Response surface method using grey relational analysis for decision making in weapon system selection

A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.

Optimization of Tribological Performance of Al-6061T6-15% SiCp-15% Al₂O₃Hybrid Metal Matrix Composites Using Taguchi Method &Grey Relational Analysis

In this investigation, optimization of tribological performance parameters of Al-6061T6 alloy reinforced with SiC (15% by weight) and Al2O3 (15% by weight) particulates having particle size of 37 μm each has been presented. The wear and frictional properties of the hybrid metal matrix composites have been studied by performing dry sliding wear test using pin-on-disc wear tester. A L27 orthogonal array is selected for the analysis of the data. From the test results it is observed that sliding distance has the significant contribution in controlling the friction and wear behaviour of hybrid composites. A confirmation test is also carried out to verify the accuracy of the results obtained through the optimization. In addition an optical micrograph test is also performed on the wear tracks to study the wear mechanism.

Optimizing the Glass Fiber Cutting Process Using the Taguchi Methods and Grey Relational Analysis

This paper mainly describes a new approach to optimizing of the cutting glass fiber with multiple performance characteristics, based on reliability analysis, Taguchi and Grey methods. During the cutting process, the speed, the volume and the cutting load are optimized cutting parameters when the performance characteristics, which include Weibull modulus and blade wear, are taken into consideration. In this paper, optimization with multiple performance characteristics is found to be the highest cutting speed and the smallest cutting volume, and the medium cutting load. An analysis of the variance of the blade wear indicates that the cutting speed (47.21%), the cutting volume (14.62%) and the cutting load (12.20%) are the most significant parameters in the cutting process of glass fibers. In summary, the most optimal cutting parameter should be A3B1C2. The results of experiments have shown that the multiple performance characteristics of cutting glass fiber are improved effectively through this approach.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Multi-Objective Optimization of Fused Deposition Modeling for Mechanical Properties of Biopolymer Parts Using the Grey-Taguchi Method

The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the coronavirus-19 disease and the ondemand necessity to perform surgery during space missions.Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing.Among all 3D printing techniques,fused deposition modelling(FDM)is a low-cost and more rapid printing technique.This article proposes the fabrication of surgical instruments,namely,forceps and hemostat using the fused deposition modeling(FDM)process.Excellent mechanical properties are the only indicator to judge the quality of the functional parts.The mechanical properties of FDM-processed parts depend on various process parameters.These parameters are layer height,infill pattern,top/bottom pattern,number of top/bottom layers,infill density,flow,number of shells,printing temperature,build plate temperature,printing speed,and fan speed.Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid(PLA)parts printed by FDM.The experiments have performed through Taguchi’s L27orthogonal array(OA).Variance analysis(ANOVA)ascertains the significance of the process parameters and their percent contributions to the evaluation indexes.Finally,as a multiobjective optimization technique,grey relational analysis(GRA)obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties.Scanning electron microscopy(SEM)examines the types of defects and strong bonding between rasters.The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength(42.6 MPa)and modulus of elasticity(3274 MPa).

Optimization of back bead geometry in the PMAG-TIG twin arc hybrid root welding process using grey based Taguchi method

This study investigated multi-response optimization of the pulse metal active gas-tungsten inert gas( PMAG-TIG) twin arc hybrid root welding process for an optimal parametric combination to yield favorable back bead geometry of welded joints using grey relational analysis and Taguchi method.Eighteen experimental runs based on an orthogonal array following the Taguchi method were performed to derive objective functions to be optimized within the experimental domain.The objective functions were selected in relation to parameters of PMAG-TIG twin arc root welding back bead geometry: back bead width to root reinforcement ratio and deposited metal height.The Taguchi approach was followed by grey relational analysis to solve the multi-response optimization problem.The significance of factors on overall quality characteristics of the weld joint was also evaluated quantitatively using analysis of variance.Optimal results were verified through additional experiments,and showed to feasibility of applying grey relation analysis in combination with Taguchi technique for continuous improvement of product quality in the manufacturing industry.

