Random Low Patch⁃rank Method for Interpolation of Regularly Missing Traces

Assuming seismic data in a suitable domain is low rank while missing traces or noises increase the rank of the data matrix,the rank⁃reduced methods have been applied successfully for seismic interpolation and denoising.These rank⁃reduced methods mainly include Cadzow reconstruction that uses eigen decomposition of the Hankel matrix in the f⁃x(frequency⁃spatial)domain,and nuclear⁃norm minimization(NNM)based on rigorous optimization theory on matrix completion(MC).In this paper,a low patch⁃rank MC is proposed with a random⁃overlapped texture⁃patch mapping for interpolation of regularly missing traces in a three⁃dimensional(3D)seismic volume.The random overlap plays a simple but important role to make the low⁃rank method effective for aliased data.It shifts the regular column missing of data matrix to random point missing in the mapped matrix,where the missing data increase the rank thus the classic low⁃rank MC theory works.Unlike the Hankel matrix based rank⁃reduced method,the proposed method does not assume a superposition of linear events,but assumes the data have repeated texture patterns.Such data lead to a low⁃rank matrix after the proposed texture⁃patch mapping.Thus the methods can interpolate the waveforms with varying dips in space.A fast low⁃rank factorization method and an orthogonal rank⁃one matrix pursuit method are applied to solve the presented interpolation model.The former avoids the singular value decomposition(SVD)computation and the latter only needs to compute the large singular values during iterations.The two fast algorithms are suitable for large⁃scale data.Simple averaging realizations of several results from different random⁃overlapped texture⁃patch mappings can further increase the reconstructed signal⁃to⁃noise ratio(SNR).Examples on synthetic data and field data are provided to show successful performance of the presented method.

Weakness Ranking Method for Subsystems of Heavy-Duty Machine Tools Based on FMECA Information

Heavy-duty machine tools are composed of many subsystems with different functions,and their reliability is governed by the reliabilities of these subsystems.It is important to rank the weaknesses of subsystems and identify the weakest subsystem to optimize products and improve their reliabilities.However,traditional ranking methods based on failure mode effect and critical analysis(FMECA)does not consider the complex maintenance of products.Herein,a weakness ranking method for the subsystems of heavy-duty machine tools is proposed based on generalized FMECA information.In this method,eight reliability indexes,including maintainability and maintenance cost,are considered in the generalized FMECA information.Subsequently,the cognition best worst method is used to calculate the weight of each screened index,and the weaknesses of the subsystems are ranked using a technique for order preference by similarity to an ideal solution.Finally,based on the failure data collected from certain domestic heavy-duty horizontal lathes,the weakness ranking result of the subsystems is obtained to verify the effectiveness of the proposed method.An improved weakness ranking method that can comprehensively analyze and identify weak subsystems is proposed herein for designing and improving the reliability of complex electromechanical products.

基于病例组合指数校正抗菌药物使用强度的模型拟合研究

目的:探究病例组合指数与抗菌药物使用强度之间的关联关系,并对抗菌药物使用的评价进行调整,对其综合考量。方法:收集安徽省某三甲医院2021-2023年病例组合指数与抗菌药物相关指标,首先通过线性模型、二次曲线等8种模型拟合探索病例组合指数与抗菌药物相关指标之间的关系,随后通过秩和比综合评价法对不同科室间抗菌药物的使用情况重新评价。结果:病例组合指数与抗菌药物使用强度之间关联性较弱,但病例组合指数与同期出院人数的乘积与抗菌药物使用累积数存在较强关联,以此为基础进行的秩和比综合评价结果前后出现较大波动。结论:病例组合指数与抗菌药物使用强度之间存在间接关联,在后续抗菌药物使用的模型运算时应考虑校正,以增强评价结果的真实性。

基于pairwise的改进ranking算法

传统基于pairwise的ranking算法,学习后得到的模型在用NDCG这样的ranking标准评价时效果并不好,对此提出了一种新型ranking算法。该算法也是使用样本对作为训练数据,但定义了一个面向NDCG评估标准的目标函数。针对此目标函数非平滑、难以直接优化的特点,提出使用割平面算法进行学习,不仅解决了上述问题,而且使算法迭代的次数不再依赖于训练样本对数。最后基于基准数据集的实验证明了算法的有效性。

A personalized trustworthy service selection method

A personalized trustworthy service selection method is proposed to fully express the features of trust, emphasize the importance of user preference and improve the trustworthiness of service selection. The trustworthiness of web service is defined as customized multi-dimensional trust metrics and the user preference is embodied in the weight of each trust metric. A service selection method combining AHP （analytic hierarchy process） and PROMETHEE （preference ranking organization method for enrichment evaluations） is proposed. AHP is used to determine the weights of trust metrics according to users＇ preferences. Hierarchy and pairwise comparison matrices are constructed. The weights of trust metrics are derived from the highest eigenvalue and eigenvector of the matrix. to obtain the final rank of candidate services. The preference functions are defined according to the inherent characteristics of the trust metrics and net outranking flows are calculated. Experimental results show that the proposed method can effectively express users＇ personalized preferences for trust metrics, and the trustworthiness of service ranking and selection is efficiently improved.

