分布式传感器网络系统的网络预测控制

本文针对分布式传感器网络系统的Fornasini-Marchesini （FM）状态空间模型,对系统的预测控制器设计问题进行研究.特别是针对所考虑的二维FM传感器网络系统,提出了一种新的网络预测控制方案来补偿通信时滞.首先,根据李雅普诺夫稳定性理论,给出了二维系统保持稳定的充分条件;然后利用稳定性条件,提出了一种新的预测控制器设计策略并保证系统的控制性能;最后,通过一个数值实例验证了所设计控制器的有效性.     

Towards automation of palynology 2: the use of texture measures and neural network analysis for automated identification of optical images of pollen grains

The automation of palynology (the identification and counting of pollen grains and spores) will be a small step for image recognition, but a giant stride for palynology. Here we show the first successful automated identification, with 100% accuracy, of a realistic number of taxa. The technique used involves a neural network classifier applied to surface texture data from light microscope images. A further significance of the technique is that it could be adapted for the identification of a wide range of biological objects, both microscopic and macroscopic. Copyright © 2004 John Wiley & Sons, Ltd.     

Evaluation and forecasting of daily groundwater outflow in a small chalky watershed

The purpose of this research is to include expert knowledge as one part of the modelling system and therefore offer the chance to create a productive interaction system between expert, mathematical model (MMO8) and artificial neural networks (ANNs). In the present project, the first objective is to determine some parameters by the MMO8 model, introduced as ANN input parameters to forecast spring outflow. The second objective is first to investigate the effect of temporal information by taking current and past data sets and then to forecast spring outflow. The good results obtained reveal the merit of the ANNs–MMO8 combination, and specifically multilayer perceptron (MLP) models. This methodology, for a network with lower, lag and number hidden layer, consistently produced better performance. Copyright © 2003 John Wiley & Sons, Ltd.     

Neural network and wavelet conjunction model for modelling monthly level fluctuations in Turkey

This paper proposes the application of a conjunction model (neuro‐wavelet) for forecasting monthly lake levels. The neuro‐wavelet (NW) conjunction model is improved combining two methods, discrete wavelet transform and artificial neural networks. The application of the methodology is presented for the Lake Van, which is the biggest lake in Turkey, and Lake Egirdir. The accuracy of the NW model is investigated for 1‐ and 6‐month‐ahead lake level forecasting. The root mean square errors, mean absolute relative errors and determination coefficient statistics are used for evaluating the accuracy of NW models. The results of the proposed models are compared with those of the neural networks. In the 1‐month‐ahead lake level forecasting, the NW conjunction model reduced the root mean square errors and mean absolute relative errors by 87–34% and 86–31% for the Van and Egirdir lakes, respectively. In the 6‐month‐ahead lake level forecasting, the NW conjunction model reduced the root mean square errors and mean absolute relative errors by 34–48% and 30‐46% for the Van and Egirdir lakes, respectively. The comparison results indicate that the suggested model could significantly increase the short‐ and long‐term forecast accuracy. Copyright © 2009 John Wiley & Sons, Ltd.     

SOFTWARE REVIEWS

software reviews are in this article BMDP/PC CONCEPTS COMPUTERIZED ATLAS EVALUATION OF ALTERNATE PROPOSALS (EAP) EXTRA: EXPRESS TRANSIT ANALYSIS MATC CAD MOTORS TRANSPORTATION PACKAGE PCMAP: Thematic Mapping Software for the IBM Personal Computer, Version 2.3 PLACE TRANPLAN . US-ATLAS     

Vulnerability,Partnerships and the Pursuit of Survival: Urban Livelihoods and Apprenticeship Contracts in a West African City

This paper analyses local level apprenticeship contracts and networks to highlight informal urban livelihoods within the context of socio-economic vulnerability and wider contemporary changes taking place in Koforidua, Ghana. It does so by specifically examining the complex entanglements of interpersonal relationships that characterize apprenticeship contracts within which home-based entrepreneurs and artisans in Koforidua engage in to sustain both current livelihoods, as well as to shore themselves against socio-economic vulnerability triggered in part by adjustment. As a result of the changing geography of the city, network entanglements, comprising resilient ties and egalitarian relations, have become vital to urban livelihoods in this community. However, apprenticeship contracts and the networks they engender can be a double-edged sword. For instance, demands of reciprocity or support from co-network members, neighbours and family, can be so taxing that some individuals opt out of the network. This tension notwithstanding, this paper contends that apprenticeship contracts and the network spaces they create have created a new social cohesion and community that transcend the traditionally known spaces of social support, i.e. ethnic ties, family ties or even institutional support.     

Automatic seismic wave detection and autoregressive model method

The problem of automatic detection of seismic waves by large telemetered seismic networks such as the Mexican Continental Aperture Seismic Network (RESMAC), is extended here to include determination of seismic first-arrival and S-phase-arrival times. A short general outline of the detection problem background and a small introduction to the autoregressive model (AR) concept are presented. Several automatic detection algorithms were implemented and compared with a newly developed autoregressive algorithm. Careful consideration of the advantages and disadvantages of each method determined that a mixed detection scheme is optimal and suitable for RESMAC. A few examples are shown that illustrate the relative performances of the methods tried here. The proposed detection scheme has the following characteristics: (a) First-arrival detection, based on a simple (average of squared input) characteristic function, and a trigger criterion that uses as a distortion measure the long-average-to-short-average ratio of the characteristic function, checked using a duration criterion; (b) use of two threshold values, one for triggering, and another for beginning the backward search for the phase arrival time; (c) use of the autoregressive model (AR) method, with the Itakura-Saito distortion measure, for S-phase detection, checked using both duration and amplitude criteria; and (d) characterization of the reliability of the determinations for their subsequent use in automatic location programs, alarms, etc. The automatic detection scheme has proved effective.     

Accessibility for High Asia： Comparative Perspectives on Northern Pakistan＇s Traffic Infrastructure and Linkages with Its Neighbours in the Hindukush-Karakoram- Himalaya

Starting with a discussion of development concepts which were applied in practice and which followed the developmentalist paradigm the expansion of traffic infrastructure in colonial and post-colonial periods is presented for the High Asian mountain rim. Selective railways and roads are the major feature of this development, which aimed first on serving the convenience of hill station visitors and followed strategic considerations later on. This bias between regional planning and implementation remains a characteristic feature. At the same time traffic infrastructure without asphalt roads is important for the mountain areas, thus breaking up the strong correlation between development and asphalt roads.     

下一代卫星网络关键技术研究进展

探讨了下一代卫星网络中关键技术的研究进展,主要包括路由策略、传输协议、移动性管理与QoS模型等几个方面,并对下一代卫星网络的研究热点和前景进行了总结和展望。     

Diverging Narratives: Evaluating the Uses of the Ideal-Typical Sequence of Transport Network Development

Abstract

The development of new transport systems has been an important and highly visible component of economic development and spatial reorganization in the past two centuries. The Ideal-Typical Sequence of network development has been a widely used model of transport development. This paper shows that this model has been used in several different ways, with different notions regarding the appropriate use, interpretation, and limitations of the model over time. Students must therefore think critically about ongoing changes to transport and communications systems and their impacts on economic and social conditions, as well as how these impacts are represented in models.