改善低次烟叶品质的生物发酵工艺优化

为改善低次烟叶吸食品质,提升烟叶可用性,优选3种酶系、菌系(蛋白多肽酶系、木质酶系、增香菌系)配制成复合生物发酵制剂,以品质改善程度为评价指标,采用单因素法和均匀设计法优化了烟叶生物发酵工艺。结果表明:(1)最佳发酵工艺条件为,发酵制剂/烟丝质量比4%、物料含水量22%、发酵温度37℃、发酵时间42 h。(2)发酵工艺各因素中,发酵温度对品质改善程度大于物料水分、发酵时间。(3)在最佳发酵条件下,烟叶品质改善程度为1.04,杂气减少、刺激性降低,感官质量大幅提升,发酵后烟叶蛋白质、淀粉、果胶、木质素分别降低9.17%、15.59%、16.67%、7.84%,醛类、酮类、醇类等物质较原样分别增加了23.70%、15.33%、41.03%。通过发酵工艺优化,烟叶化学成分更协调,烟叶可用性提升。

基于系统协调度模型的汛限水位分期控制

为协调防洪与兴利的矛盾,提高洪水资源化利用效益,基于改进模糊集方法进行汛期分期,建立系统协调度模型并计算得到汛限水位的动态控制域。以思林水库为例,前、后汛期的汛限水位与发电效益协同贡献度成正比,与防洪风险协同贡献度成反比;为实现系统协调度最大,前、后汛期的汛限水位动态控制域应分别为[435,437]m和[435,438]m,前、后汛期可分别增发电量2169.907×10^(4)、6509.722×10^(4)kW·h,水资源利用量可分别提高0.716×10^(8)、1.079×10^(8)m^(3)。研究成果可提高洪水资源利用效率,为水库安全合理运行提供参考。

师范专业认证理念下的课程目标达成度评价方法的探索与实践

在师范专业认证及持续改进的背景下,文章以“C程序设计”课程为例,阐述了基于培养目标和对毕业要求支撑的反向设计的课程目标;针对课程目标的达成,进行了教学内容、方法、手段的改革;构建了混合式教学课程目标评价体系和反馈机制,给出了计算模型;基于教学班的教学平台考核数据,定量、定性地分析了课程目标、子目标及考核项的达成度;根据分析结果,给出了教学过程中教与学的改进措施。

基于IMFO-LSTM模型的光伏功率预测研究

随着光伏发电大容量接入电网,为降低光伏发电输出的随机性,提出一种基于改进飞蛾优化(improved moth-flame optimization,IMFO)的长短期记忆网络(long short-term memory,LSTM)进行光伏发电功率预测。首先,通过数据预处理,进行灰色关联度分析,减少输入变量维数,再根据选取的输入变量,通过灰色关联度分析法,进行相似日样本选取;其次,为提高飞蛾算法的性能,对其位置更新公式进行改进;接着,根据IMFO-LSTM的网络层数和学习率,提高其预测精度,降低随机性;最后,基于预处理好的相似日样本,采用优化后的LSTM进行预测。仿真结果表明:该模型的预测精度得到一定提升,满足实际工程要求。

基于三种水质指数方法的万泉河口健康评价

为了解海南万泉河口的水质变化特征现状,以2021年5月至2022年5月的溶氧量、氨氮、总氮、总磷以及五日生化需氧量为水质指标,分别采用单因子评价法、综合污染指数法和改进的灰色关联分析法对水质状况进行了分析与评价,并对三种评价方法的结果进行比较.结果表明:万泉河口各个位点都受到了不同程度的污染,多数位点的溶氧量和总氮含量超过中国Ⅲ类水环境质量标准,其中以位于沙美内海最南端的位点和位于河口北侧狭窄河道的位点污染最为严重,总氮和生化需氧量含量超过中国Ⅲ类水环境质量标准,并且污染程度呈现明显的季节性变化,旱季的污染程度较雨季更高.同单因子评价法与综合污染指数法相比,改进的灰色关联分析法能够较为全面且客观地评价污染物的影响,并能判断主要的污染物类别,可有效地进行水质评价.