Weighted-Tau Rank:一种采用加权Kendall Tau的面向排序的协同过滤算法

已知的面向排序的协同过滤算法主要有两个缺点:计算用户相似度时只考虑用户对同一产品对的偏好是否一致,而忽略了用户对产品对的偏好程度以及该偏好在用户间的流行度;进行偏好融合和排序时需要中间步骤来构建价值函数然后才能利用贪婪算法产生推荐列表。为解决上述问题:我们利用类TF-IDF加权策略对用户的偏好程度及偏好流行度进行综合考量,使用加权的Kendall Tau相关系数计算用户间的相似度;进行偏好融合与排序时则使用基于投票的舒尔茨方法直接产生推荐列表。在两个电影数据集上,本文提出的算法在评测指标NDCG上的效果要明显优于其他流行的协同过滤算法。

PageRank算法的二级加速优化方案

为有效提高搜索引擎中网页排序的效率,针对当今PageRank算法优化方案的加速效果仍无法满足高速增长的网络规模所带来的数据处理需求现状,提出一种二级加速优化方法。对网络图邻近矩阵实行预处理,将其原点平移转化为等效矩阵,实现对幂法收敛速度的一级加速;提出一种改进的Aitken加速算法,应用到等效矩阵的幂法计算中,实现二级加速。实例仿真计算结果表明,改进的Aitken算法将原算法加速效率提升约25%,二级加速后的PageRank算法将原算法的求解效率提升约60%,优于类似优化方案加速效果。

Using a process-oriented methodology to precisely evaluate temperature suitability for potato growth in China using GIS

A process-oriented methodology to conduct precise evaluation temporally and spatially on temperature suitability for potato growth was applied in China. Arable lands in China were gridded with 1 km×1 km geographic units, and potential potato phenology in each unit was automatically identified in terms of the potato planting initial temperature and effective accu- mulated temperature. A temperature thermal response coefficient model was used to compute a temperature suitability value for each day of potato phenology in each geographic unit. In addition, five temperature suitability ranking methods were applied to define suitable areas： （1） upper fourth quantile, （2） median, （3） expected value＋1/4 standard deviation, （4） expected value＋1/2 standard deviation, （5） expected value＋1 standard deviation. A validation indicator was innovated to test the effectiveness of the five ranking methods. The results showed that from a strict degree point of view, the five methods sequence was as follows： 1=3〉4〉2〉5, with a and c determined as the two best ranking methods. For methods 1 and 3, the suitable potato growing area was 1 of 57.76× 10^4 km2. In addition, the suitable, areas were spatially coincident with the main potato producing counties. The study output technically supports the proposal from China＇s government that there is a large potential area to grow winter-ploughed potato in South China because the potential suitable area for growing potato is approximately 2×10^7 ha. In southeast Heilongjiang and east Jilin, where it is hilly and mountainous, there are still some potentially suitable areas for potato growing accounting for nearly 2.32×10^6 ha. The authors suggest to optimize the agricultural regionalization and layout in China and to adjust the cropping pattern structure.

Ranking important nodes in complex networks by simulated annealing

In this paper, based on simulated annealing a new method to rank important nodes in complex networks is presented.First, the concept of an importance sequence（IS） to describe the relative importance of nodes in complex networks is defined. Then, a measure used to evaluate the reasonability of an IS is designed. By comparing an IS and the measure of its reasonability to a state of complex networks and the energy of the state, respectively, the method finds the ground state of complex networks by simulated annealing. In other words, the method can construct a most reasonable IS. The results of experiments on real and artificial networks show that this ranking method not only is effective but also can be applied to different kinds of complex networks.

