A Linkage Learning Genetic Algorithm with Linkage Matrix

The goal of linkage learning, or building block identification, is the creation of a more effective Genetic Algorithm （GA）. This paper proposes a new Linkage Learning Genetic Algorithms, named m-LLGA. With the linkage learning module and the linkage-based genetic operation, m-LLGA is not only able to learn and record the linkage information among genes without any prior knowledge of the function being optimized. It also can use the linkage information stored in the linkage matrix to guide the selection of crossover point. The preliminary experiments on two kinds of bounded difficulty problems and a TSP problem validated the performance of m-LLGA. The m-LLGA learns the linkage of different building blocks parallel and therefore solves these problems effectively; it can also reasonably reduce the probability of building blocks being disrupted by crossover at the same time give attention to getting away from local minimum.

Phantom-based evaluations of two binning algorithms for four-dimensional CT reconstruction in lung cancer radiation therapy

Objective: The purpose of this study was to evaluate the performance of the phase-binning algorithm and amplitude-binning algorithm for four-dimensional computed tomography(4DCT) reconstruction in lung cancer radiation therapy. Methods: Quasar phantom data were used for evaluation. A phantom of known geometry was mounted on a four-dimensional(4D) motion platform programmed with twelve respiratory waves(twelve lung patients trajectories) and scanned with a Philips Brilliance Big bore 16-slice CT simulator. The 4DCT images were reconstructed using both phase- and amplitude-binning algorithms. Internal target volumes(ITVs) of the phase- and amplitude-binned image sets were compared by evaluation of shape and volume distortions. Results: The phantom experiments illustrated that, as expected, maximum inhalation occurred at the 0% amplitude and maximum exhalation occurred at the 50% amplitude of the amplitude-binned 4DCT image sets. The amplitude-binned algorithm rendered smaller ITV than the phase-binning algorithm. Conclusion: The amplitude-binning algorithm for 4DCT reconstruction may have a potential advantage in reducing the margin and protecting normal lung tissue from unnecessary irradiation.

Linkage intensity learning approach with genetic algorithm for causality diagram

The causality diagram theory, which adopts graphical expression of knowledge and direct intensity of causality, overcomes some shortages in belief network and has evolved into a mixed causality diagram methodology for discrete and continuous variable. But to give linkage intensity of causality diagram is difficult, particularly in many working conditions in which sampling data are limited or noisy. The classic learning algorithm is hard to be adopted. We used genetic algorithm to learn linkage intensity from limited data. The simulation results demonstrate that this algorithm is more suitable than the classic algorithm in the condition of sample shortage such as space shuttle’s fault diagnoisis.

Complete Real Solution of the Five-orientation Motion Generation Problem for a Spherical Four-bar Linkage

For a spherical four-bar linkage,the maximum number of the spherical RR dyad（R：revolute joint）of five-orientation motion generation can be at most 6.However,complete real solution of this problem has seldom been studied.In order to obtain six real RR dyads,based on Strum＇s theorem,the relationships between the design parameters are derived from a 6th-degree univariate polynomial equation that is deduced from the constraint equations of the spherical RR dyad by using Dixon resultant method.Moreover,the Grashof condition and the circuit defect condition are taken into account.Given the relationships between the design parameters and the aforementioned two conditions,two objective functions are constructed and optimized by the adaptive genetic algorithm（AGA）.Two examples with six real spherical RR dyads are obtained by optimization,and the results verify the feasibility of the proposed method.The paper provides a method to synthesize the complete real solution of the five-orientation motion generation,which is also applicable to the problem that deduces to a univariate polynomial equation and requires the generation of as many as real roots.

Conditions of Non-Unique Identifiers in Record Linkage Using Japanese Cohort Dataset

The applications of unique identifiers such as name, home address and social security number to link different datasets have been commonly used and well-published. Also, the theoretical concepts of probabilistic algorithm in record linkage have been well-defined in the literature. However, few studies have reported the applications of its probabilistic algorithm using non-unique identifiers. In this paper, we investigate several variables (weight, height, waist, age, sex, smoking and alcohol habit) as non-unique identifiers using Japanese cohort dataset with three-year baseline of 1989-1991 to observe how effectively these identifiers can be used and what influence those may have on record linkage. Moreover, we modify the conditions of these identifiers and estimate the sensitivity, specificity and accuracy for comparison. We further investigate this by using extended ten-year baseline of 1989-1999 as well. As a result, we conclude that the combination of age, sex, weight and height predicts better estimation with regards to the sensitivity, specificity and accuracy than other combinations in both men and women in case of using three-year baseline, whereas the combination of age, sex and height predicts better in both men and women in case of using ten-year baseline.

