基于KL-散度的电力用电数据自动脱敏算法研究

电力数据中包含一些隐私数据,一旦泄漏,就会对个人隐私安全造成隐患。为保证电力数据的安全性,提出了基于KL-散度设计电力用电数据自动脱敏算法。基于KL-散度算法建立敏感数据过滤模型,计算不同变量数据的KL距离,得到其相似性指标,对用户项目评分进行平滑处理,将具备相似性的敏感数据分成不同的批次。敏感数据去身份化处理,将数据匿名转换,计算用户真实路径被泄露的概率。设计数据自动脱敏算法,分别计算概念化数据、元组信息以及信息流的损失程度,以此判定脱敏后的数据是否可用。检验脱敏前后数据一致性,三类电力用电数据的变化率分别为0.43%、0.14%和0.11%,远远小于标准值。且算法在运行过程中单位时间处理数据量和平均延迟时间也较为理想,可见该脱敏算法具备实用性。

图形化编程平台运行算法的研究

主要通过可视化编程语言的研究 ,在开发面向虚拟仪器系统的图形化编程平台 (GPP)中提出了基于改进数据流语言的程序运行算法。该算法采用数据驱动的方式 ,实现了GPP元件的数据处理及元件之间的数据传递和数据类型转换等一套完善的运行机制。

列车运行自动控制(ATO)算法的研究

通过分析列车自动控制算法所面临的问题 ,提出了具有自适应、智能化的列车自动驾驶算法及推理机结构。

行车自动运行算法的应用和推广

主要论述了全自动电镀生产线的行车自动运行算法,通过对电镀生产线的自动化控制到电镀线的工艺,逐步深入到行车自动运行的算法。根据多年的编程的积累,对自动线算法进行了探讨,进而提高电镀生产线的生产效率,具有很高的实用性。

基于遗传算法的漫湾水电站厂内优化运行研究

运用MATLAB采用遗传算法对水电站厂内机组负荷分配情况进行模拟计算,在发电量满足调度要求并保证安全优质的情况下对机组负荷分配进行调整,优化机组运行使电站的耗流量减少;并对计算数据进行分析,研究峰谷负荷差对耗流量的影响。结果显示,峰谷负荷差对电站耗流量的影响可以做出定量的分析,该结论对于制定峰谷时差电价有一定指导意义,对于安排水电站优化运行,提高水电站运行效率有十分重要的现实意义。

对Apriori算法的改进及其实现研究

传统的关联规则挖掘Apriori算法时间开销大,针对Apriori算法的不足之处,基于关系代数理论,利用关系矩阵及相关运算给出了搜索频繁项集的基于关系代数理论的关联规则挖掘(ORAR)算法。利用关系矩阵只需扫描数据库一次,以降低算法运行时间,挖掘频繁项集,最后通过仿真实验比较这两个算法的执行时间,讨论了数据样本量和最小支持度对算法性能的影响。通过大量的仿真实验证明改进的ORAR算法是高效的,减少了挖掘数据集中频繁项集的运行时间。

基于归档集特性的自适应多目标粒子群优化算法

为了改善多目标粒子群算法收敛性能及跳出局部最优的能力,通过研究算法运行过程中归档集规模的变化,总结归档集规模的变化规律,并依此规律提出一种近似确定算法运行状态的简单方法。基于算法运行状态的近似确定,可以自适应调整参数。实验分析与比较结果显示,自适应方法能够有效地加速收敛,而且对于一些复杂问题有较好的跳出局部最优的能力。实验结果同时表明,近似确定算法状态的方法对于参数的调整是简单且有效的。

变速连续Petri网的性质及运行分析

给出了一种变速连续Ｐｅｔｒｉ网的定义及主要性质．详细阐述了其运行算法．在算法中主要考虑了对冲突的检测及处理．给出了一个示例，并通过仿真得到了其运行情况．

基于有向图的工作流建模及其运行

文章通过定义活动节点、有向边及活动的启动方式构建了基于有向图的工作流模型,利用此模型可以直观地、清晰地表达各种业务工作过程,以解决传统工作流模型在过程表达方面的不足;在此模型的基础上,构建了活动的状态集、状态函数、动作模型和条件模型,给出了活动的执行规则且详细描述了基于该规则的活动内部运行机制;在活动内部运行机制的基础上定义了工作流模型的运行算法。

