预测人员震害损失的神经网络模型

随着区域经济的发展与城市化进程的加快,人口的集中度不断增加,这也给抗震防灾带来了新的课题。对地震中人员的损失进行有效的预测可为抗震防灾工作提供有力的管理方向。选择地震发生的震级、震源深度、震中烈度、设防水准、地震加速度、人口密度、地震预报等影响地震灾害人员伤亡的主要因素作为预测指标,以37次严重地震灾害为样本,建立了我国特征的BP神经网络地震灾害人员伤亡预测模型。     

用方差分析法预测濮阳市冬小麦播种期降水量趋势

使用1971-2000年濮阳市冬小麦播种期降水量资料,采用方差分析法,按不同长度周期进行排列,求出各个周期的F值,进行F检验定出第一周期,其位相值为第一周期的第一次值。将原序列减去第一周期的位相值作为新序列1,对新序列1再进行不同长度周期排列,求出各个周期的F值,再进行F检验定出第二周期。对第一、二周期进行稳定性检查,采用经稳定后的第一、二周期的第2次值各自外推,求出预报初值,计算出剩余方差,建立预报方程,进而可计算出降水量预报值。经回代检验,历史拟合率为30/30=100%;2001-2005年试报准确率为4/5=80%。     

Assessing the Impacts of Initial Snow Conditions over the Tibetan Plateau on China Precipitation Prediction Using a Global Climate Model

Two ensemble experiments were conducted using a general atmospheric circulation model. These experiments were used to investigate the impacts of initial snow anomalies over the Tibetan Plateau（TP） on China precipitation prediction. In one of the experiments, the initial snow conditions over the TP were climatological values; while in the other experiment, the initial snow anomalies were snow depth estimates derived from the passive microwave remote-sensing data. In the current study, the difference between these two experiments was assessed to evaluate the impact of initial snow anomalies over the TP on simulated precipitation. The results indicated that the model simulation for precipitation over eastern China had certain improvements while applying a more realistic initial snow anomaly, especially for spring precipitation over Northeast China and North China and for summer precipitation over North China and Southeast China. The results suggest that seasonal prediction could be enhanced by using more realistic initial snow conditions over TP, and microwave remote-sensing snow data could be used to initialize climate models and improve the simulation of eastern China precipitation during spring and summer. Further analyses showed that higher snow anomalies over TP cooled the surface, resulting in lower near- surface air temperature over the TP in spring and summer. The surface cooling over TP weakened the Asian summer monsoon and brought more precipitation in South China in spring and more precipitation to Southeast China during summer.     

一种基于AR 模型的预测滤波压制随机噪声方法

在地震勘探中,随机噪声是一类不可避免的噪声,它的存在极大地降低了地震资料的信噪比,导致偏移成像效果差甚至不能成像。自适应线性预测滤波方法是在时间--空间域自回归( AR) 模型系数变化的假定下,把自回归( AR) 模型数学表达式进行变换,引入代价函数以提高解的稳定性、唯一性,推导得到压制一维和二维随机噪声的递归算法。通过模拟和实际地震资料验证表明,该方法能较好地压制低信噪比资料中的随机噪声干扰,同时能较好地保护有效地震信号。     

基于前春对流层温度和北大西洋涛动的中国夏季降水统计预测模型

本文在分析中国夏季降水典型模态与前期春季对流层中上层温度主要分布类型、北大西洋涛动(简称NAO)之间关系的基础上,提出基于前春对流层温度和NAO的中国夏季降水统计预测模型,并对利用该模型预报的2004～2009年中国160站夏季降水进行检验.结果表明:中国大范围夏季降水多寡主要与5月NAO变化有关,“南多(少)北少(多...     

Potential use of model predictive control for optimizing the column flotation process

A constrained model predictive control (MPC) strategy is proposed to deal with the problem of optimizing flotation column operation using secondary variables. Froth depth, collection zone gas hold-up and bias rate are selected as secondary variables to be controlled whereas tailing, wash-water and gas flow rate are used as manipulated variables. The control problem was formulated in order to minimize the tracking error of the gas hold-up and bias rate by maintaining gas flow rate, wash-water flow rate and bias rate within their operational limits. In particular, a strategy was conceived to optimize the column flotation process based on establishing an unreachable high set point for the gas hold-up (which is equivalent to maximizing the bubble surface area available for particle collection at a given flotation reagent dosage and thus recovery), while simultaneously satisfying operational constraints (such as ensuring a positive bias rate to prevent gangue entrainment and therefore concentrate grade deterioration). Several other operational constraints on wash-water, gas rate, gas hold-up and bias rate were considered, their use being justified from a processing point of view. Since this study deals with the hydrodynamic characteristics of flotation columns, a pilot flotation column working with a two-phase system is sufficient to demonstrate the advantages of using predictive control for this process optimization.     

顾及线性化模型误差补偿的卡尔曼滤波算法

针对扩展卡尔曼滤波（EKF）线性化所产生的线性化模型误差问题,使用非线性预测滤波对线性化所引起的模型误差进行预测,并在标准EKF的解算过程中考虑到预测所得误差的统计特性,使模型更趋于真实情况。通过算例对改进算法的性能进行了验证。     

预测函数算法在同步发电机励磁系统中的应用

预测函数控制(Predictive Function Control)方法克服了传统预测控制算法复杂、在线计算量大的缺点,具有算法简单、计算量小、跟踪速度快和精度高等优点,适合同步发电机励磁等快速系统.介绍了预测函数控制(PFC)的基本原理和特点,成功地将预测函数控制算法运用到同步发电机励磁系统中.仿真结果表明:预测函数控制算法的控制效果明显优于PID和分数阶PID控制器,其对同步发电机启动时的机端电压、短路时的电压和断路时的电压等都能起到良好的控制作用.     

On the study of control effectiveness and computational efficiency of reduced Saint-Venant model in model predictive control of open channel flow

Model predictive control (MPC) of open channel flow is becoming an important tool in water management. The complexity of the prediction model has a large influence on the MPC application in terms of control effectiveness and computational efficiency. The Saint-Venant equations, called SV model in this paper, and the Integrator Delay (ID) model are either accurate but computationally costly, or simple but restricted to allowed flow changes. In this paper, a reduced Saint-Venant (RSV) model is developed through a model reduction technique, Proper Orthogonal Decomposition (POD), on the SV equations. The RSV model keeps the main flow dynamics and functions over a large flow range but is easier to implement in MPC. In the test case of a modeled canal reach, the number of states and disturbances in the RSV model is about 45 and 16 times less than the SV model, respectively. The computational time of MPC with the RSV model is significantly reduced, while the controller remains effective. Thus, the RSV model is a promising means to balance the control effectiveness and computational efficiency.     

川北地区铀成矿特征与成矿预测

川北地区是我国南方重要的砂岩型铀矿成矿带之一.文章通过区域地质背景和典型铀矿床研究,总结了该区的铀成矿规律,厘定了砂岩型铀矿区域预测要素.根据预测要素构置了区域预测变量,并应用特征分析法圈定18片预测区,为今后的总体找矿部署提供科学依据.