Study and application of an improved four-dimensional variational assimilation system based on the physical-space statistical analysis for the South China Sea

The four-dimensional variational assimilation(4D-Var)has been widely used in meteorological and oceanographic data assimilation.This method is usually implemented in the model space,known as primal approach(P4D-Var).Alternatively,physical space analysis system(4D-PSAS)is proposed to reduce the computation cost,in which the 4D-Var problem is solved in physical space(i.e.,observation space).In this study,the conjugate gradient(CG)algorithm,implemented in the 4D-PSAS system is evaluated and it is found that the non-monotonic change of the gradient norm of 4D-PSAS cost function causes artificial oscillations of cost function in the iteration process.The reason of non-monotonic variation of gradient norm in 4D-PSAS is then analyzed.In order to overcome the non-monotonic variation of gradient norm,a new algorithm,Minimum Residual(MINRES)algorithm,is implemented in the process of assimilation iteration in this study.Our experimental results show that the improved 4D-PSAS with the MINRES algorithm guarantees the monotonic reduction of gradient norm of cost function,greatly improves the convergence properties of 4D-PSAS as well,and significantly restrains the numerical noises associated with the traditional 4D-PSAS system.

大规模复杂换热网络联动进化障碍分析及策略改进

针对启发式算法在优化大规模换热网络时出现优化精细度不足的问题,提出一种以小负荷公用工程为导向的换热单元耦合联动强制进化策略。该策略以小负荷公用工程作为导向,构建具有耦合关系的换热单元环路,并对环路内的换热单元热负荷进行联动调整,同时保持环路外换热单元的热负荷和流股匹配不变。该策略旨在最大程度回收流股的能量,以减少小负荷公用工程使用带来的费用增加。将策略应用于强制进化随机游走算法并对两个算例进行测试,算例H8C7和H10C10的优化结果分别为1495292$/a和1713637$/a。与改进前相比,分别降低了7466$/a和7533$/a;与文献中最优解相比,分别减少了2033$/a和1450$/a,证明了该策略的有效性。

3D打印机多轴联动插补算法的研究与优化

针对3D打印过程中,打印机多轴联动插补算法计算效率低的问题和Bresenham算法在3D打印运动控制中的不足,在现有算法基础之上提出阶跃式Bresenham算法、速度自适应算法,分别完成喷嘴的成型扫描运动和浆料的挤出运动.采用两种算法相结合的方式控制3D打印机多轴联动,从而提高3D打印机的插补速度.同时分析了该控制方式在微控制器中的实现流程,并将其移植于微控制器中.本研究设计了直线插补仿真试验和不同算法的3D打印试验,证明了该控制方式在打印精度不变的前提下能够提高打印效率.

基于产业链图谱的服装企业产业链挂链关系挖掘

服装产业是全球最重要的制造行业之一,而服装产业链图谱则是服装产业生态中的重要工具。为了服装相关企业能快速、准确挂链,文章研究并构建服装产业链图谱,将产业链中的链点、关系和属性进行建模和表示,再通过企业信息收集和企业关键词提取构建企业信息数据库,从而提出了一种产业链企业自动挂链算法。该算法基于CoSENT模型计算企业关键词和产业链链点之间的相似性,并通过自定义规则对匹配结果进行过滤,进而评估关键词和链点之间的相关性,自动匹配和选择最优的产业链图谱链点,实现企业的产业链自动挂链。通过与其他匹配算法的对比实验表明,该算法在F1-Measure指标上明显优于其他算法(比基于Jaccard方法高14%,比Word2Vec方法高10.5%,比SBERT方法高2.5%),显著提升了企业挂链效率和准确性,为优化服装产业链图谱提供了有力的支撑和参考。