化工机械制冷设备自动化调试技术的应用

化工机械制冷设备是化工生产中的重要工艺装置,自动化技术的应用极大地提高了其运行效果和经济效益。本文通过对一类化工机械制冷设备的现状和运行问题的分析,介绍了自动化调试技术在其中的应用。根据设备的工艺特性和调试需求,开发出一套以PLC为核心的自动化调试系统。该系统利用现场总线技术收集设备运行数据,通过高效的运行算法,实现制冷设备的自动启停、调节和故障诊断操作。实践应用表明,该技术不仅提高了制冷设备的运行稳定性和效率,降低了运维人员的工作强度,也在一定程度上节约了能耗。对于化工设备的自动化升级,尤其在当前的工业4.0背景下,本研究提供了有力的技术支持,并为制冷设备的进一步智能化奠定了基础。

小型微电网系统电能计量表自动化控制研究

小型微电网系统电能智能管理过程中,依靠基础的PID算法对电能计量表进行自动化控制,易受震荡作用影响,导致该控制模式下电能计量表的示值误差较大。因此,该文研究了一种新型小型微电网系统电能计量表自动化控制方法。考虑电能计量表工作原理,运用均值偏移算法实时跟踪计量表运行参数。建立CAN大数据通信协议,实现运行参数和控制指令的高质量传输。以PLC控制思想为核心,结合遗传优化PID整定算法搭建自动化控制框架。再引入多目标优化思想,完成对电能计量表多目标协同自动化控制。实验结果表明:应用新研究方法对电能计量表运行状态进行自动化控制后,远程自动抄表的示值误差不超过±0.5%,满足了电能计量的准确性要求。

实时阵列信号处理系统设计

根据实际项目需求设计了一种实时阵列信号处理系统,采用多路高速光纤作为数据输入、输出接口;4片处理器组成互联的拓扑结构,任何两片处理器之间都可以互相传送数据,多片处理器可同时对数据进行高速处理;系统配备了大容量存储器,可满足大量数据的存储要求;采用两片现场可编程门阵列器件对系统接口、时序进行控制;为每片处理器分配了处理任务,并对信号处理算法运行时间及数据传输时间进行评估。该系统已在实际项目中运行,充分满足项目要求,运行稳定,验证了本系统设计的可行性。

三角剖分问题

一、三角剖分的含义: 给定一个多边形的顶点以及任意两个顶点之间的距离(这里的距离可以是平面上的欧氏距离,也可是其它任意的度量函数。),所谓多边形的三角剖分就是要选出多边形的某些弦(两个不相邻的顶点间的连线),使得这些弦两两不相交,并且它们把整个多边形分成三角形。这些弦所构成的集合就称作多边形的一个三角剖分。在所有三角剖分中。

Road traffic states estimation algorithm based on matching of regional traffic attracters

To effectively solve the traffic data problems such as data invalidation in the process of the acquisition of road traffic states,a road traffic states estimation algorithm based on matching of the regional traffic attracters was proposed in this work.First of all,the road traffic running states were divided into several different modes.The concept of the regional traffic attracters of the target link was put forward for effective matching.Then,the reference sequences of characteristics of traffic running states with the contents of the target link's traffic running states and regional traffic attracters under different modes were established.In addition,the current and historical regional traffic attracters of the target link were matched through certain matching rules,and the historical traffic running states of the target link corresponding to the optimal matching were selected as the initial recovery data,which were processed with Kalman filter to obtain the final recovery data.Finally,some typical expressways in Beijing were adopted for the verification of this road traffic states estimation algorithm.The results prove that this traffic states estimation approach based on matching of the regional traffic attracters is feasible and can achieve a high accuracy.

