Selection Method for Kernel Function in Nonparametric Extrapolation Based on Multicriteria Decision-Making Technology

Wang, Jixin; Liu, Yan; Zeng, Xiaohua; Zhou, Zhenping; Wang, Naixiang; Shen, Wanghao

doi:10.1155/2013/391273

Cited by 5 publications

(7 citation statements)

References 19 publications

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“…Analyzing possibilities of DEMATEL to be applied in hybrid methods DEMATEL Lee et al, 2013 [193] Combining imperialist competitive algorithm and MCDM to optimize production system ICA, TOPSIS Fallah-Jamshidi and Amiri, 2013 [194] Solving selection problem of kernel function, an example of power split device of hybrid electrical vehicles AHP, Entropy Wang et al, 2013 [195] Solving problems under risk and uncertainty by applying prospect theory and fuzzy numbers; an example of oil split in the see Fuzzy logic, Prospect theory, fuzzy TODIM Krohling and de Souza, 2012 [196] Mathematical Programming (MP); Arti cial Intelligence (AI); Fuzzy Inference System (FIS); Integer Programming (IP); Imperialist Competitive Algorithm (ICA); TOmada de Decisão interative multicrit erio (in Portuguese), that means interactive and multiple attribute decision making (TODIM …”

Section: Discussionmentioning

confidence: 99%

Hybrid Multiple Criteria Decision Making Methods: A Review of Applications in Engineering

et al. 2016

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Abstract. To support evaluation and selection processes in engineering, formal decisionmaking methods can be used. A great number of works applying diverse Multiple-Criteria Decision-Making (MCDM) techniques for engineering problems have been published recently. A new approach of hybrid MCDM methods has been developed, rapidly, during the past few years. The current paper aims at lling the gap and summarizing publications related to applications of hybrid MCDM for engineering. The study is limited solely to papers referred in Thomson Reuters Web of Science Core Collection academic database. It aims to review how the papers have been distributed by period of publishing and by country; multiple-criteria decision-making methods have been used, most frequently, in developing hybrid approaches and in domains the methods have been applied for. For a more detailed analysis of applications, journal articles from engineering research area were grouped by research domains and further by analyzed issues. Findings of the current review paper con rm that hybrid MCDM approaches, due to their abilities in integrating di erent techniques, can assist in handling miscellaneous information taking into account stakeholders' preferences when making decisions in engineering.

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Section: Discussionmentioning

confidence: 99%

Hybrid Multiple Criteria Decision Making Methods: A Review of Applications in Engineering

et al. 2016

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“…Wang et al [68] proposed a selection method for the kernel function and the multi-criteria decision making technique was successfully used to solve the problem of the kernel function selection. For the bandwidth selection, Heidenreich et al [69] reviewed the bandwidth selections for the kernel density estimation and some of the methods can be used in NPE.…”

Section: Nonparametric Extrapolation Methods (Npe)mentioning

confidence: 99%

“…In Wang et al [68], the selection of the kernel function was considered. Four kinds of kernel functions were illustrated; the extrapolation results are shown in Fig.…”

Section: Case Analysis Of Npementioning

confidence: 99%

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A Review of the Extrapolation Method in Load Spectrum Compiling

Wang¹,

Hong-bin²,

Li³

et al. 2016

SV-JME

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60 INTRODUCTIONIn engineering, many mechanical structures and components are subjected to complex and random loads, which determine the fatigue reliability and life of the machinery [1] and [2]. Thus, it is indispensable to conduct fatigue analysis and life prediction of the structures and components based on a load spectrum [3] and [4]. Currently, a load spectrum is widely used in the fields of aerospace [5] . In practice, a long-term load spectrum contains the complete load information, but it is difficult to be directly measured due to the restrictions of testing technology, as well as time and cost. Therefore, it is necessary to obtain a long-term load spectrum based on a short-term one.The traditional load spectrum compiling method multiplies a short-term load spectrum with a constant proportionality coefficient [15] to [17]. Since only the data measured in a finite time is repeated, the extreme loads that cannot be measured and have a greater impact on damage are ignored. Load extrapolation methods can overcome the above limitation of the traditional method. With the development of statistics and computer software, new methods have been applied to load extrapolation. In load spectrum compiling, results may vary from each other with different extrapolation methods. Therefore, selecting an appropriate load extrapolation method is very important, but that is difficult in practice. For a better understanding of the methods and to provide selection guidance, several commonly used extrapolation methods are reviewed and summarized based on the literature and illustrations in this paper.The extrapolation methods are classified as the parametric extrapolation method (PE), nonparametric extrapolation method (NPE) and quantile extrapolation method (QE). In PE, sample data is supposed to obey a known distribution, and the parameters in the function are estimated according to the load sample. In NPE, an extrapolated result is obtained because the density distribution with an arbitrary shape can be received based on a nonparametric density estimation. When the sample data has different load characteristics due to different working conditions and different operating behaviors in the testing process, QE can break the data into a series of clusters and computes the damage of each rainflow matrix. The literature and illustrations are presented to evaluate the extrapolation methods and the characteristics of various extrapolation methods, such as the critical factors, the advantages and disadvantages, and the application ranges, are summarized. Some potential research prospects are

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“…Besides, an evaluation criterion based on multi-criteria decisionmaking technology was provided to select the most appropriate model from the existing KDE models for NPRFE. 12 Compared with parametric models in the PRFE and LRFE, KDE model may be more suitable for the extrapolation of complex and random loads. It is datadriven as it does not need to make a hypothesis distribution for load samples and then the probability density of estimation point is obtained.…”

Section: Introductionmentioning

confidence: 99%

Non-parametric load extrapolation based on load extension for semi-axle of wheel loader

Wang

Jiang

2017

Advances in Mechanical Engineering

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Load extrapolation is the paramount step in compiling load spectra of the mechanical components. To avoid the limitation of the stationary processes in parametric extrapolation methods, the non-parametric extrapolation method is widely investigated in recent years. However, the accuracy of kernel density estimation of the large load cycles in existing non-parametric methods should be still improved. Aiming at this issue, a non-parametric rain-flow extrapolation method based on load extension is presented. In this method, combining with non-parametric extrapolation model and Markov chain Monte Carlo method, the measured load-time histories for semi-axle in different operating sections are extended and extrapolated. The extrapolated load spectra curves and the relative damage ratio are compared with the results obtained by the existing rain-flow extrapolation methods. The results show that the proposed method can realize the reasonable extrapolation of load-time histories.

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Selection Method for Kernel Function in Nonparametric Extrapolation Based on Multicriteria Decision-Making Technology

Cited by 5 publications

References 19 publications

Hybrid Multiple Criteria Decision Making Methods: A Review of Applications in Engineering

Hybrid Multiple Criteria Decision Making Methods: A Review of Applications in Engineering

A Review of the Extrapolation Method in Load Spectrum Compiling

Non-parametric load extrapolation based on load extension for semi-axle of wheel loader

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