Log rank检验的功效

目的:L og rank检验是生存资料比较的标准方法,但无与之匹配的样本量测定方法。论述了这种检验的功效,为样本量研究提供依据。方法:由L ach in-Fou lkes法计算期望功效作为参照,回顾L og rank检验的3种形式,按M on te C arlo方法分别计算其观测功效,然后作对比分析。结果:所得观测功效在多数试验集均低于期望功效。与上半部相比,寿命表下半部期望和观测功效均较低。所得观测功效在不同终检水平或不同生存分布各不相同。结论:L ach in-Fou lkes法产生的样本量偏小,不能满足L og rank检验的预定功效。L og rank检验所需样本量因终检水平、生存时间或生存分布而异,L ach in-Fou lkes法无视这些事实,无法作出切合实际的测定,因此必须寻求与这种检验匹配的样本量测定方法。

Log rank检验所需样本量的测定:迭代非中心法

目的:提出一种迭代非中心法,用于Log rank检验所需样本量的测定,并同Lachin-Foukes法进行了比较。方法:预置样本量重复抽样,计算Log rank检验统计量及其平均值。调整预置样本量重复操作,当该平均值充分逼近预定非中心参数时,最后预置样本量被看成是所需样本量。结果:该法所得样本量因生存分布而异,可满足Log rank检验预定功效。相比之下,Lachin-Foukes法所得样本量偏小,用于Log rank检验功效不足。结论:迭代非中心法优于Lachin-Foukes法,可用于慢性病和癌症生存研究的设计。

New Ranking of Generalized Quadrilateral Shape Fuzzy Number Using Centroid Technique

The output of the fuzzy set is reduced by one for the defuzzification procedure.It is employed to provide a comprehensible outcome from a fuzzy inference process.This page provides further information about the defuzzifica-tion approach for quadrilateral fuzzy numbers,which may be used to convert them into discrete values.Defuzzification demonstrates how useful fuzzy ranking systems can be.Our major purpose is to develop a new ranking method for gen-eralized quadrilateral fuzzy numbers.The primary objective of the research is to provide a novel approach to the accurate evaluation of various kinds of fuzzy inte-gers.Fuzzy ranking properties are examined.Using the counterexamples of Lee and Chen demonstrates the fallacy of the ranking technique.So,a new approach has been developed for dealing with fuzzy risk analysis,risk management,indus-trial engineering and optimization,medicine,and artificial intelligence problems:the generalized quadrilateral form fuzzy number utilizing centroid methodology.As you can see,the aforementioned scenarios are all amenable to the solution pro-vided by the generalized quadrilateral shape fuzzy number utilizing centroid methodology.It’s laid out in a straightforward manner that’s easy to grasp for everyone.The rating method is explained in detail,along with numerical exam-ples to illustrate it.Last but not least,stability evaluations clarify why the Gener-alized quadrilateral shape fuzzy number obtained by the centroid methodology outperforms other ranking methods.

Using the Method of Maximizing Deviation to Make Decision for M ultiindices

This paper takes the synthesizing evaluation about industrial economic benefits by examples and proposes a new method named maximizing deviation method for multiindices decision. The new method can automatically determine the weight coefficients among the multiindices and also can obtain the exact and reliable evaluation results without subjectivity.

Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.

Method of Searching for Earthquake Disaster Evacuation Routes Using Multi-Objective GA and GIS

This study treats the determination of routes for evacuation on foot in earthquake disasters as a multi-objective optimization problem, and aims to propose a method for quantitatively searching for evacuation routes using a multi-objective genetic algorithm (multi-objective GA) and GIS. The conclusions can be summarized in the following three points. 1) A GA was used to design and create an evacuation route search algorithm which solves the problem of the optimization of earthquake disaster evacuation routes by treating it as an optimization problem with multiple objectives, such as evacuation distance and evacuation time. 2) In this method, goodness of fit is set by using a Pareto ranking method to determine the ranking of individuals based on their relative superiorities and inferiorities. 3) In this method, searching for evacuation routes based on the information on present conditions allows evacuation routes to be derived based on present building and road locations.?Further, this method is based on publicly available information;therefore, obtaining geographic information similar to that of this study enables this method to be effective regardless of what region it is applied to, or whether the data regards the past or the future. Therefore, this method has high degree of spatial and temporal reproducibility.

An efficient block variant of robust structured multifrontal factorization method

Based on the two-dimensional three-temperature （2D3T） radiation diffusion equations and its discrete system, using the block diagonal structure of the three-temperature matrix, the reordering and symbolic decomposition parts of the RSMF method are replaced with corresponding block operation in order to improve the solution efficiency. We call this block form method block RSMF （in brief, BRSMF） method. The new BRSMF method not only makes the reordering and symbolic decomposition become more effective, but also keeps the cost of numerical factorization from increasing and ensures the precision of solution very well. The theoretical analysis of the computation complexity about the new BRSMF method shows that the solution efficiency about the BRSMF method is higher than the original RSMF method. The numerical experiments also show that the new BRSMF method is more effective than the original RSMF method.

