Multi-source coordinated stochastic restoration for SOP in distribution networks with a two-stage algorithm

After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s resilience. In this study, a multi-source coordinated load restoration strategy was investigated for a distribution network with soft open points(SOPs). Here, the flexible regulation ability of the SOPs is fully utilized to improve the load restoration level while mitigating voltage deviations. Owing to the uncertainty, a scenario-based stochastic optimization approach was employed,and the load restoration problem was formulated as a mixed-integer nonlinear programming model. A computationally efficient solution algorithm was developed for the model using convex relaxation and linearization methods. The algorithm is organized into a two-stage structure, in which the energy storage system is dispatched in the first stage by solving a relaxed convex problem. In the second stage, an integer programming problem is calculated to acquire the outputs of both SOPs and power resources. A numerical test was conducted on both IEEE 33-bus and IEEE 123-bus systems to validate the effectiveness of the proposed strategy.

A Tongue-images Segmentation Method Based on Local Restoration and Watershed Algorithm

Objective: To propose a method to segment tongue- images efficiently, and extract tongue- body accurately and quickly. Methods: Firstly, a kind of color- images' pre- processing technique was used to solve tongue- surface reflection problem. Neighbouring and similar region's information was used to restore the region with tongue- surface reflection problem by replacement. Secondly, the restored image was transformed into a gray one, and then processed by mathematical morphological operation- dilation to get a closed- loop edge. The third technique used was watershed algorithm, which is an usual tool in image segmentation. 'Watershed' function of matlab software was used to complete this algorithm. After that, region- combination technique was used. Through measuring neighbourship and similarity of regions, a non- objective and non- background region was merged into one of its neighbouring regions. This step was repeated until only two regions, objective and background regions, were left in the image. At last, corresponding to the merged image, tongue- body image was got from the original image. Results: 316 images were randomly taken from the image library for experiments, and 299 images were correctly segmented, so, the successful ratio is 94.62%. On the other hand, average time of running this method was about 50 s under whole sampling environment. Conclusion: The method presented in this paper can segment a tongue- body image from its original one effectively, and thus laying a good foundation for the following analysis work.

Image Restoration of Depth of Field Extension Imaging System Based on Genetic Algorithm

Genetic algorithm is a search algorithm based on genetic mechanism and natural selection. It has been widely applied to research fields including image processing field. The paper improves standard genetic algorithm and improves the arithmetic speed of the algorithm, which achieves better image restoration effect. And the paper compares the image restoration quality of traditional algorithm, standard genetic algorithm and improved genetic algorithm to prove the feasibility of applying genetic algorithm to image restoration.

PRECESION： progressive recovery and restoration planning of interdependent services in enterprise data centers

The primary focus of this paper is to design a progressive restoration plan for an enterprise data center environment following a partial or full disruption. Repairing and restoring disrupted components in an enterprise data center requires a significant amount of time and human effort. Following a major disruption, the recovery process involves multiple stages, and during each stage, the partially recovered infrastructures can provide limited services to users at some degraded service level. However, how fast and efficiently an enterprise infrastructure can be recovered de- pends on how the recovery mechanism restores the disrupted components, considering the inter-dependencies between services, along with the limitations of expert human operators. The entire problem turns out to be NP- hard and rather complex, and we devise an efficient meta-heuristic to solve the problem. By considering some real-world examples, we show that the proposed meta-heuristic provides very accurate results, and still runs 600-2800 times faster than the optimal solution obtained from a general purpose mathematical solver [1].

SOFT COMPUTING APPROACH FOR NOISY IMAGE RESTORATION

A genetic learning algorithm based fuzzy neural network was proposed for noisy image restoration, which can adaptively find and extract the fuzzy rules contained in noise. It can efficiently remove image noise and preserve the detail image information as much as possible. The experimental results show that the proposed approach is able to performa far better than conventional noise removing techniques.

An Inexact Restoration Package for Bilevel Programming Problems

Bilevel programming problems are a class of optimization problems with hierarchical structure where one of the con-straints is also an optimization problem. Inexact restoration methods were introduced for solving nonlinear programming problems a few years ago. They generate a sequence of, generally, infeasible iterates with intermediate iterations that consist of inexactly restored points. In this paper we present a software environment for solving bilevel program-ming problems using an inexact restoration technique without replacing the lower level problem by its KKT optimality conditions. With this strategy we maintain the minimization structure of the lower level problem and avoid spurious solutions. The environment is a user-friendly set of Fortran 90 modules which is easily and highly configurable. It is prepared to use two well-tested minimization solvers and different formulations in one of the minimization subproblems. We validate our implementation using a set of test problems from the literature, comparing different formulations and the use of the minimization solvers.