丘陵山地桑叶采收机取袋机构优化设计与试验

针对丘陵山地桑叶采收机收集装置自动取袋过程实现困难的问题,通过桑叶取袋装袋过程运动学分析,对取袋机构进行了优化设计与试验.首先通过分析整机结构与取袋机构工作原理,建立了取袋机构运动学分析模型;以最大横向取袋距离和取袋瞬间角度为目标,建立了优化设计模型,并开发了辅助分析设计软件,确定了取袋机构参数的取值范围;采用带基因策略的非支配排序遗传算法(NSGA-II)对模型求解,获得最优设计参数.其次根据最优设计参数建立了三维模型,利用ANSYS进行运动学仿真分析,结果表明取袋机构末端执行器位移图像和速度曲线与设计要求一致,可满足取袋机构设计要求.最后研制出桑叶采收机与取袋机构样机,对取袋机构样机开展高速摄像试验,验证了取袋机构运动轨迹与理论仿真结果基本一致.以曲柄转速、吨口袋种类、磁吸石外圆尺寸为试验因素,取袋开袋成功率为指标开展桑叶取袋开袋正交试验,并根据最优组合进行验证试验.试验结果表明:曲柄转速为0.1 r/s、吨口袋形状与尺寸为方体550 mm、磁吸石外圆尺寸为20 mm时,取袋开袋成功率为97.50%,表明该机构能完成取袋作业,可实现桑叶采收机的取袋开袋功能.

一种基于折息最小二乘法的PMSM磁链辨识方法

永磁同步电机(permanent magnet synchronous motor,PMSM)的磁链准确辨识是实现高性能电机控制的基础。针对传统递推最小二乘(recursive least squares,RLS)法受噪声影响小但存在数据饱和,影响辨识精度和动态性问题,以及遗忘最小二乘(recursive least squares with forgetting factor,FRLS)法避免数据饱和但存在参数估计误差与动态跟踪性能矛盾的问题,文章提出一种基于折息最小二乘(recursive least squares with discount factor,DRLS)法的磁链辨识方法。该算法在FRLS法中引入加权因子构成折息因子,采用递推方法进行磁链辨识,减小参数估计误差,提高磁链辨识精度及动态跟踪能力。通过MATLAB仿真及半实物仿真试验,验证所提磁链识别方法的有效性。

矿井工作面UWB联动闭锁技术及应用设计

通过对超宽带无线载波通信技术(UWB)及TDOA、TOF 2种定位算法的综合研究及分析计算,在综采工作面部署测量基础点检测源,在综采工作面作业人员及大型设备上部署被测量点发射源,并且被测量点发射源可对大型设备的电液控系统进行逻辑控制,通过计算测量基础点检测源与被测量点发射源之间的距离实现接近监测及联动闭锁。基于此,提出了综采工作面联动闭锁预警系统的整体设计方案,该方案同时适用于综采工作面其他大型设备的接近监测及联动闭锁,降低了工作面人员被液压支架、采煤机、掘进机等大型设备误伤的风险。

引江济淮工程高低联动智能视频感知技术研究

引江济淮工程中原有的低点监控视野范围窄、抗干扰能力差、缺乏智能化功能,已无法满足智慧水利建设的要求。利用通信高塔作为挂载点,在引江济淮工程的关键标段植入高点智能化监控设备,从而构建出高低联动智能视频感知体系。其中利用人工智能技术,建立AI模型训练平台,实现了包含区域入侵侦测、水面漂浮物检测在内的多项视频侦测、检测功能。应用实践表明,在多种智能算法的赋能加持下,高低联动智能视频感知体系显著提高了报警准确率和智能识别距离,为数字引江济淮的建设提供了有效助力。

Design of a Multi-axis Motion Control Platform Based on LabVIEW’s Fuzzy Control Algorithm

This paper presents a fuzzy control algorithm applied to the position control of a multi-axis motion platform to achieve high precision motion control of the multi-axis motion platform.A LabVIEW-based multi-axis motion control system is designed.This system controls stepper motors using trapezoidal acceleration/deceleration pulse types and fuzzy control algorithms,which effectively avoids mechanical jitter and loss of step in the process of multi-angle motion of the stepper motor,and achieves accurate control of the stepper motor.The TCP/IP(transmission control protocol/internet protocol)communication protocol is used,so that data are output stably and not lost in the process of transmission and communication,achieving the purpose of interconnection of different systems and remote control of equipment.This control system has been tested to maintain a high level of stability and repeatability during actual operation.

Algorithm of brush short-circuit coeffcients of DC machines for extremely low speed drives

When a direct-current （DC） machine runs at extremely low speed or standstill, the reduction in the armature resistance and the armature flux linkage due to the short circuited coils by the brushes on the commutator should not be neglected. Taking this reduction effect into account, the average values of the reduction coefficients relate to the machine parameters in complicated forms. In this paper, an effective algorithm for the precise computation of the average values of these reduction coefficients is proposed. Furthermore, in the algorithm, the effect of the insulation thickness between the commutator segments and the multiplicity of the wave winding are considered for the first time. The proposed algorithm can also be accommodated into the computer-aided design （CAD） of a DC machine, which normally runs at extremely low speed or standstill.