可实现弱等效方案排序的改进TOPSIS排序法

针对TOPSIS法可能存在多个备选方案的接近度相同而无法进行全排序的问题。首先,考虑到等效方案在正、负理想解距离上的差异,本文将其细分为强等效方案(不同方案到理想解距离相等)与弱等效方案(不同方案到理想解距离的比值相等但距离不等)。其次,以二维目标为坐标系描述TOPSIS系统,发现TOPSIS评价系统中有:(1)所有方案均位于某一特定区域;(2)强等效方案为同一点,而弱等效方案则位于特定直线上等特性。进而,依据二维目标空间下等效方案与正、负理想解的相对位置关系,针对存在弱等效方案的TOPSIS评价系统,提出一种在依据接近度对备选方案进行分组与组间排序基础上,重新定义排序指数对组内等效方案实施排序。从而设计出一种组间排序基础上的组内排序与组间排序相结合的改进TOPSIS排序法。该方法既不改变方案的原有TOPSIS排序,又可实现弱等效方案的全排序。最后通过数值分析验证所提出方法的合理性和有效性。

基于视觉信息加工的草原公路行车安全性分析

为探究草原公路各典型行车环境驾驶人视觉信息加工模式的差异性,从视觉层面解析草原公路行车安全,基于眼动仪开展草原公路实车实验,提取驾驶人在自由行驶、跟驰、对向来车、后车切入、路侧风险、交叉口6种真实行车环境下的眼动数据。首先,从视觉分配和视觉搜索两个维度构建评价指标体系,采用动态聚类法将驾驶人的视觉兴趣区域划分为5类,将信息熵与马尔可夫链平稳分布理论结合,构建视点分布信息熵量化驾驶人视觉注意分配的复杂度,并引入扫视幅度、扫视速度分析驾驶人对视觉信息的搜索过程。最后,构建基于CRITIC法的加权秩和比评价模型,对不同行车环境下驾驶人的视觉信息加工强度进行了综合评价。结果显示:驾驶人的视点分布在不同行车环境中存在差异,但当前车道始终是驾驶人获取视觉信息的主视区;各视觉评价指标随行车环境的变化呈显著的统计学差异;驾驶人遇到路侧风险时的视觉信息加工强度最大,行车安全性相对更低。

Shuffled complex evolution coupled with stochastic ranking for reservoir scheduling problems

This paper introduces an optimization method(SCE-SR)that combines shuffled complex evolution(SCE)and stochastic ranking(SR)to solve constrained reservoir scheduling problems,ranking individuals with both objectives and constrains considered.A specialized strategy is used in the evolution process to ensure that the optimal results are feasible individuals.This method is suitable for handling multiple conflicting constraints,and is easy to implement,requiring little parameter tuning.The search properties of the method are ensured through the combination of deterministic and probabilistic approaches.The proposed SCE-SR was tested against hydropower scheduling problems of a single reservoir and a multi-reservoir system,and its performance is compared with that of two classical methods(the dynamic programming and genetic algorithm).The results show that the SCE-SR method is an effective and efficient method for optimizing hydropower generation and locating feasible regions quickly,with sufficient global convergence properties and robustness.The operation schedules obtained satisfy the basic scheduling requirements of reservoirs.

基于有限差分低秩分解策略的黏声各向异性纯qP波正演模拟方法

地下介质的黏弹性和各向异性特征会导致地震波出现相位频散和振幅衰减,如果在地震数据处理中忽略这些影响,那么成像结果会出现同相轴畸变和偏移假象。常规黏声TTI介质拟声波方程可用于模拟地震波在黏声各向异性介质中的传播特征,但存在伪横波干扰和受模型参数限制(各向异性参数ε必须大于δ)等问题。为了解决上述问题,将基于声学近似的纯qP波频散关系与常Q衰减模型相结合,推导了一种黏声TTI介质纯qP波方程。该方程包含解耦的相位频散和振幅衰减项,便于实现衰减补偿逆时偏移。基于新推导的方程,发展了有限差分低秩分解求解策略,实现了黏声TTI介质纯qP波正演模拟。数值模拟结果表明,该方程克服了黏声TTI介质拟声波方程的局限,可较为准确且稳定地模拟地震波在黏声各向异性介质中的传播过程。同时,该有限差分低秩分解求解策略继承了有限差分求解方法高效的优势,相比于传统低秩分解法具有更高的计算效率。