Fuzzy based decision support method for selection of sustainable wastewater treatment technologies

Inadequate decision support tools have led to selection of inappropriate wastewater treatment technologies.The objectives of this research were to investigate performance data for wastewater treatment technologies,develop a Decision Support Method(DSM)for evaluating performance of technologies,and to validate the developed method.The method was developed through evaluation of performance of wastewater treatment technologies against environmental and economic indicators.Fuzzy logic techniques in form of linguistic variables were applied in order to support decision making under uncertainty.The DSM relied on performance evaluation in order to rate effectiveness of wastewater treatment technologies.DSM was validated through a training tool in ED-WAVE,a model developed by a consortium of European and Asian countries.The reliance of the DSM on performance evaluation was an improvement on the existing decision support tools such as ED-WAVE that relied on retrieval of past performance data.As DSM integrated environmental and economic factors in evaluating wastewater treatment technologies,it was thus able to select a process that was not only environmentally sustainable but also economically affordable.

Light-Weighted Decision Support Framework for Selecting Cloud Service Providers

Multi-criteria decision making(MCDM)is a technique used to achieve better outcomes for some complex business-related problems,whereby the selection of the best alternative can be made in as many cases as possible.This paper proposes a model,the multi-criteria decision support method,that allows both service providers and consumers to maximize their profits while preserving the best matching process for resource allocation and task scheduling.The increasing number of service providers with different service provision capabilities creates an issue for consumers seeking to select the best service provider.Each consumer seeks a service provider based on various preferences,such as price,service quality,and time to complete the tasks.In the literature,the problem is viewed from different perspectives,such as investigating how to enhance task scheduling and the resource allocation process,improve consumers’trust,and deal with network problems.This paper offers a novel model that considers the preferences of both service providers and consumers to find the best available service provider for each consumer.First,the model adopts the best-worst method(BWM)to gather and prioritize tasks based on consumers’and service providers’preferences.Then,the model calculates and matches similarities between the sets of tasks from the consumer’s side with the sets of tasks from the provider’s side to select the best service provider for each consumer using the two proposed algorithms.The complexity of the two algorithms is found to be O(n3).

Computer System Reliability Allocation Method and Supporting Tool

This paper presents a computer system reliability allocation method that is based on the theory of statistic and Markovian chain,which can be used to allocate reliability to subsystem, to hybrid system and software modules. A relevant supporting tool built by us is introduced.

Casing life prediction using Borda and support vector machine methods

Eight casing failure modes and 32 risk factors in oil and gas wells are given in this paper. According to the quantitative analysis of the influence degree and occurrence probability of risk factors, the Borda counts for failure modes are obtained with the Borda method. The risk indexes of failure modes are derived from the Borda matrix. Based on the support vector machine (SVM), a casing life prediction model is established. In the prediction model, eight risk indexes are defined as input vectors and casing life is defined as the output vector. The ideal model parameters are determined with the training set from 19 wells with casing failure. The casing life prediction software is developed with the SVM model as a predictor. The residual life of 60 wells with casing failure is predicted with the software, and then compared with the actual casing life. The comparison results show that the casing life prediction software with the SVM model has high accuracy.

Novel Design Method of COG Measurement System Via Supporting Reaction Method

Center of gravity(COG)is an important parameter of projectiles and rockets,for which supporting reaction method(or support reaction method)is an important COG measurement method.Based on this supporting reaction method a novel design method is proposed to determine the key design parameters of the COG measurement system.The method can quantitatively analyze the influence of the design parameters on the COG accuracy,in the measurement system designed with supporting reaction method.Using the principle of static balance,the error propagation theory,and the system accuracy analysis method,the equal-range required sensor precision(RSP)surface and non-equal-range required sensor pair precision(RSPP)adapted surface are adopted.The influence of random errors(like sensor accuracy and distance calibration accuracy)is analyzed.The selection strategy of equal-range and non-equal-range sensors is chosen,and then the recommended calibration accuracy values are obtained.For the quality detection accuracy of±0.6 kg and the axial COG detection accuracy of±1.5 mm,the RSP surface is drawn by the proposed method,and the force sensor with±0.23 kg detection accuracy is selected.The experimental verification meets the accuracy requirements and verifies the effectiveness of the proposed design method for the system parameters of the COG measurement equipment.

