Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.     

基于软件定义网络和移动边缘计算的车联网高效任务卸载方案

随着车联网(IoV)中车辆和智能应用数目的增加使计算密集型任务激增,传统架构难以满足用户需求。为解决车联网计算资源不足且分配不均匀、应用时延需求无法满足、任务能耗成本较高的问题,结合移动边缘计算(MEC)和软件定义网络(SDN),设计了一种从宏基站到MEC服务器到车辆的车联网架构中的高效任务卸载方案,并提出一种改进的低复杂度非支配排序遗传算法,优化任务卸载成本和MEC服务器的负载均衡率。实验仿真结果表明,相比于随机卸载,NO-MEC卸载,NO-I卸载,传统NSGA、NSGA-Ⅱ卸载,GA卸载,Q-learning卸载,DQN卸载方案,所提方案有着更低的卸载成本,更优的负载均衡率,得到近似最高的系统效用,能够给车联网中的车辆用户带来更优质的网络服务。     

基于控制网关的环境舒适性检测系统

随着互联网信息技术的发展,智能家居得到普及应用,如何检测并评价家居环境的舒适性非常重要。建立一个系统将环境检测模块和无线传感节点加载到控制网关上,实现方便、快捷的网络信息交互,用户可以随时随地了解家庭环境状况,并能通过该检测系统及时采取自调节措施,使偏离的环境状况趋向设定值。该检测系统能够保证内部网络通讯实时可靠,实现环境参数的有效采集和控制,为后续环境舒适性指标的平衡评测提供可靠的载体。     

Trend Assessment by the Innovative-Şen Method

Hydro-meteorological time series may include trend components mostly due to climate change since about three to four decades. Trend detection and identification in a better and refined manner are among the major current research topics in water resources domain. Even though different methodologies can be found for trend detection in literature, two well-known procedures are the Mann-Kendall (MK) trend test and recently innovative-?en trend method, which provides different aspects of the trend. The theoretical basis and application of these two methods are completely different. The MK test gives a holistic monotonic trend without any categorization of the time series into a set of clusters, but the innovative-?en method is based on cluster and provides categorical trend behavior in a given time series. The main purpose of this paper is to provide important differences between these two approaches and their possible similarities. The applications of the two approaches are given for hydro-meteorological records including relative humidity, temperature, precipitation and runoff from Ergene drainage basin in the north-western part of Turkey. It is observed that although MK trend test does not show significant trend almost in all the cases, the innovative-?en approach yields trend categorizations as “very low”, “low”, “medium” “high” and “very high”, which should be taken into consideration in future flood (“very high”) and drought (“very low”) studies.     

混合MIDC馈入下的工频变化量阻抗方向保护 动作特性分析

交流电网故障引发线路换相换流器高压直流(Line Commutated Converter High Voltage Direct Current, LCC-HVDC)换相失败,改变了原有交流电网工频变化量方向保护动作特性。针对这一问题,建立了由电压源换流器高压直流(Voltage Source Converter HVDC, VSC-HVDC)系统与LCC-HVDC系统组成的混合多馈入直流(bybrid multi-infeed HVDC,HMIDC)输电系统模型,并与馈入同一交流电网的单条LCC-HV     

载体对Li-Mn氧化物催化甲烷氧化偶联反应作用

采用浸渍法制备不同金属氧化物载体负载的Li-Mn/MO_x(M=Mg,La,Ti,Si,Zr,Ta)催化剂,对其甲烷氧化偶联反应活性进行评价。结果表明,以TiO_2为载体制备的Li-Mn/TiO_2催化剂具有较高的CH_4转化率和C2烃选择性,C_2烃产率显著提高,金属氧化物TiO_2是Li-Mn复合氧化物的优良催化剂载体。n(Li)∶n(Mn)=1.0∶2.0形成的Li-Mn/TiO_2催化剂具有最高的CH_4转化率和C_2烃选择性,n(C_2H_4)∶n(C_2H_6)的增加有助于提高反应产物中C_2H_4的相对浓度,W元素的添加未能进一步提高Li-Mn/TiO_2催化剂的催化活性。Li-Mn/TiO_2催化剂在n(Li)∶n(Mn)=1.0∶2.0、反应温度775℃、反应压力0.1 MPa、V(CH_4)∶V(O_2)=2.5、空速7 200 m L·(h·g)~(-1)和催化剂用量0.5 g条件下,CH_4转化率达31.9%,C_2选择性达52.7%,表现出最佳催化效果。     

ZSM-5/堇青石整体催化剂对NO低温氧化的催化性能

采用原位水热合成技术,以蜂窝状堇青石陶瓷为载体,分别合成了硅铝比为300的高硅和纯硅的ZSM-5分子筛/堇青石整体催化剂,并采用X射线衍射(XRD)和扫描电镜(SEM)等手段对催化剂进行了表征,考察了反应温度、水汽含量和空速等对NO氧化反应的影响.结果表明:在硅铝比为300的ZSM-5/堇青石和纯硅ZSM-5/堇青石整...     

Contour diagram fuzzy model for maximum surface ozone prediction

A contour diagram approach is presented for the identification of surface ozone concentration feature based on a set of rules by considering the meteorological variables such as the solar radiation, wind speed, temperature, humidity and rainfall. A fuzzy rule system approach is used because of the imprecise, insufficient, ambiguous and uncertain data available. The contour diagrams help to identify qualitative ozone concentration variability rules which are more general than conventional statistical or time series analysis. In the methodology, ozone concentration contours are based on a fixed variable as ozone precursor, namely, NO_x and as the third variable one of the meteorological factors. Such contour diagrams for ozone concentration variation are prepared for six months. It is possible to identify the maximum ozone concentration episodes from these diagrams and then to set up the valid rules in the form of IF-THEN logical statements. These rules are obtained from available daily ozone, NO_x and meteorological data as a first approximate reasoning step. In this manner, without mathematical formulations, expert maximum ozone concentration systems are identified. The application of the contour diagram approach is performed for daily ozone concentration measurements on European side of Istanbul city. It is concluded that through approximate reasoning with fuzzy rules, the maximum ozone concentration episodes can be identified and predicted without any mathematical expression.