Operational Modal Analysis of a Ship Model in the Presence of Harmonic Excitation

A ship is operated under an extremely complex environment, and waves and winds are assumed to be the stochastic excitations. Moreover, the propeller, host and mechanical equipment can also induce the harmonic responses. In order to reduce structural vibration, it is important to obtain the modal parameters information of a ship. However, the traditional modal parameter identification methods are not suitable since the excitation information is difficult to obtain. Natural excitation technique-eigensystem realization algorithm （NExT-ERA） is an operational modal identification method which abstracts modal parameters only from the response signals, and it is based on the assumption that the input to the structure is pure white noise. Hence, it is necessary to study the influence of harmonic excitations while applying the NExT-ERA method to a ship structure. The results of this research paper indicate the practical experiences under ambient excitation, ship model experiments were successfully done in the modal parameters identification only when the harmonic frequencies were not too close to the modal frequencies.

PV Power Short-Term Forecasting Model Based on the Data Gathered from Monitoring Network

The degree of accuracy in predicting the photovoltaic power generation plays an important role in appropriate allocations and economic operations of the power plants based on the generating capacity data gathered from the geographically separated photovoltaic plants through network. In this paper, a forecasting model is designed with an optimization algorithm which is developed with the combination of PSO （Particle Swarm Optimization） and BP （Back Propagation） neural network. The proposed model is further validated and the experiment results show that the predication model assures the prediction accuracy regardless the day type transitions and other relevant factors, in the proposed model, the prediction error rate is worth less than 20% in all different climatic conditions and most of the prediction error accuracy is less than 10% in sunny day, and whose precision satisfies the management requirements of the power grid companies, reflecting the significance of the proposed model in engineering applications.

A new clustering algorithm for large datasets

The Circle algorithm was proposed for large datasets.The idea of the algorithm is to find a set of vertices that are close to each other and far from other vertices.This algorithm makes use of the connection between clustering aggregation and the problem of correlation clustering.The best deterministic approximation algorithm was provided for the variation of the correlation of clustering problem,and showed how sampling can be used to scale the algorithms for large datasets.An extensive empirical evaluation was given for the usefulness of the problem and the solutions.The results show that this method achieves more than 50% reduction in the running time without sacrificing the quality of the clustering.

Peak shaving operation optimization of high proportion new energypower generation considering wind-solar complementationand source-load coupling

To optimize peaking operation when high proportion new energy accesses to power grid,evaluation indexes are proposed which simultaneously consider wind-solar complementation and source-load coupling.A typical wind-solar power output scene model based on peaking demand is established which has anti-peaking characteristic.This model uses balancing scenes and key scenes with probability distribution based on improved Latin hypercube sampling(LHS)algorithm and scene reduction technology to illustrate the influence of wind-solar on peaking demand.Based on this,a peak shaving operation optimization model of high proportion new energy power generation is established.The various operating indexes after optimization in multi-scene peaking are calculated,and the ability of power grid peaking operation is compared whth that considering wind-solar complementation and source-load coupling.Finally,a case of high proportion new energy verifies the feasibility and validity of the proposed operation strategy.

Fast wire segmenting algorithm considering layout density and signal integrity

A k-shortest path based algorithm considering layout density and signal integrity for good buffer candidatelocations is proposed in this paper. Theoretical results for computing the maximal distance betweenbuffers are derived under the timing, noise and slew rate constraints. By modifying the traditional uniformwire segmenting strategy and considering the impact of tile size on density penalty function, this work proposesk-shortest path algorithm to find the buffer insertion candidate locations. The experiments show thatthe buffers inserted can significantly optimize the design density, alleviate signal degradation, save thenumber of buffers inserted and the overall run time.

Task Assignment Problem of Robots in a Smart Warehouse Environment

The task assignment problem of robots in a smart warehouse environment （TARSWE） based on cargo-to-person is investigated. Firstly, the sites of warehouse robots and the order picking tasks are given and the task assignment problem for picking one order is formulated into a mathematical model to minimize the total operation cost. Then a heuristic algorithm is designed to solve the task assignment problem for picking multiple orders. Finally, simulations are done by using the orders data of online bookstore A. The results show that using the heuristic algorithm of this paper to assign robots, the cost was reduced by 2% and it can effectively avoid far route and unbalanced workload of robots. The feasibility and validity of the model and algorithm are verified. The model and algorithm in this paper provide a theoretical basis to solve the TARSWE.