Vibration reliability analysis for aeroengine compressor blade based on support vector machine response surface method

To ameliorate reliability analysis efficiency for aeroengine components, such as compressor blade, support vector machine response surface method(SRSM) is proposed. SRSM integrates the advantages of support vector machine(SVM) and traditional response surface method(RSM), and utilizes experimental samples to construct a suitable response surface function(RSF) to replace the complicated and abstract finite element model. Moreover, the randomness of material parameters, structural dimension and operating condition are considered during extracting data so that the response surface function is more agreeable to the practical model. The results indicate that based on the same experimental data, SRSM has come closer than RSM reliability to approximating Monte Carlo method(MCM); while SRSM(17.296 s) needs far less running time than MCM(10958 s) and RSM(9840 s). Therefore,under the same simulation conditions, SRSM has the largest analysis efficiency, and can be considered a feasible and valid method to analyze structural reliability.

Time-variant reliability analysis of three-dimensional slopes based on Support Vector Machine method

In the reliability analysis of slope, the performance functions derived from the most available stability analysis procedures of slopes are usually implicit and cannot be solved by first-order second-moment approach. A new reliability analysis approach was presented based on three-dimensional Morgenstern-Price method to investigate three-dimensional effect of landslide in stability analyses. To obtain the reliability index, Support Vector Machine (SVM) was applied to approximate the performance function. The time-consuming of this approach is only 0.028% of that using Monte-Carlo method at the same computation accuracy. Also, the influence of time effect of shearing strength parameters of slope soils on the long-term reliability of three-dimensional slopes was investigated by this new approach. It is found that the reliability index of the slope would decrease by 52.54% and the failure probability would increase from 0.000 705% to 1.966%. In the end, the impact of variation coefficients of c and f on reliability index of slopes was taken into discussion and the changing trend was observed.

Analysis of the Improvement Methods for Equipment Maintenance Support

According to military requirement, and based on the problems of equipment maintenance support methods in high-tech battles, each element supporting equipment maintenance is analyzed, and the methods for improving equipment maintenance are proposed.

REQUIREMENTS AND DESIGN METHOD FOR MATCHING AIRCRAFT GUNS WITH THEIR SUPPORTING STRUCTURE

In aircraft structural dynamic design the matching of guns with their supportingstructure is one of the most important tasks on which hinges the success or failure of thestructural design.The design curves for matching guns with their supporting structure can be obtained fromresponse calculations of the plate-spring system supporting the gun on the ground,the modelstructure tested on the ground and the actual structure.A set of matching curves is given forengineering application.Then,the matching design can be accomplished by means of impactload spectrograms so as to perform an optimal structural design and to make further improvementson dynamic design program.

Elaboration of an Easy Aqueous Sol-Gel Method for the Synthesis of Micro- and Mesoporous <i>γ</i>-Al₂O₃Supports

An aqueous sol-gel method for the synthesis of γ-Al2O3 supports has been developed for the use in tar reforming applications. It was determined the influences of two different aluminum precursors (aluminum sec-butoxide (Al[OCH(CH3)CH2CH3]3) and aluminum nitrate (Al(NO3)3)) on the textural and crystallographic properties of Al2O3 supports. Only the formation of γ-Al2O3 is aimed in order to use these alumina materials as catalytic supports, because it presents high specific surface area and pore volume values. Additionally, the synthesis of γ-Al2O3 was realized with the use of a functionalized silicon precursor, [3-(2-aminoethylamino)propyl]trimethoxysilane, called EDAS. By the presence of an ethylenediamine group in this molecule, it is possible to chelate metallic ions and to highly increase their dispersion at a molecular level during the synthesis of metallic catalysts supported on alumina, which is an asset for catalytic applications. So it was developed a synthesis sol-gel procedure for the cogelation between the functionalized silicon alkoxide EDAS and alumina precursor. The alumina supports synthesized with Al(NO3)3 as precursor presented higher porous values than the ones obtained with aluminium sec-butoxide precursor. Since nitrate salts are much easier to handle than alkoxides, these observations allowed validating Al(NO3)3 as aluminum source for the future synthesis procedures for metallic catalysts supported on alumina.

