一种修正的电阻层析成像Landweber迭代算法

研究了灵敏度矩阵更新的Landweber迭代图像重建算法,以期提高重建图像精度。灵敏度矩阵更新时的初始图像由Landweber迭代法获得,对不同迭代次数的灵敏度矩阵更新间隔进行了比较,并且对灵敏度矩阵的更新次数进行了分析,仿真及实验结果表明,该方法能有效提高图像重建精度。     

基于改进半阈值迭代算法的ECT图像重建

针对电容层析成像逆问题求解存在病态性和欠定性的问题,将压缩感知理论应用到成像过程中缓解其欠定性.首先将初始信号稀疏化处理,其次基于高斯随机阵对灵敏度矩阵的各行重新排列,随后进行奇异值分解得到了列独立性更高的观测矩阵.最后将基于l1/2-范数的半阈值迭代算法引入到ECT成像过程中,并在罚函数中加入l2-范数的约束项,通过...     

基于SVM的ECT图像重建算法

电容层析成像（ECT）技术是基于电容敏感机理的过程层析成像技术。ECT的图像重建是一个典型的有限样本非线性映射问题。支持向量机（SVM）作为一种小样本处理方法,具有较强的泛化能力,被认为是目前针对小样本分类问题的最佳理论。提出了一种基于SVM的四层神经网络的图像重建算法,仿真结果表明,该算法用于三相流图像重建具有较强的空间分辨率和泛化能力。     

基于改进SR3模型算法的ECT图像重建研究

针对电容层析成像技术应用于气固两相流检测时,图像重建过程中存在的不适定性问题,提出一种稀疏松弛正则化回归模型(SR3)应用于ECT图像重建。采用软阈值迭代法和梯度下降法为SR3模型求解器,向SR3模型中加入L1、L2惩戒项,并设计滤值环节优化解向量。实验结果表明,改进SR3模型算法相比Tikhonov正则化算法、L1正则化算法及原SR3模型算法,重建图像精度明显提高,图像相对误差显著降低,有较好的成像效果。     

基于迭代函数系统的分形算法及其应用

给出了基于迭代函数系统的分形内插管法控制系数的一个计算公式，并将其机制随机化，同时，给出了模拟平面分形图的一个新算法，结合两种算法，对四川丹凤场气田阳新统断层的分布进行了计算机模拟，其结果对油气勘察开发有一定实际意义。     

多相流参数的测量技术

本介绍了多相流参数的测量技术,该技术可以很好地实现管内油气水三相流的流量、速度、压力降和相份额等重要设计参数的测量,对进一步实现油气水三相流的在线测量有重要意义。     

ERT技术图像重建算法研究

两相流参数测量中,电阻层析成像技术的图像重建算法可归为两大类,即直接法和迭代法。对常用的几种图像重建算法进行了比较性研究,结果表明:直接法速度快,但重建图像质量不理想,仅可作定性分析;迭代法总体上说重建图像质量较高,但速度较慢。当增加像素数以提高重建图像分辨率时,直接法重建图像耗时增量较小,迭代型算法中改进的Newton-Raphson算法、BFGS算法由于目标函数的Hessian矩阵维数增加,计算时间大大增加,而改进的BFGS算法因简化了Hessian矩阵及其逆矩阵的计算,时间增量则较小。     

非线性耦合系统的变分迭代算法

本文提出了求解非线性耦合系统的一种迭代算法,这种方法是应用广泛拉氏乘子构造较正泛函,然后用变分理论最佳识别。这种方法对初近似不敏感,也没有“小参数”的限制,可广泛用于非线性振动问题。     

多相流计量撬在塔里木油田的应用

为了解决高含硫化氢试采单井计量误差大、人员操作风险高问题,2011年塔里木油田在某试采单井引进多相流计量撬,本文详细介绍了多相流计量撬的组成及工作原理并对其操作的可行性及结果的可靠性进行了验证。     

基于小波变换的CT/ECT图像融合方法

在基于工业CT及ECT的多相流参数测量中,CT所得重建图像分辨率较高,但由于其投影角度较少,重建图像边缘出现失真;对于ECT 系统,由于其敏感场软场特性,其重建图像分辨率较低,但图像边缘保真度高。基于二者的互补特性,研究了CT/ECT图像融和方法,提出了改进的逻辑滤波器算法应用于小波变换的低频系数融合规则,结果表明该方法可提高融合后的重建图像质量。     

A Refined Global Segmentation of X-Ray CT Images for Multi-phase Geomaterials

X-ray computed tomography images of three-phase silica sand and glass bead specimens are analyzed and used to evaluate the segmentation performances of Otsu-, and recursion-based multilevel algorithms. A global image segmentation technique that combines iterative and recursive algorithms, namely a refined statistics-based global segmentation is proposed for segmenting multi-phase granular geomaterials. The performance of the proposed algorithm is tested by segmenting partially saturated silica sand and glass bead specimens. For the tested silica sand specimen, the refined statistics method estimated void ratio and degree of saturation were 0.67 and 39.35%. The estimates for the glass bead specimen yielded 0.64 and 43.49%, respectively. The true void ratio (0.66) and degree of saturation (37.71%) were determined with a user-controlled Image processing software package—Image-Pro. It was found that the proposed method estimated the void ratio and the degree of saturation with 1.52 and 4.35 percent errors for the silica sand and with 15.63 and 0.34 percent errors for the glass bead, respectively. The computational time of the proposed method was found to be shorter than other methods considered. Overall, it is concluded that the proposed technique performed better in segmenting three-phase granular geomaterials.     

