A threshold model of social contagion process for evacuation decision making

Individual evacuation decisions are often characterized by the influence of one’s social network. In this paper a threshold model of social contagion, originally proposed in the network science literature, is presented to characterize this social influence in the evacuation decision making process. Initiated by a single agent, the condition of a cascade when a portion of the population decides to evacuate has been derived from the model. Simulation models are also developed to investigate the effects of community mixing patterns and the initial seed on cascade propagation and the effect of previous time-steps considered by the agents and the strength of ties on average cascade size. Insights related to social influence include the significant role of mixing patterns among communities in the network and the role of the initial seed on cascade propagation. Specifically, faster propagation of warning is observed in community networks with greater inter-community connections.     

The GRAAL of carpooling: GReen And sociAL optimization from crowd-sourced data

Carpooling, i.e. the sharing of vehicles to reach common destinations, is often performed to reduce costs and pollution. Recent work on carpooling takes into account, besides mobility matches, also social aspects and, more generally, non-monetary incentives. In line with this, we present GRAAL, a data-driven methodology for GReen And sociAL carpooling. GRAAL optimizes a carpooling system not only by minimizing the number of cars needed at the city level, but also by maximizing the enjoyability of people sharing a trip. We introduce a measure of enjoyability based on people’s interests, social links, and tendency to connect to people with similar or dissimilar interests. GRAAL computes the enjoyability within a set of users from crowd-sourced data, and then uses it on real world datasets to optimize a weighted linear combination of number of cars and enjoyability. To tune this weight, and to investigate the users’ interest on the social aspects of carpooling, we conducted an online survey on potential carpooling users. We present the results of applying GRAAL on real world crowd-sourced data from the cities of Rome and San Francisco. Computational results are presented from both the city and the user perspective. Using the crowd-sourced weight, GRAAL is able to significantly reduce the number of cars needed, while keeping a high level of enjoyability on the tested data-set. From the user perspective, we show how the entire per-car distribution of enjoyability is increased with respect to the baselines.     

A multi-class model-based control scheme for reducing congestion and emissions in freeway networks by combining ramp metering and route guidance

The paper proposes a multi-class control scheme for freeway traffic networks. This control scheme combines two control strategies, i.e. ramp metering and route guidance, in order to reduce the total time spent and the total emissions in a balanced way. In particular, the ramp metering and route guidance controllers are feedback predictive controllers, i.e. they compute the control actions not only on the basis of the measured system state, but also on the basis of the prediction of the system evolution, in terms of traffic conditions and traffic emissions. Another important feature of the controllers is that they have a multi-class nature: different classes of vehicles are considered and specific control actions are computed for each class. Since the controllers are based on a set of parameters that need to be tuned, the overall control framework also includes a module to properly determine the gains of the controllers. The simulation analysis reported in the paper shows the effectiveness of the proposed control framework and, in particular, the possibility of implementing control policies that are specific for each vehicle type.     

Carrying Capacity Reliability of Railway Networks

The railway network carrying reliability refers to the carrying capacity meeting the OD demand which consciously changed with random and irresistible factors under prescribed conditions and stated time. Based on reviewing the domestic and international achievement of carrying capacity reliability research and analyzing the characteristics of railway transportation, the paper presents the definition of the carrying capacity reliability of railway network. Then, a model for railway network capacity calculation is developed and the approach for reliability determination is proposed. In the final section, a numerical experiment is conducted with different levels of OD demand. The result shows that the fluctuation of OD demand directly affects the carrying capacity of railway networks, and the effective control of fluctuation plays a positive role for a good performance of railway networks.     

多层反馈混沌神经网络及其在交叉口优化控制中的应用

研究城市交叉口交通控制信号优化配时问题。以Hopfield网络和混沌模型为基础,开发了多层反馈混沌神经网络,将其应用于城市交通控制信号配时优化,并开发了应用于优化计算的能量函数和车辆平均延误计算式;探讨了城市交通系统的混沌特性,并开发混沌定量判别算法。以广东某交叉路口为对象进行了仿真,结果表明:与传统的配时方法相比,采用所开发的多层反馈混沌神经网络进行优化配时,交叉路口车辆的平均延误可以平均减少25.1%,可以大大提高路口的通行效率。该网络也可以应用于其他对象的优化。     

基于神经网络的部分预应力混凝土梁荷载-裂缝模型研究

混凝土结构裂缝形成和发展的过程十分复杂，具有一定的随机性，难于用常规的方法进行建模。应用神经网络较强的函数映射能力和联想、记忆功能，对部分预应力混凝土梁的荷载－裂缝关系进行建模，通过试验数据进行验证，效果良好，证明应用神经网络来对部分预应力混凝土梁的荷载－裂缝关系进行建模是可行的。     

广义Gauss模型及其模拟退火算法

研究了求解优化问题全局解的随机神经网络方法，将Gauss模型拓展为广义Gauss模型，使之能求解一般优化问题的全局解。进而引入全局性较好的模拟退火算法的思想，提出了广义Gauss模型的模拟退火算法。通过算例比较了几种计算智能算法的全局性。广义Gauss模型的模拟退火运行全局性最好，但它付出了时间的代价；广义Gauss模型兼顾了计算效率和全局性；广义Hopfield网络的全局性最不理想。     

TCP Upload and Download Fairness over IEEE 802.11 Wired-cum-Wireless Heterogeneous Networks

IntroductionThe interaction between wireless and wired net-works is becoming important with the growth ofdeployment of wireless networks. Gopal andRaychaudhuri[1]investigated the TCP simultaneous-send problem in infrastructure mode 802.11 wirelesslocal ar…     

星型数据网络通信仿真分析

就专网中的星形数据网推导出数学排队模型,并进行计算机仿真,得到相应的网络性能参数,对星形数据网的运行具有指导性意义。     

舰炮武器系统保障性神经网络评价模型及分析

针对舰炮武器系统保障性评价问题,根据其保障性内涵,运用BP神经网络,建立了舰炮武器系统的保障性评价模型,给出了研制阶段舰炮武器系统保障性定性与定量相结合的评估方法,克服了以往定性评价方法的模糊性和不确定性,能更准确地为舰炮武器的保障性设计提供依据。并以多种型号舰炮武器系统为例,对其保障性进行了评价。计算结果说明该方法可有效地用于舰炮武器系统的保障性评价。