顶棒支撑法复位髓内钉固定治疗难复性股骨转子间骨折的临床效果

目的分析顶棒支撑法复位髓内钉固定治疗难复性股骨转子间骨折的临床效果。方法于2020年8月至2022年8月在南阳市中心医院收集病例展开研究,将严格按照纳排标准筛选的106例难复性股骨转子间骨折患者作为研究对象,根据随机数字表法分为研究组与对照组,各53例。对照组接受切开或有限切开复位结合髓内钉固定治疗,研究组接受顶棒支撑法复位髓内钉固定。统计对比两组患者围手术期情况、骨折复位质量、术后恢复情况;对比两组患者术前、术后6个月髋关节功能评分;对比两组并发症发生率。结果研究组手术时间、骨折复位时间较对照组短,手术出血量较对照组少(P<0.05)。研究组骨折复位质量优于对照组(P<0.05)。研究组骨折愈合、开始负重和住院时间较对照组短(P<0.05)。术后6个月,两组髋关节功能评分均较术前提高,研究组高于对照组(P<0.05)。研究组并发症发生率[5.66%(3/53)]较对照组[18.87%(10/53)]低(P<0.05)。结论采用顶棒支撑法复位髓内钉固定治疗难复性股骨转子间骨折可减轻对机体的创伤,降低并发症发生率,提高复位效果,促进骨折愈合和髋关节功能恢复。

Krylov Iterative Methods for Support Vector Machines to Classify Galaxy Morphologies

Large catalogues of classified galaxy images have been useful in many studies of the universe in astronomy. There are too many objects to classify manually in the Sloan Digital Sky Survey, one of the premier data sources in astronomy. Therefore, efficient machine learning and classification algorithms are required to automate the classifying process. We propose to apply the Support Vector Machine (SVM) algorithm to classify galaxy morphologies and Krylov iterative methods to improve runtime of the classification. The accuracy of the classification is measured on various categories of galaxies from the survey. A three-class algorithm is presented that makes use of multiple SVMs. This algorithm is used to assign the categories of spiral, elliptical, and irregular galaxies. A selection of Krylov iterative solvers are compared based on their efficiency and accuracy of the resulting classification. The experimental results demonstrate that runtime can be significantly improved by utilizing Krylov iterative methods without impacting classification accuracy. The generalized minimal residual method (GMRES) is shown to be the most efficient solver to classify galaxy morphologies.

A Review of the Key Points in the Design of Small-Radius Curved Ramp Bridges

This article explores the fundamentals of small-radius curved ramp bridges.It covers the selection of box girder spans,support methods,and forms,along with design optimization techniques for this type of bridge structure.The purpose of this paper is to provide robust support for enhancing the design quality of these bridges and ensuring their efficacy in real-world applications.

基于空间投影和聚类划分的SVR加速算法

数据不仅能产生价值,还对统计学的科学发展提供了动力。随着科技的飞速发展,海量数据得以涌现,但大规模的数据会导致很多传统处理方法很难满足各领域对数据分析的需求。面对海量数据时代学习算法的低效性,分治法通常被认为是解决这一问题最直接、最广泛使用的策略。SVR是一种强大的回归算法,在模式识别和数据挖掘等领域有广泛应用。然而在处理大规模数据时,SVR训练效率低。为此,该文利用分治思想提出一种基于空间投影和聚类划分的SVR加速算法(PKM-SVR)。利用投影向量将数据投影到二维空间;利用聚类方法将数据空间划分为k个互不相交的区域;在每个区域上训练SVR模型;利用每个区域的SVR模型预测落入同一区域的待识别样本。在标准数据集上与传统的数据划分方法进行对比实验,实验结果表明该算法训练速度较快,并表现出更好的预测性能。

