An optimum vehicular path algorithm for traffic network based on hierarchical spatial reasoning

Human beings' intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers' choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large-scale traffic networks.     

不确定混沌系统的反同步与参数辨识

针对一类混沌系统,提出了一种系统的混沌反同步设计方案,基于该方案,设计一种自适应控制方法,实现了参数不确定系统的混沌反同步和未知参数的辨识.数值模拟结果表明了提出方法的有效性.     

Novel pinning control strategies for synchronisation of complex networks with nonlinear coupling dynamics

This paper considers the global stability of controlling an uncertain complex network to a homogeneous trajectory of the uncoupled system by a local pinning control strategy. Several sufficient conditions are derived to guarantee the network synchronisation by investigating the relationship among pinning synchronisation, network topology, and coupling strength. Also, some fundamental and yet challenging problems in the pinning control of complex networks are discussed: (1) what nodes should be selected as pinned candidates? (2) How many nodes are needed to be pinned for a fixed coupling strength? Furthermore, an adaptive pinning control scheme is developed. In order to achieve synchronisation of an uncertain complex network, the adaptive tuning strategy of either the coupling strength or the control gain is utilised. As an illustrative example, a network with the Lorenz system as node self-dynamics is simulated to verify the efficacy of theoretical results.     

Estimating the parameters of forest inventory using machine learning and the reduction of remote sensing features

Locally computed statistics of image texture and a case-based reasoning (CBR) system were evaluated for mapping of forest attributes. Cluster analysis was preferred to regression models, as a pre-selection method of features. The best stand-based accuracy using satellite sensor images was 74.64 m⁻³ ha⁻¹ (36%) RMSE for stand volume, 1.98 m⁻³ ha⁻¹ a⁻¹ (49%) for annual increase in stand volume, where κ = 0.23 for stand growth classes and κ = 0.41 for dominant tree species in stands. The top pixel-based accuracy using orthophotos was 76.54 m⁻³ ha⁻¹ (41%) RMSE for stand volume, 1.87 m⁻³ ha⁻¹ a⁻¹ (44%) for annual increase in stand volume, where κ = 0.24 for stand growth classes and κ = 0.38 for dominant tree species in stands. Mean saturation in 30 m radius was the most useful feature when orthophotos were used, and standard deviation of Landsat ETM 6.2 values in 80 m radius was the best when satellite sensor images were used. The most valuable feature components (radii, channels and local statistics) for orthophotos were: 30 m kernel radius, lightness and the mean of pixel values; for satellite sensor images: 80 m kernel radius, near-infrared channel (ETM 4) and the mean of pixel values. Locally computed statistics.     

Ecological performance and possible origin of a ubiquitous but under-studied gastropod

Invasions by non-indigenous species (NIS) have been suggested to alter local, regional and global biota on unprecedented scales. To manage NIS, it is pivotal to identify whether a species is introduced or native, but even today the geographical origin of thousands of species worldwide remain uncertain. Most of these ‘cryptogenic species’ are inconspicuous and rare, but in a few instances, they can also be abundant and conspicuous species, with large impacts on community structure. The identification of cryptogenic species, and summarizing information on their most likely origin, is an important task in invasion biology, and can highlight the need for research and management. Here, we document that the gastropod Batillaria australis in the Swan River estuary (Perth, Western Australia) is a conspicuous species of uncertain origin. A literature review combined with new survey data revealed that all evidence point to a recent human-mediated transfer; for example, it is absent from the fossil record, was first collected in 1954, has a low parasite diversity, has increased its population size dramatically in recent times, is separated by >3000 km from conspecifics, has no long-distance dispersal mechanisms, and existing ocean currents run against a natural range extension. Surprisingly, despite political and scientific focus on NIS hardly any ecological data have been published on this species from Western Australia. We show that B. australis is highly abundant in both seagrass beds (424 ± 29 ind m⁻²) and on unvegetated sand flats (92 ± 22 ind m⁻²) being orders of magnitudes more abundant than any native gastropod in the Swan River. Experiments showed that high resistance to predation and environmental stress potentially explains its success. From our survey data, we calculated that >3.6 billion invasive snails today occupy the Swan River. This large snail populations support other organisms; for example, almost 1 billion macroalgae are found attached to living B. australis and >100 million hermit crabs occupy its empty shells. Given Battilaria’s high abundance, wide distribution, large size, persistent shells that support other organisms and bioturbating behavior, it seems inescapable that this potential invader has impacted the ecosystem functioning of the Swan River. We argue that the search for abundant species of uncertain origin should continue, and that these species generally should be treated with the same interest as high status invaders to mitigate impacts in already invaded systems and to avoid secondary spread into neighboring ecosystems.     

基于范例推理的山区公路滑坡治理方案决策模型

随着西部大开发的进行,将有更多的山区高等级公路有待建设.公路滑坡问题已经成为影响公路工程质量、建设时间和安全程度的关键因素.即将遇到的公路滑坡和已经治理完成的公路滑坡在发育机制、滑动模式及治理方式上有许多十分相似之处,若对每个滑坡都进行分析,研究制定其治理方法,就需投入大量的人力和财力.针对影响山区公路滑坡治理方案的决策因素的随机性和未知性,提出基于范例推理的山区公路滑坡治理方案决策模型,对模型的推理机制、山区公路滑坡范例库的建立和目标范例与源范例的相似度计算等问题进行了讨论.通过实例分析表明,模型是有效的.     

基于典型事例推理的路径规划方法研究

提出了把基于典型事例推理的智能方法应用到路径规划过程中。在结合道路网络知识的基础上,定义了典型事例,并基于事例进行了推理。实验结果表明,该算法减少了搜索空间,加快了搜索速度,并满足人们喜欢在熟悉路径上行驶的偏好。     

动态数据空间分析的不确定性问题——以城市中心识别为例

目的 动态数据在空间分析中存在不确定性问题。以手机定位数据为例来识别城市中心,探索可塑性面积单元问题和不确定的地理情境问题,发现群体活动强度的空间自相关程度受到采样区域划分方式和分析单元大小的影响,地理情境的时空动态变化也会带来不确定的地理情境问题。讨论了减轻不确定性的可能方法。     

短时交通预测的动态出行信息服务协同工作平台

目前,国内城市出行信息服务平台和网络地图平台主要提供静态信息服务,城市交通动态特征难以得到真实反映,对以时间和费用为主要准则的公众出行缺乏实用价值。本文提出了历史数据推理和微观交通仿真相结合,进行短时交通预测以服务公众出行的一种新方法设计了实时交通信息处理与发布服务器、GIS应用服务器与数据库管理系统三者协同工作的体系结构实现了顾及短时预测交通状况的公众出行路径规划过程,并作了验证。因此,为公众动态出行信息服务和动态网络电子地图的实现,提供了一个可行的解决方案。