Optimal Dynamic Voltage Restorer Using Water Cycle Optimization Algorithm

This paper proposes a low complexity control scheme for voltage control of a dynamic voltage restorer(DVR)in a three-phase system.The control scheme employs the fractional order,proportional-integral-derivative(FOPID)controller to improve on the DVR performance in order to enhance the power quality in terms of the response time,steady-state error and total harmonic distortion(THD).The result obtained was compared with fractional order,proportionalintegral(FOPI),proportional-integral-derivative(PID)and proportional-integral(PI)controllers in order to show the effectiveness of the proposed DVR control scheme.A water cycle optimization algorithm(WCA)was utilized to find the optimal set for all the controller gains.They were used to solve four power quality issues;balanced voltage sag,balanced voltage swell,unbalanced voltage sag,and unbalanced voltage swell.It showed that one set of controller gain obtained from the WCA could solve all the power quality issues while the others in the literature needed an individual set of optimal gain for each power quality problem.To prove the concept,the proposed DVR algorithm was simulated in the MATLAB/Simulink software and the results revealed that the four optimal controllers can compensate for all the power quality problems.A comparative analysis of the results in various aspects of their dynamic response and%THD was discussed and analyzed.It was found that PID controller yields the most rapid performance in terms of average response time while FOPID controller yields the best performance in term of average%steady-state error.FOPI controller was found to provide the lowest THD percentage in the average%THD.FOPID did not differ much in average response from the PID and average%THD from FOPI;however,FOPID provided the most outstanding average steady-state error.According to the CBMA curve,the dynamic responses of all controllers fall in the acceptable power quality area.The total harmonic distortion(THD)of the compensated load voltage from all the controllers were within the 8%limit in accordance to the IEEE std.519-2014.

基于L-R非线性迭代的降质图像复原算法

为克服图像传输和获取过程中受模糊、失真等因素影响所造成的图像降质,提出一种基于L-R非线性迭代的降质图像复原算法。建立图像退化和恢复模型,并给出复原图像的评价测度。仿真实验结果表明,与传统的维纳滤波相比,该算法在存在多种随机噪声的情况下,能达到较好的图像复原效果。

应用改进自蛇模型和L-R算法恢复毫米波图像

在毫米波的图像恢复中,L-R算法是一种简单而有效的非线性方法,但当噪声不可忽略时,L-R算法难以获得较好的复原结果。针对毫米波图像数据量少和图像分辨率低的特点,提出基于改进自蛇模型和L-R算法毫米波图像恢复方法,以局部方差构造自蛇模型的边缘停止函数,其改进自蛇模型在消除噪声的同时更能够保留图像中的边缘和细节特征,然后使用L-R算法进行图像恢复,这种改进算法通过使用基于改进自蛇模型去噪能有效地减少噪声对L-R算法的影响。实验结果表明:在信噪比和相关度方面本文算法提高了L-R算法的性能,可用于含噪声的图像复原。

Non-Restoring开方算法及FPGA实现

简单介绍了开方运算的Non-Restoring算法,并对该算法的实现问题进行了深入研究。与其他一些算法相比,该算法具有计算过程简单、结果准确等优点。基于特定专用集成电路(ASIC)和VHDL语言,给出了用现场可编程门阵列(FPGA)实现该算法的一种方案。

A Compound Algorithm of Denoising Using Second-Order and Fourth-Order Partial Differential Equations

In this paper, we propose a compound algorithm for the image restoration. The algorithm is a convex combination of the ROF model and the LLT model with a parameter function 0. The numerical experiments demonstrate that our compound algorithm is efficient and preserves the main advantages of the two models. In particular, the errors of the compound algorithm in L2 norm between the exact images and corresponding restored images are the smallest among the three models. For images with strong noises, the restored images of the compound algorithm are the best in the corresponding restored images. The proposed algorithm combines the fixed point method, an improved AMG method and the Krylov acceleration. It is found that the combination of these methods is efficient and robust in the image restoration.

Algorithm for repairing the damaged images of grain structures obtained from the cellular automata and measurement of grain size

Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical incon- sistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidifica- tion, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed al- gorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.

An Algorithm for the Inverse Problem of Matrix Processing: DNA Chains, Their Distance Matrices and Reconstructing

We continue to consider one of the cybernetic methods in biology related to the study of DNA chains. Exactly, we are considering the problem of reconstructing the distance matrix for DNA chains. Such a matrix is formed on the basis of any of the possible algorithms for determining the distances between DNA chains, as well as any specific object of study. At the same time, for example, the practical programming results show that on an average modern computer, it takes about a day to build such a 30 × 30 matrix for mnDNAs using the Needleman-Wunsch algorithm;therefore, for such a 300 × 300 matrix, about 3 months of continuous computer operation is expected. Thus, even for a relatively small number of species, calculating the distance matrix on conventional computers is hardly feasible and the supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains, then we publish algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. Previously, we used the method of branches and boundaries, but in this paper we propose to use another new algorithm for restoring the distance matrix for DNA chains. Our recent work has shown that even greater improvement in the quality of the algorithm can often be achieved without improving the auxiliary heuristics of the branches and boundaries method. Thus, we are improving the algorithms that formulate the greedy function of this method only. .