基于广域信息处理的配电网故障隔离技术研究

针对分布式电源并入配电网后,传统算法进行故障检测时存在定位准确度偏低、反应速度较慢的问题,文中基于广域信息处理技术提出了一种配电网故障隔离方法。该方法采用模态分解算法将故障复杂信号分解为多种类基础小信号,使用支持向量机对这些小信号进行数据分类。但由于传统支持向量机的收敛速度较慢,因此通过引入粒子群算法对其参数加以优化,从而提升模型的运算速度。实验结果表明,在加入分布式电源的电网中,所提算法的故障定位准确率为96.7%,平均运行时间则为43.9 s,且这两项参数在对比算法中均为最优。由此证明,该算法可应用于实际工程中,为配电网故障隔离提供技术支撑。

基于贪婪算法的云计算数据块节能存储仿真

针对云数据储存能量消耗大的问题,提出基于贪婪算法的云计算数据块节能存储方法。建立具有用户访问层、核心服务层和服务管理层的云计算架构,了解数据块产生过程和储存环境;将物理机利用率、能源消耗量和主机储存能力作为节能储存的约束条件,将待储存的数据块封装为虚拟机,利用贪婪算法描述虚拟机部署问题,构建贪婪算法下虚拟机分配环境;计算单个物理机和整个数据中心的数据块储存能力和资源请求能力,综合考虑虚拟机分配的相关向量,运算数据储存时的能量消耗;以总体能量最小为目标函数,将虚拟机分为主模块与备用模块,通过设置虚拟机状态转换规则来减少储存开销,实现节能储存。实验结果表明,上述方法在数据储存过程中能够有效减少服务器开启数量,节省储存功率,达到节能目的。

数据驱动儿童专科医院大型医疗设备运行评价体系建设

目的探索通过数据采集及分析评价儿童专科医院大型医疗设备运行水平的方法,提出大型医疗设备使用及配置建议。方法通过物联网终端采集设备运行数据,结合医院HIS、RIS、HRP等系统数据,建立儿童专科医院大型医疗设备评价指标体系,运用CRITIC法对单类、单台设备数据进行量化评价。结果医院大数据平台实现了对单台大型设备运行数据纵向分析并形成可视化图表,通过PC端及移动端展示。申康市级平台数据分析,实现对儿童专科医院大型设备运行水平的综合量化评价及使用配置建议。结论通过数据采集及分析,实现儿童专科医院大型设备运行评价体系建设,提升大型设备管理水平。

Element-free Galerkin method for free vibration of rectangular plates with interior elastic point supports and elastically restrained edges

The element-free Galerkin method is proposed to solve free vibration of rectangular plates with finite interior elastic point supports and elastically restrained edges.Based on the extended Hamilton's principle for the elastic dynamics system,the dimensionless equations of motion of rectangular plates with finite interior elastic point supports and the edge elastically restrained are established using the element-free Galerkin method.Through numerical calculation,curves of the natural frequency of thin plates with three edges simply supported and one edge elastically restrained,and three edges clamped and the other edge elastically restrained versus the spring constant,locations of elastic point support and the elastic stiffness of edge elastically restrained are obtained.Effects of elastic point supports and edge elastically restrained on the free vibration characteristics of the thin plates are analyzed.

基于纸张纤维特征的纸页抗张强度智能模拟及预测研究

对纸页抗张强度进行智能模拟,有助于更好地对某种纸页的性能进行分析甚至预测。基于此,针对现有纸页抗张强度模拟方法的缺陷进行总结,认为现有典型Page分析模型存在客观性分析不足等问题,结合偏最小二乘法、支持向量机等构建了一种基于造纸纤维特性的纸页抗张强度智能模拟模型,借助该模型对某种典型纸页的性能进行模拟分析。测试结果表明:该模型能够高效、准确地对纸页抗张强度进行预测,与传统模型相比具有更强的实用性。