基于用电大数据处理的配网供电可靠性分析方法研究

针对现有大多数方法难以准确分析配网可靠性影响因素的问题,文中开展了一种基于用电大数据处理的配网供电可靠性分析方法研究。该研究以大数据平台为基础设计了用电数据处理模型,并通过插值法来完成数据预处理。同时利用熵权法来优化灰色关联分析法,以全面考虑数据的潜在特征。通过将改进灰色关联分析法用于分析供电可靠性指标与各影响因素的关联程度,从而为配网改造优化提供指导意见。基于某供电公司的用电大数据对所提方法进行实验测试,其分析准确率最高且最稳定,均超过了90%。而环网率的关联系数也达到了0.852,影响最大。

镇江市数字经济与实体经济融合发展的实证研究——基于耦合协调度模型和灰色关联分析法

数字经济与实体经济融合发展已成为推动我国经济增长的重要动力。首先,探索了数字经济与实体经济融合发展内在机理;其次,采用熵值法和耦合协调度模型对镇江市数字经济与实体经济融合发展水平进行了测算,归纳总结了镇江市2018—2022年数字经济与实体经济融合发展现状,即镇江市数字经济与实体经济由最初2018年的严重失调发展为2022年的优质协调,且呈现出协同促进效果,但实体经济发展水平已呈现逐步落后于数字经济发展水平的趋势;然后,利用灰色关联分析法探究了镇江市数字经济与实体经济融合发展的影响因素,其中数字产业化和产业数字化的影响最为显著;最后,基于研究结论,提出了增强数字产业辐射力、加快数字产业化进程、提升实体产业数字化水平等促进镇江市数字经济与实体经济融合发展的对策。

五自由度上肢康复机器人设计与分析

针对由脑卒中、脊髓损伤等造成的上肢运动功能减退、需康复的问题,设计了一款基于人体上肢尺寸的可穿戴式五自由度上肢康复机器人。使用改进的D-H参数法,建立了其运动学模型,结合数字仿真软件的机器人工具箱,验证了其模型的正确性;利用蒙特卡罗法得到机器人的工作空间云图,通过与各关节运动范围进行对比,验证了其工作范围的合理性。最后运用五次多项式插值法对其进行轨迹规划,获得了各个关节角的角度、速度、加速度的平稳曲线图。实验结果验证了上肢康复机器人结构设计的正确性和整个康复训练过程的可行性。

基于AHP-CRITIC复合熵权法和灰色关联度分析的生地黄炒炭工艺优选

目的:筛选生地黄炭的最佳炮制工艺参数,为生地黄炭质量控制提供综合评价模型。方法:以生地黄炭饮片6个有效成分(梓醇、地黄苷D、焦地黄苯乙醇苷A1、毛蕊花糖苷、异毛蕊花糖苷、5-羟甲基糠醛)的质量分数、吸附力、得率和外观性状评分共9个评价指标,采用L_(9)(3^(4))正交试验设计和单因素考察,结合层次分析法(AHP)-指标权重确定方法(CRITIC)复合熵权确定各评价指标的权重系数,以直观分析、方差分析及复合熵权法结合灰色关联度分析法对正交试验结果进行综合评价,优选生地黄炭最佳炮制工艺。结果:优选的生地黄炭最佳炮制工艺参数为:温度200℃,炒制20 min,转速25 Hz。结论:AHP-CRITIC复合熵权法和灰色关联度分析法结合正交试验进行生地黄炭炮制工艺优化,各指标权重系数客观且真实,优选的炒炭工艺稳定可行,重复性良好,可以为生地黄炭炮制工艺标准及质量标准的建立提供试验依据。

Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron

High chrome white cast iron is particularly preferred in the production of machine parts requiring high wear resistance. Although the amount of chrome in these materials provides high wear and corrosion resistances, it makes their machinability difficult. This study presents an application of the grey relational analysis based on the Taguchi method in order to optimize chrome ratio, cutting speed, feed rate, and cutting depth for the resultant cutting force (Fr) and surface roughness (Ra) when hard turning high chrome cast iron with a cubic boron nitride (CBN) insert. The effect levels of machining parameters on Fr and Ra were examined by an analysis of variance (ANOVA). A grey relational grade (GRG) was calculated to simultaneously minimize Fr and Ra. The ANOVA results based on GRG indicated that the feed rate, followed by the cutting depth, was the main parameter and contributed to respo ses. Optimal levels of parameters were found when the chrome ratio, cutting speed, feed rate, and cutting depth were 12%, 100m/min, 0.05mm/r, and 0.1mm, respectively, based on the multiresponse optimization results obtained by considering the maximum signal to noise (SIN) ratio of GRG. Confirmation results were verified by calculating the confidence level within the interval width.

