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。     

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...     

Stochastic wave energy calculation formulation

The wave energy potential is directly proportional to the wave period and second power of wave height averaged over a suitable time period. The wave height and period have temporal and spatial stochastic variations. It is the main purpose of this paper to derive the most general wave energy formulation by considering simultaneously the temporal variations both in the wave height and period. The correction factor is derived explicitly in terms of cross-correlation and the coefficients of variation. The application of the methodology is performed for wave measurement stations located in the Pacific Ocean off the west coast of the US.     

溶胶-凝胶法制备草酸二甲酯加氢Cu/SiO2催化剂及性能

以正硅酸乙酯为硅源,采用溶胶-凝胶法制备草酸二甲酯加氢合成乙二醇的Cu/SiO₂催化剂,并考察老化时间对Cu/SiO₂催化剂活性与结构的影响。用N2物理吸附、XRD、FT-IR和H₂-TPR等技术对Cu/SiO₂催化剂性能与结构进行表征。结果表明,溶胶-凝胶法制备的Cu/SiO₂催化剂中有层状硅酸铜形成,铜物种均匀分布在载体SiO₂上,易被还原,活性较高。合理的老化时间可抑制SiO₂对催化剂表面活性位的包覆,提高活性。在200 ℃、2.0 MPa、氢酯物质的量比60∶1、草酸二甲酯空速1.0 h^-1和老化时间1.5 h的条件下,草酸二甲酯转化率达99.51%,乙二醇选择性93.60%。
     

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.     

3种氨基酸铜螯合物的稳定常数测定研究

报道了利用722型分光光度计,采用等物质的量系列法,测定3种氨基酸铜螯合物一系列变化组合的溶液的吸光度A。以溶液的吸光度A与铜的物质的量分数f作出连续变化曲线,可求出3种氨基酸(甘氨酸、赖氨酸、蛋氨酸)分别与铜离子螯合的组成配比(n≈2)和计算出3种氨基酸铜螯合物的稳定常数。