一个制造网络的最大流算法

制造网络流广泛应用于解决水源的调度及上厂的产品运输、分配、合成等问题。本文提出一个制造网络流的最大流算法。     

A Branch-and-Bound Algorithm for Flow Shop Scheduling Problems

This article is concerned with the solution of the flow shop scheduling problem in which all jobs have the same machine ordering. A branch-and-bound algorithm is developed for finding the sequence of J jobs to be processed on M machines which minimizes the schedule time. Thib algorithm consists of branching and bounding processes, but without the backtracking process which guarantees optimality. The procedure employed is that in constructing a subset of feasible sequences, a node representing a partial sequence is branched. Selection of the node depends on the lower-bound concept as a decision rule. This lower bound is based on resolving the conflict of jobs on the last machine. By using this algorithm, the number of explored nodes is considerably reduced and, hence, the computational effort involved in obtaining an optimal or near-optimal solution is decreased. High quality of solutions is obtained. Computationally, this algorithm extends the size of problems that can reasonably be solved.     

求解混合互补问题的一种内点算法

针对混合互补问题,提出了一种在数值上具有稳健性质的内点算法,并证明了其收敛性定理,数值例子表明这一算法是有效的。     

工业过程迭代学习算法的鲁棒性

在工业过程稳态优化进程中,为了进一步改善工业过程的动态品质,提出了迭代学习控制策略。本文研究系统状态初值漂移和系统参数扰动对迭代学习控制算法收敛性的影响。理论分析表明,当系统状态初值漂移和系统参数扰动在一定范围内,迭代学习控制算法关于是鲁棒的。     

A Greedy Network Flow Algorithm for A Warehouse Leasing Problem

In this paper we consider the problem of a firm which must lease warehouse space over a finite planning horizon. Demand for space in each time period is a random variable with known density function. The firm contracts for warehouse space for each time period at the beginning of the planning horizon via a primary contract. If demand exceeds space in any period, additional space can be obtained via a secondary contract. The leasing problem is shown to be equivalent to a linear programming problem under reasonable assumptions. The dual to the linear program is shown to be equivalent to a network flow problem which can be solved via a greedy algorithm, and admits a rather simple primal variable recovery procedure. Computational evidence indicates that dual problems with some 200,000 arcs can be solved efficiently.     

动态CT脑灌注影像后处理算法

分析了动态CT脑灌注影像定量测量的相关理论基础。设计实现了实用的医学影像后处理算法,通过量化分析动态CT脑灌注检查所获得的影像序列可测量出脑组织的血流灌注量,绘制出一系列的时间密度曲线,进而分析、计算出相关的脑血流动力学参数,得到具有临床诊断价值的功能影像。临床病例测试表明,该算法的计算机实现对于正确诊断急性脑缺血等早期脑部急性病症,具有十分显著的辅助作用。     

A New Optimal Iterative Algorithm for Solving Nonlinear Poisson Problems in Heat Diffusion

The nonlinear Poisson problems in heat diffusion governed by elliptic type partial differential equations are solved by a modified globally optimal iterative algorithm (MGOIA). The MGOIA is a purely iterative method for searching the solution vector x without using the invert of the Jacobian matrix D. Moreover, we reveal the weighting parameter αc in the best descent vector w = αcE + DTE and derive the convergence rate and find a criterion of the parameter γ. When utilizing αc and γ, we can further accelerate the convergence speed several times. Several numerical experiments are carefully discussed and validated the proposed method.     

混合流程型企业主生产计划的启发式算法

提出了一个新的启发式算法,该启发式算法称为多目标主生产计划算法(MOMPS),用于解决混合流水线车间的主生产计划安排,该启发式算法主要有以下目标:最小化拖期惩罚,最小化完工时间,最小化装设和库存成本等.该算法先对所有的定单进行排序,然后根据最小生产成本树及其该树的最大生产能力进行定单的分配,如果定单数量超出了最大生产能力,对生产网络进行调整,通过比较次优生产成本树和拖期以后的最小生产成本决定定单是否该拖期.最后通过和一般的线性规划进行比较,得出该算法在解决混合流程型企业的多目标主生产计划的制定中十分有效,有时得到的结果和线性规划模型解出的解是一致的.