulty planning and mismanagement of irrigation schemes are the principle reasons of groundwater quality deterioration. This study presents an artificial neural network (ANN) model predicting concentration of nitrate, the most common pollutant in shallow aquifers, in groundwater of Harran Plain. The samples from 24 observation wells were monthly analysed for 1 year. Nitrate was found in almost all groundwater samples to be significantly above the maximum allowable concentration of 50 mg/L, probably due to the excessive use of artificial fertilizers in intensive agricultural activities. Easily measurable parameters such as temperature, electrical conductivity, groundwater level and pH were used as input parameters in the ANN-based nitrate prediction. The best back-propagation (BP) algorithm and neuron numbers were determined for optimization of the model architecture. The Levenberg–Marquardt algorithm was selected as the best of 12 BP algorithms and optimal neuron number was determined as 25. The model tracked the experimental data very closely (R = 0.93). Hence, it is possible to manage groundwater resources in a more cost-effective and easier way with the proposed model application.  相似文献   

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models     

T. G. Sitharam  Pijush Samui  P. Anbazhagan 《Geotechnical and Geological Engineering》2008,26(5):503-517

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.  相似文献   

江苏省银行网点分布格局及其影响因素研究     

车冰清  朱传耿  李敏 《地理科学》2017,37(12):1867-1874

以江苏省为研究对象,基于网络平台的银行网点地理数据,运用最近邻指数、Ripley’s K函数以及多元线性回归等分析方法,分别对五大商业银行、农业金融机构、中小商业银行、江苏地方银行以及外资银行的空间分布特征进行探讨,并揭示不同类型银行网点区位选择的影响因素。研究结果：整体上,江苏省银行网点空间偏向分布差异明显“南多北少”,空间集聚特征显著“城区密集分布和外围分散分布”;不同类型银行由于功能和市场定位的不同,除在城区密集分布的共性外,在城市外围区域的分布密度和服务范围存在较大差异。城市建成区面积、人口规模、人均地区生产总值、规模以上工业企业数量、城镇化率、二三产业产值比重是影响银行网点区位选择的主要因素,但对不同类型银行网点分布的影响程度不同。五大商业银行网点分布倾向于人口规模大、城镇化率高的城市,农业金融机构网点更依赖于农业人口因素,中小商业银行网点偏爱二三产业发达的区域,规模以上工业企业数量对江苏地方银行网点的布局具有显著影响,外资银行主要分布在对外开放程度高和国外资本输入较多的城市。城市行政级别和城市性质等制度因素对农业金融机构、外资银行网点区位选择的影响作用较强。  相似文献   

跨区域线性文化遗产类旅游资源价值评价——以长安-天山廊道路网中国段为例   总被引：3，自引：1，他引：2  

任唤麟 《地理科学》2017,37(10):1560-1568

跨区域线性文化遗产是一类特殊的旅游资源。基于其特殊性,以其各遗产点的价值评价作为整个遗产的价值评价;借助层次分析法、菲什拜因-罗森伯格模型,通过设定评分标准与评价等级,构建跨区域线性文化遗产旅游资源价值评价模型;实证分析认为提出的方法与模型能较准确地评价资源价值,长安-天山廊道路网中国段各遗产点价值均在优良等级及以上,其中27.3%为五级（特品级）资源,59.1%为四级资源,13.6%为三级资源,在旅游开发中应采取领先开发或重点开发、分区开发及加强遗产点历史文化挖掘与宣传普及等策略。  相似文献   

A linear tessellation model to identify spatial pattern in urban street networks     

Yakun He  Wenhao Yu  Xiang Zhang 《International journal of geographical information science》2017,31(8):1541-1561

Street patterns reflect the distribution characteristics of a street network and affect the urban structure and human behavior. The recognition of street patterns has been a topic of interest for decades. In this study, a linear tessellation model is proposed to identify the spatial patterns in street networks. The street segments are broken into consecutive linear units with equal length. We define five focal operations using neighborhood analysis to extract the geometric and topological characteristics of each linear unit for the purpose of grid-pattern recognition. These are then classified by Support Vector Machine, and the result is optimized based on Gestalt principles. The experimental results demonstrate that our method is effective for mining grid patterns in a street network.  相似文献   

关于发展人工影响天气数值模式的一些问题   总被引：3，自引：0，他引：3       下载免费PDF全文

许焕斌  尹金方 《Acta Meteorologica Sinica》2017,75(1):57-66

人工影响天气的学科基础是中小尺度天气动力学与云降水物理学,需要将天气-动力-云降水物理耦合为一体。考虑到目前将天气动力学性质的基础数值模式用于人工影响天气中的问题,从数值模式动力方程、模式分辨率、云物理过程、数值求解方案、初边值条件等方面系统地探索了发展人工影响天气数值模式中一些需要重点解决、且不可忽视的特色问题,并举例对相关问题提出了解决思路和方法。期望提出的问题有助于构思更适合于人工影响天气数值模式,使数值模式功能真正向满足人工影响天气的要求靠近一步。  相似文献   

Group K-Nearest Neighbors queries in spatial network databases     

Maytham Safar 《Journal of Geographical Systems》2008,10(4):407-416

This paper addresses the problem of Group K-Nearest Neighbors (GKNN) queries in spatial network databases, and suggests a novel approach based on real network distances. This approach essentially uses network Voronoi diagram properties together with a progressive incremental network expansion for determining the inner network distances that are needed to obtain GKNN queries.   相似文献   

基于神经网络方法的芦苇叶面积指数遥感反演   总被引：2，自引：0，他引：2  

陈健  倪绍祥  李云梅 《国土资源遥感》2008,(2):62-67

提出了一种从TM图像上获取芦苇冠层叶面积指数的方法:首先对芦苇的生长背景进行分类;然后,对不同的背景光谱利用冠层反射率(FCR)模型计算得到查找表;最后,利用实测数据和查找表中的数据作为参数进行BP神经网络模型训练,从而得到芦苇冠层LAI。结果表明,人工神经网络方法有很强的非线性拟合能力,能够消除背景对反演结果的影响,有效提高LAI反演的精度。  相似文献