Three-Dimensional Scenes Restore Using Digital Image

Encryption and decryption method of three-dimensional objects uses holograms computer-generated and suggests encoding stage. Information obtained amplitude and phase of a three-dimensional object using mathematically stage transforms overlap stored on a digital computer. Different three-dimensional images restore and develop the system for the expansion of the three-dimensional scenes and camera movement parameters. This article talks about these kinds of digital image processing algorithms as the reconstruction of three-dimensional model of the scene. In the present state, many such algorithms need to be improved in this paper proposing one of the options to improve the accuracy of such reconstruction.

A Regularized Randomized Kaczmarz Algorithm for Large Discrete Ill-Posed Problems

Tikhonov regularization is a powerful tool for solving linear discrete ill-posed problems.However,effective methods for dealing with large-scale ill-posed problems are still lacking.The Kaczmarz method is an effective iterative projection algorithm for solving large linear equations due to its simplicity.We propose a regularized randomized extended Kaczmarz(RREK)algorithm for solving large discrete ill-posed problems via combining the Tikhonov regularization and the randomized Kaczmarz method.The convergence of the algorithm is proved.Numerical experiments illustrate that the proposed algorithm has higher accuracy and better image restoration quality compared with the existing randomized extended Kaczmarz(REK)method.

A New Genetic Algorithm Based Upon Globally Optimal Choosing and Its Practices

A new genetic algorithm (GA) is developed. It features three new operations: restoration, reconstruction and recording the better, so as to produce a limited monotonic sequence of fitness value, to realize a globally optimal choosing, and to converge to a globally optimal solution through a perfectly stochastic process. Practical examples are given to illustrate the superiority of this new GA.

Numerical Comparisons of Different Imaging Algorithms

Image processing is the set of operations performed to extract “information” from the image. An interesting problem in digital image processing is the restoration of degraded images. It often happens that the resulting image is different from the expected image. Our problem will therefore be to recover an image close to the original image from a poor quality image (that has been skewed by Gaussian and additive noise). There are several algorithms on how we can improve the broken image in better quality. We present in this paper our numerical results obtained with the models of Tikhonov regularization, ROF, Vese Osher, anisotropic and isotropic TV denoising algorithms.

基于边缘检测的数字媒体深度交互式图像分割算法

针对数字媒体深度交互式图像受噪声干扰,导致其边缘检测效果较差,影响其分割精度的问题,提出基于边缘检测的数字媒体深度交互式图像分割算法。首先,利用小波变换方法对数字媒体中的图像进行去噪处理,提高图像分割精度;其次,使用高斯函数与低通滤波增强去噪后的图像,提高图像的清晰度,为图像分割提供便利;最后,依据自适应阈值算法对数字媒体的图像进行边缘检测,像素合集中存在上下阈值。根据其上下阈值的计算求出像素合集中的高低两个阈值,并对其实施边缘连接,实现数字媒体图像分割。实验结果表明,所提方法对分割数字媒体图像去噪效果好,分割精度和效率高。

基于区域分割和DM642的数字图像修复系统研究

由于数字图像中颜色通道之间关联性显著,改变某颜色分量,会导致剩余分量随之变化,使数字图像整体视觉效果出现变化,针对该问题,文中研究基于区域分割和DM642的数字图像修复系统。将DM642处理器作为系统核心处理器,在该处理器协助下,针对破损数字图像采用基于分通道自体理论的数字图像区域分割方法,利用图像颜色信息和像素间的空间关系,实现图像修复区域分割。针对需修复区域,通过基于Criminisi算法的数字图像修复方法提取修复像素点生成修复块,利用图像自相似性,在未破损区域找到与修复块匹配度最高的样本块,用此样本填充修补破损区域。实验结果表明,此系统能够有效分割数字图像的修复区域,修复视觉效果较好,且修复后数字图像不存在明显失真问题,可实现多图像并行快速修复。

基于Criminisi算法的四经绞罗纹样修复研究

文章针对古代罗织物受到诸多因素影响而产生破损、难以提取修复这一问题,提出了一种结合开运算和Criminisi算法的图像修复方法。收集具有规律性特征的四经绞罗传统纹样,用图谱分析法分析最具代表性的菱形纹,使用原算法和开运算改进过的Criminisi算法,对图像进行剪裁,得出掩膜,计算优先权后进行纹样填充,完成了四经绞罗规律型图样的数字化修复。结果表明,经过开运算改进的Criminisi算法弥补了原算法的不足,修复后的图像和原算法修复的相比更加清晰平滑,验证了此算法修复四经绞罗纹样的可行性与可信性,为罗织物的传承和修复提供了较为可靠的方法。