动态导航交通信息服务平台系统

随着通信技术、网络技术的快速发展,车辆导航技术正逐步向动态网络导航演进．本文通过分析目前动态导航交通信息服务平台存几个主要薄弱的技术问题,提出层次化的动态导航交通信息服务平台总体框架．该框架由数据供应层、动态导航信息服务层、通信层和用户层组成．本文研究平台的总体框架、软件体系结构、数据库的建立和发布协议等主要关键技术．建立实现了B／S与C／S混合模式的交通信息服务技术平台．     

建基岩体开挖前后的声波曲线特性及其成因分析

自然斜坡在形成演化过程中,受区域构造、河谷下切、地壳隆升以及外部营力(如风化卸荷)作用,加之岩体物理力学特性等多种地质环境因素影响,可在岸坡浅表层(由表及里)形成应力释放区、应力调整区和原始地应力稳定区;但在岸坡(建基)岩体人工开挖过程中,由于爆破扰动及岩体瞬间卸荷等影响,以上应力分区将重新波动调整。声波VP作为评价岩体质量优劣的一个重要指标,因具备简便、快速、准确、可靠等特点得到了广泛应用与发展。现就此以前期勘探平硐声波测试及开挖坝面岩体质量单孔声波检测结果为基础,讨论建基岩体开挖前后波速曲线的形态特征以及应力分区分布范围,并分析导致曲线形态的地质原因,以期为坝基开挖及后续声波监测工作等提供一定的科学依据。     

南水北调中线小南河串流片防洪水位计算

传统的多河流串流计算主要采用水库联调的方法,把串流的各条河流概化为静态水库,库水位水平且不考虑横向流动。为解决串流区水流的横向流动及水面线并不总像库水位一样水平的问题,采用二维非恒定流数学模型计算串流区洪水演进。通过概化地形、考虑入流、糙率、边界条件和水流的横向流动等因素,计算出了整个串流区域的水面线、水深、流速、出流等水力要素,并给出洪水演进模拟图,为确定河流与总干渠交叉建筑物的规模、总干渠左岸沿线水面线和对沿线村庄、农田的防洪影响提供了可靠的依据。     

A method for stochastic multiple criteria decision making based on dominance degrees

This paper proposes a method for solving the stochastic multiple criteria decision making (SMCDM) problem, where consequences of alternatives with respect to criteria are represented by random variables with probability distributions. Firstly, definitions and related analysis of dominance degree of one probability distribution over another are given. Then, by calculating the dominance degrees, the dominance degree matrix of alternative pairwise comparisons with respect to each criterion is built. Further, using PROMETHEE II method, an overall dominance degree matrix of alternative pairwise comparisons is constructed, and a net flow of each alternative is calculated. Based on the obtained net flows, a ranking of alternatives is determined. Finally, numerical examples for the three cases are given to illustrate the use of the proposed method.     

Univariate marginal distribution algorithm dynamics for a class of parametric functions with unitation constraints

In this paper, we introduce a mathematical model for analyzing the dynamics of the univariate marginal distribution algorithm (UMDA) for a class of parametric functions with isolated global optima. We prove a number of results that are used to model the evolution of UMDA probability distributions for this class of functions. We show that a theoretical analysis can assess the effect of the function parameters on the convergence and rate of convergence of UMDA. We also introduce for the first time a long string limit analysis of UMDA. Finally, we relate the results to ongoing research on the application of the estimation of distribution algorithms for problems with unitation constraints.     

Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains

In the real-world manufacturing/distribution planning decision (MDPD) integration problems in supply chains, the environmental coefficients and parameters are normally imprecise due to incomplete and/or unavailable information. This work presents a fuzzy linear programming approach based on the possibility theory. It applies this approach to solve multi-product and multi-time period MDPD problems with imprecise goals and forecast demand by considering the time value of money of related operating cost categories. The proposed approach attempts to minimize the total manufacturing and distribution costs by considering the levels of inventory, subcontracting and backordering, the available machine capacity and labor levels at each source, forecast demand and available warehouse space at each destination. This study utilizes an industrial case study to demonstrate the feasibility of applying the proposed approach to practical MDPD problems. The primary contribution of this paper is a fuzzy mathematical programming methodology for solving the MDPD integration problems in uncertain environments.     

Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China

Productive wetland systems at land-water interfaces that provide unique ecosystem services are challenging to study because of water dynamics, complex surface cover and constrained field access. We applied object-based image analysis and supervised classification to four 32-m Beijing-1 microsatellite images to examine broad-scale surface cover composition and its change during November 2007-March 2008 low water season at Poyang Lake, the largest freshwater lake-wetland system in China (> 4000 km²). We proposed a novel method for semi-automated selection of training objects in this heterogeneous landscape using extreme values of spectral indices (SIs) estimated from satellite data. Dynamics of the major wetland cover types (Water, Mudflat, Vegetation and Sand) were investigated both as transitions among primary classes based on maximum membership value, and as changes in memberships to all classes even under no change in a primary class. Fuzzy classification accuracy was evaluated as match frequencies between classification outcome and a) the best reference candidate class (MAX function) and b) any acceptable reference class (RIGHT function). MAX-based accuracy was relatively high for Vegetation (≥ 90%), Water (≥ 82%), Mudflat (≥ 76%) and the smallest-area Sand (≥ 75%) in all scenes; these scores improved with the RIGHT function to 87-100%. Classification uncertainty assessed as the proportion of fuzzy object area within a class at a given fuzzy threshold value was the highest for all classes in November 2007, and consistently higher for Mudflat than for other classes in all scenes. Vegetation was the dominant class in all scenes, occupying 41.2-49.3% of the study area. Object memberships to Vegetation mostly declined from November 2007 to February 2008 and increased substantially only in February-March 2008, possibly reflecting growing season conditions and grazing. Spatial extent of Water both declined and increased during the study period, reflecting precipitation and hydrological events. The “fuzziest” Mudflat class was involved in major detected transitions among classes and declined in classification accuracy by March 2008, representing a key target for finer-scale research. Future work should introduce Vegetation sub-classes reflecting differences in phenology and alternative methods to discriminate Mudflat from other classes. Results can be used to guide field sampling and top-down landscape analyses in this wetland.     

New statistical methods for investigating submarine pockmarks

We investigate the applicability of some novel spatial analysis techniques, developed for studies of astrophysical datasets, to the analysis of spatial point data in sedimentary basins. The techniques are evaluated and compared with standard methods using two test areas that contain large numbers of submarine pockmarks developed in distributed arrays. The familiar Ripley K and Voronoi tesselation techniques are used, and the results are then compared with those obtained using more novel techniques, the correlation length and minimal spanning tree. The correlation length technique is found to identify the precise distances at which clustering occurs more accurately, making a physical interpretation more clear than is possible using the Ripley K. The minimal spanning tree is found to be powerful at identifying the space-filling nature of the pockmark distribution, and has the advantage of being immune to edge effects. The use of these two novel techniques permits more information to be extracted from the datasets, and demonstrates clear statistically significant differences between them, which are not detectable using standard techniques.     

QoS-based cooperative algorithm for integral multi-commodity flow problem

This paper treats with integral multi-commodity flow through a network. To enhance the Quality of Service (QoS) for channels, it is necessary to minimize delay and congestion. Decreasing the end-to-end delay and consumption of bandwidth across channels are dependent and may be considered in very complex mathematical equations. To capture with this problem, a multi-commodity flow model is introduced whose targets are minimizing delay and congestion in one model. The flow through the network such as packets, also needs to get integral values. A model covering these concepts, is NP-hard while it is very important to find transmission strategies in real-time. For this aim, we extend a cooperative algorithm including traditional mathematical programming such as path enumeration and a meta-heuristic algorithm such as genetic algorithm. To find integral solution satisfying demands of nodes, we generalize a hybrid genetic algorithm to assign the integral commodities where they are needed. In this hybrid algorithm, we use feasible encoding and try to keep feasibility of chromosomes over iterations. By considering some random networks, we show that the proposed algorithm yields reasonable results in a few number of iterations. Also, because this algorithm can be applied in a wide range of objective functions in terms of delay and congestion, it is possible to find some routs for each commodity with high QoS. Due to these outcomes, the presented model and algorithm can be utilized in a variety of application in computer networks and transportation systems to decrease the congestion and increase the usage of channels.