A Two-Stage Vehicle Type Recognition Method Combining the Most Effective Gabor Features

Vehicle type recognition(VTR)is an important research topic due to its significance in intelligent transportation systems.However,recognizing vehicle type on the real-world images is challenging due to the illumination change,partial occlusion under real traffic environment.These difficulties limit the performance of current state-of-art methods,which are typically based on single-stage classification without considering feature availability.To address such difficulties,this paper proposes a two-stage vehicle type recognition method combining the most effective Gabor features.The first stage leverages edge features to classify vehicles by size into big or small via a similarity k-nearest neighbor classifier(SKNNC).Further the more specific vehicle type such as bus,truck,sedan or van is recognized by the second stage classification,which leverages the most effective Gabor features extracted by a set of Gabor wavelet kernels on the partitioned key patches via a kernel sparse representation-based classifier(KSRC).A verification and correction step based on minimum residual analysis is proposed to enhance the reliability of the VTR.To improve VTR efficiency,the most effective Gabor features are selected through gray relational analysis that leverages the correlation between Gabor feature image and the original image.Experimental results demonstrate that the proposed method not only improves the accuracy of VTR but also enhances the recognition robustness to illumination change and partial occlusion.

Similarity evaluation of stratum anti-drilling ability and a new method of drill bit selection

Considering the stratum anti-drilling ability,drill bit working conditions,drill bit application effect and drill bit economic benefits,the similarity of stratum anti-drilling ability was evaluated by grey relational analysis theory to screen out candidate drill bits with reference values.A new comprehensive performance evaluation model of drill bit was established by constructing the absolute ideal solution,changing the relative distance measurement method,and introducing entropy weight to work out the closeness between the candidate drill bits and ideal drill bits and select the reasonable drill bit.Through the construction of absolute ideal solution,improvement of relative distance measurement method and introduction of entropy weight,the inherent defects of TOPSIS decision analysis method,such as non-absolute order,reverse order and unreasonable weight setting,can be overcome.Simple in calculation and easy to understand,the new bit selection method has good adaptability to drill bit selection using dynamic change drill bit database.Field application has proved that the drill bits selected by the new drill bit selection method had significant increase in average rate of penetration,low wear rate,and good compatibility with the drilled formations in actual drilling.This new method of drill bit selection can be used as a technical means to select drill bits with high efficiency,long life and good economics in oilfields.

基于层次分析法的逼近理想解排序法—灰色关联度法对新建医院大型医用设备购置的决策分析

目的:构建基于层次分析法(AHP)的逼近理想解排序法(TOPSIS)—灰色关联度法大型医用设备购置决策模型,以保障新建医院开诊中有效进行分阶段购置大型医用设备。方法:根据AHP确定购置决策模型的指标权重,通过TOPSIS得出各设备相对贴近度,通过灰色关联度法算出各设备相对关联度,根据专家组评估系数将相对贴近度和相对关联度整合为综合贴近度完成购置决策模型构建。选取医院临床检查和治疗常用的X射线计算机断层扫描(CT)、磁共振成像(MRI)、数字减影血管造影(DSA)、电子直线加速器(LA)、发射性型计算机断层扫描(ECT)和数字X射线摄影(DR)6种大型医用设备进行新建医院大型医用设备购置决策研究。结果:构建的大型医用设备购置决策模型计算的购置设备优先级排序为CT、MRI、DR、DSA、ECT和LA。根据资金情况和相关政策,新建医院第一批购置CT、MRI和DR三种设备,在新建医院开诊后半年内未出现临床检查和治疗挤兑等情况,医院整体运行平稳。结论:基于AHP的TOPSIS—灰色关联度法构建的大型医用设备购置决策模型应用于新建医院大型医用设备购置效果良好,能够有效满足新建医院平稳运行的需求。

基于熵权法和灰色关联度法的梨品质区分

以不同品种梨(砀山酥梨、贡梨、黄冠梨、库尔勒香梨)为研究对象,在其理化指标检测结果的基础上,结合低场核磁共振检测技术,探究梨水分分布与理化指标之间的关联性,进而通过相关性分析和主成分分析确立评价品质的核心指标,以熵权法权重结果作为分辨系数,构建梨品质的灰色关联度评价模型。结果表明:不同品种梨的各理化指标存在显著性差异,其水分分布与理化指标显著性相关,确立了A_(23)、可滴定酸、A_(22)和可溶性固体含量为核心指标的模型,该模型能够快速准确地对梨的综合品质进行区分。