数控连杆机构式机器人的平衡特性及优化

为了提升数控连杆机构式机器人的平衡特性,以一种数控连杆机构式机器人机构为研究对象,首先计算总质心坐标,采用倾覆力矩和惯性力作为机器人静态及动态平衡性评价指标;其次构建去除支链的传统机器人,将该机器人与数控连杆式机器人进行对比,对比结果表明,数控连杆机构式机器人的平均倾覆力矩比传统串联机器人减小了96.31%;在负载为10 kg的情况下,x方向和y方向的惯性力比传统机器人分别减少了20.76%、34.88%;为进一步提升机器人平衡性,以支链杆长为设计变量,总惯性力最小为目标函数,支链杆长之和为约束条件,运用遗传算法,求出其杆长最优解。优化结果表明,优化后的机器人总惯性力相比优化前减小21.67%,从而验证了杆件优化的有效性。

基于PID控制的多轴联动数控机床运动误差补偿

为了降低多轴数控机床在运动过程中产生的误差,提高数控机床的控制精度,提出多轴联动的数控机床运动误差补偿方法。构建多轴联动数控机床在工作状态下的运动轨迹方程,在机床运动轨迹方程的基础上计算多轴联动数控机床的运动误差。采用粒子群优化算法优化PID控制器中的关键参数,将上述计算得到的运动误差输入优化后的PID控制器中,完成多轴联动数控机床运动误差的补偿。实验结果表明,所提方法可高精度地完成椭圆控制和螺旋旋转体控制,且运动误差补偿结果不受多轴联动数控机床运动速度的影响,具有良好的适应性。

Conjugate Gradient Algorithm in the Four-Dimensional Variational Data Assimilation System in GRAPES

Minimization algorithms are singular components in four-dimensional variational data assimilation(4DVar).In this paper,the convergence and application of the conjugate gradient algorithm(CGA),which is based on the Lanczos iterative algorithm and the Hessian matrix derived from tangent linear and adjoint models using a non-hydrostatic framework,are investigated in the 4DVar minimization.First,the influence of the Gram-Schmidt orthogonalization of the Lanczos vector on the convergence of the Lanczos algorithm is studied.The results show that the Lanczos algorithm without orthogonalization fails to converge after the ninth iteration in the 4DVar minimization,while the orthogonalized Lanczos algorithm converges stably.Second,the convergence and computational efficiency of the CGA and quasi-Newton method in batch cycling assimilation experiments are compared on the 4DVar platform of the Global/Regional Assimilation and Prediction System(GRAPES).The CGA is 40%more computationally efficient than the quasi-Newton method,although the equivalent analysis results can be obtained by using either the CGA or the quasi-Newton method.Thus,the CGA based on Lanczos iterations is better for solving the optimization problems in the GRAPES 4DVar system.

基于策略的矿井水灾避灾路径动态规划

为了解决现有静态路径规划方法无法满足煤矿井下突水灾害动态变化需求,以及传统最短路径算法运行效率有待提升等问题,提出一种基于策略的矿井水灾避灾路径动态规划方法及系统。该方法考虑水流对人员逃生的影响,首先将巷道环境影响因子对避灾路径的影响程度量化为巷道距离当量长度;然后以时间最短为原则,引入人员逃生速度,计算逃生通过每条巷道的时间,构建以逃生时间为邻接矩阵的数学模型;并结合安全监控、水文监测系统联动策略,根据实时监测的井下环境情况,动态修改巷道节点属性,开发基于三维GIS一张图的矿井水灾避灾路径三维动态规划系统。最后,结合矿井实例进行测试分析,验证了算法设计的有效性,可以指导井下人员安全撤离,提高煤矿安全管控能力。

基于组合算法的铁路物流网络空间结构特征识别

铁路物流是物流系统的重要组成部分,其网络结构反映了铁路物流系统内部要素间相互联系、相互制约的内在性。应用PageRank算法测算铁路物流网络节点重要程度,应用首要流分析法提取网络主体结构,应用多重流分析法确定显著流数量,设计组合算法识别铁路物流网络空间结构特征。研究结果表明铁路物流对外联系密切省份集聚,形成了7个数量和规模不同的铁路物流圈,铁路物流圈呈现出地理相邻、产业相关和中心辐射的特征。根据铁路物流圈层特征提出推动铁路物流高质量发展的建议。