基于扩展卡尔曼滤波的测量系统数据分析

为消除误差和随机干扰对测量数据的影响。利用扩展卡尔曼滤波算法对测量数据进行处理,并提出基于扩展卡尔曼滤波算法的不可信点判断方法对测量数据进行野值剔除。两种方法结合运用,可以在保留数据特征的基础上,提高数据的精度,更好地反映测量目标的性能。     

Intelligent tool wear monitoring based on parallel residual and stacked bidirectional long short-term memory network

Effective tool wear monitoring (TWM) is essential for accurately assessing the degree of tool wear and for timely preventive maintenance. Existing data-driven monitoring methods mainly rely on complex feature engineering, which reduces the monitoring efficiency. This paper proposes a novel TWM model based on a parallel residual and stacked bidirectional long short-term memory (PRes–SBiLSTM) network. First, a parallel residual network (PResNet) is used to extract the multi-scale local features of sensor signals adaptively. Subsequently, a stacked bidirectional long short-term memory (SBiLSTM) network is used to obtain the time-series features related to the tool wear characteristics. Finally, the predicted tool wear value is outputted through a fully connected network. A smoothing correction method is applied to improve the prediction accuracy. The proposed model is experimentally verified to have a high prediction accuracy without sacrificing its generalization ability. A TWM system framework based on the PRes–SBiLSTM network is proposed, which has a certain reference value for TWM in actual industrial environments.     

A parallel micro evolutionary algorithm for heterogeneous computing and grid scheduling

This work presents a novel parallel micro evolutionary algorithm for scheduling tasks in distributed heterogeneous computing and grid environments. The scheduling problem in heterogeneous environments is NP-hard, so a significant effort has been made in order to develop an efficient method to provide good schedules in reduced execution times. The parallel micro evolutionary algorithm is implemented using MALLBA, a general-purpose library for combinatorial optimization. Efficient numerical results are reported in the experimental analysis performed on both well-known problem instances and large instances that model medium-sized grid environments. The comparative study of traditional methods and evolutionary algorithms shows that the parallel micro evolutionary algorithm achieves a high problem solving efficacy, outperforming previous results already reported in the related literature, and also showing a good scalability behavior when facing high dimension problem instances.     

The interprocedural analysis and automatic parallelization of Scheme programs

Lisp and its descendants are among the most important and widely used of programming languages. At the same time, parallelism in the architecture of computer systems is becoming commonplace. There is a pressing need to extend the technology of automatic parallelization that has become available to Fortran programmers of parallel machines, to the realm of Lisp programs and symbolic computing. In this paper we present a comprehensive approach to the compilation of Scheme programs for shared-memory multiprocessors. Our strategy has two principal components:interprocedural analysis andprogram restructuring. We introduceprocedure strings andstack configurations as a framework in which to reason about interprocedural side-effects and object lifetimes, and develop a system of interprocedural analysis, using abstract interpretation, that is used in the dependence analysis and memory management of Scheme programs. We introduce the transformations ofexit-loop translation andrecursion splitting to treat the control structures of iteration and recursion that arise commonly in Scheme programs. We propose an alternative representation for s-expressions that facilitates the parallel creation and access of lists. We have implemented these ideas in a parallelizing Scheme compiler and run-time system, and we complement the theory of our work with snapshots of programs during the restructuring process, and some preliminary performance results of the execution of object codes produced by the compiler.This work was supported in part by the National Science Foundation under Grant No. NSF MIP-8410110, the U.S. Department of Energy under Grant No. DE-FG02-85ER25001, the Office of Naval Research under Grant No. ONR N00014-88-K-0686, the U.S. Air Force Office of Scientific Research under Grant No. AFOSR-F49620-86-C-0136, and by a donation from the IBM Corportation.     

Parallel heap: An optimal parallel priority queue

We describe a new parallel data structure, namely parallel heap, for exclusive-read exclusive-write parallel random access machines. To our knowledge, it is the first such data structure to efficiently implement a truly parallel priority queue based on a heap structure. Employing p processors, the parallel heap allows deletions of (p) highest priority items and insertions of (p) new items, each in O(log n) time, where n is the size of the parallel heap. Furthermore, it can efficiently utilize processors in the range 1 through n.This work was supported by U.S. Army's PM-TRADE contract N61339-88-g-0002, Florida High Technology and Industry grant 11-28-716, and Georgia State University's internal research support during spring and summer quarters, 1991.     

基于五层十五级遥感数据结构的并行算法研究

针对当前环境与监测预报小卫星宽覆盖和海量数据显示与处理不足的现状,设计五层十五级遥感数据组织结构,并依据此结构设计一种新的并行计算算法,得到并行计算的最大近优估算值,优化环境与监测预报小卫星海量数据的遥感产品生产能力,提高环境监测预报效率。     

基于并行遗传算法的配送路线求解

遗传算法(Genetic Algorithm)是一类借鉴生物界的进化规律演化而来的随机化搜索方法,已经成功运用在很多大规模的组合优化问题中。利用如今流行的并行计算机系统,对遗传算法进行并行化,可解决标准遗传算法的速度瓶颈问题。本文在MPI并行环境下,用C++语言实现了粗粒度模型的并行遗传算法。结合并行遗传算法的特点,提出了解决物流配送路线优化的策略以及给出相应的算法过程,并进行了有效验证。通过研究结果表明,与传统遗传算法相比,并行遗传算法提高了运算速度,降低了平均开销时间并且最小总路径值更理想。     

鸟体动力学本构模型参数反演的并行优化技术

研究鸟体本构模型的动力学过程,是飞行器抗鸟撞,保证飞行安全的重要问题。由于鸟体模型参数难确定,为得到准确而合理的鸟体参数,在已知鸟体本构模型的前提下,采用并行优化技术对本构参数进行反演。将鸟撞平板的试验结果与数值仿真结果的相对误差平方和最小作为目标函数,将待反演的鸟体参数作为设计变量,在同一撞击速度范围内,将鸟撞不同靶板分为不同工况构造并行优化反演模型。把反演得到的鸟体参数代回到鸟撞平板仿真模型中检验,经与试验结果对比,效果较好,表明采用的并行优化技术是有效的、可靠的。并行优化反演技术的实现为更准确的获取鸟体参数提供了新的思路和方法,也为提高飞行器抗鸟撞设计研究提供有益参考。     

并行计算在光线追踪中的应用

目前,计算机图形学的技术包括有光栅化,光线追踪,辐射度3种主流算法.而光线追踪又以其绘制的真实感性及实现的方便性,受到了广泛的应用.但光线追踪的最大问题在于性能.围绕光线追踪中的核心算法-射线与三角形相交算法展开讨论,引入基于Intel TBB并行编程工具的线程级并行技术以及基于SIMD的指令并行技术,提高其算法的速度.其加速技术可以使光线跟踪的性能在计算机多核的情况下,相对于串行跟踪方法有明显的改善.     

关于Photoshop插件的SAR图像处理探究

SAR图像处理主要包括相干斑抑制、特征提取等,如果在使用Photoshop插件SAR图像处理图片,将主要精力集中于算法的设计和优化方面,可以尽量减少在用户界面、内存管理和基本的图像操作方面的编程,既可以实现多种图像处理,又容易实现功能的充分扩大与填充,从而在最短的时间内做做多的事。