期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到31篇文章
< 1 2 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Prophage mediate the emergence of NDM-13-positive monophasic Salmonella Indiana by imprecise excision 认领 引用
1
作者 Zhenyu Wang Yue Jiang +3 位作者 Pengyun Shao Xinan Jiao Jing Wang Qiuchun Li 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2026年第5期2178-2182,共5页
Salmonella,a prominent foodborne pathogen,presents a serious threat to both humans and animals,causing severe diseases like typhoid,paratyphoid,and various gastrointestinal conditions,including diarrhea,vomiting,and g... Salmonella,a prominent foodborne pathogen,presents a serious threat to both humans and animals,causing severe diseases like typhoid,paratyphoid,and various gastrointestinal conditions,including diarrhea,vomiting,and gastroenteritis(Mead et al.1999;Majowicz et al.2010;Liu et al.2025).Until now,more than 2,600 serovars of Salmonella enterica have been identified(Lu et al.2025),among which S.Indiana is highly prevalent in poultry,particularly in chicken and turkey(EFSA and ECDC 2020).Since its first isolation from an infant in the United States in 1955,reports of S.Indiana infections have been steadily increasing worldwide,with most cases linked to poultry consumption and characterized by gastroenteritis and diarrhea(Bai et al.2015;Chao et al.2017;Du et al.2022).Traditional slide agglutination tests for serotyping have limited ability to distinguish monophasic variants,such as S.Typhimurium and monophasic S.Typhimurium. 展开更多
关键词 prophage salmonella enterica Salmonella Indiana poultry gastroenteritis NDM serovars imprecise excision
暂未订购 下载PDF
A novel imprecise stochastic process model for time-variant or dynamic uncertainty quantification 认领 引用 被引量：5
2
作者 Jinwu LI Chao JIANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2022年第9期255-267,共13页
This paper proposes a novel model named as “imprecise stochastic process model” to handle the dynamic uncertainty with insufficient sample information in real-world problems. In the imprecise stochastic process mode... This paper proposes a novel model named as “imprecise stochastic process model” to handle the dynamic uncertainty with insufficient sample information in real-world problems. In the imprecise stochastic process model, the imprecise probabilistic model rather than a precise probability distribution function is employed to characterize the uncertainty at each time point for a time-variant parameter, which provides an effective tool for problems with limited experimental samples. The linear correlation between variables at different time points for imprecise stochastic processes is described by defining the auto-correlation coefficient function and the crosscorrelation coefficient function. For the convenience of analysis, this paper gives the definition of the P-box-based imprecise stochastic process and categorizes it into two classes: parameterized and non-parameterized P-box-based imprecise stochastic processes. Besides, a time-variant reliability analysis approach is developed based on the P-box-based imprecise stochastic process model,through which the interval of dynamic reliability for a structure under uncertain dynamic excitations or time-variant factors can be obtained. Finally, the effectiveness of the proposed method is verified by investigating three numerical examples. 展开更多
关键词 Dynamic reliability analysis Epistemic uncertainty Imprecise random variable Imprecise stochastic process P-box model Time-variant uncertainty
暂未订购 下载PDF
Augmented line sampling and combination algorithm for imprecise time-variant reliability analysis 认领 引用
3
作者 Xiukai YUAN Weiming ZHENG +1 位作者 Yunfei SHU Yiwei DONG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2024年第12期258-274,共17页
Assessment of imprecise time-variant reliability in engineering is a critical task when accounting for both the variability of structural properties and loads over time and the presence of uncertainties involved in th... Assessment of imprecise time-variant reliability in engineering is a critical task when accounting for both the variability of structural properties and loads over time and the presence of uncertainties involved in the ambiguity of parameters simultaneously.To estimate the Imprecise Time-variant Failure Probability Function(ITFPF)and derive the imprecise reliability results as a byproduct,Adaptive Combination Augmented Line Sampling(ACALS)is proposed.It consists of three integrated features:Augmented Line Sampling(ALS),adaptive strategy,and the optimal combination.ALS is adopted as an efficient analysis tool to obtain the failure probability function w.r.t.imprecise parameters.Then,the adaptive strategy iteratively applies ALS while considering both imprecise parameters and time simultaneously.Finally,the optimal combination algorithm collects all result components in an optimal manner to minimize the Coefficient of Variance(C.o.V.)of the ITFPF estimate.Overall,the proposed ACALS method outperforms the original ALS method by efficiently estimating the ITFPF while guaranteeing a minimal C.o.V.Thus,the proposed approach can serve as an effective tool for imprecise time-variant reliability analysis in real engineering applications.Several examples are presented to demonstrate the superiority of the proposed approach in addressing the challenges of estimating the ITFPF. 展开更多
关键词 Time-variant reliability Imprecise reliability Line sampling Adaptive strategy Combination algorithm
暂未订购 下载PDF
Structural Reliability Modeling Based on Imprecise Probability Theory under Insufficient Data 认领 引用
4
作者 刘征 米金华 +2 位作者 吕志强 李彦锋 黄洪钟 《Journal of Donghua University(English Edition)》 EI CAS 2015年第6期1011-1014,共4页
Traditional structural reliability analysis methods adopt precise probabilities to quantify uncertainties and they are suitable for systems with sufficient statistical data.However,the problem of insufficient data is ... Traditional structural reliability analysis methods adopt precise probabilities to quantify uncertainties and they are suitable for systems with sufficient statistical data.However,the problem of insufficient data is often encountered in practical engineering.Thus,structural reliability analysis methods under insufficient data have caught more and more attentions in recent years and a lot of nonprobabilistic reliability analysis methods are put forward to deal with the problem of insufficient data.Non-probabilistic structural reliability analysis methods based on fuzzy set,Dempster-Shafer theory,interval analysis and other theories have got a lot of achievements both in theoretical and practical aspects and they have been successfully applied in structural reliability analysis of largescale complex systems with small samples and few statistical data.In addition to non-probabilistic structural reliability analysis methods,structural reliability analysis based on imprecise probability theory is a new method proposed in recent years.Study on structural reliability analysis using imprecise probability theory is still at the start stage,thus the generalization of imprecise structural reliability model is very important.In this paper,the imprecise probability was developed as an effective way to handle uncertainties,the detailed procedures of imprecise structural reliability analysis was introduced,and several specific imprecise structural reliability models which are most effective for engineering systems were given.At last,an engineering example of a cantilever beam was given to illustrate the effectiveness of the method emphasized here.By comparing with interval structural reliability analysis,the result obtained from imprecise structural reliability model is a little conservative than the one resulted from interval structural reliability analysis for imprecise structural reliability analysis model considers that the probability of each value is taken from an interval. 展开更多
关键词 imprecise probability structural reliability cantilever beam interval analysis
暂未订购 下载PDF
Imprecise Computation Based Real-time Fault Tolerant Implementation for Model Predictive Control 认领 引用
5
作者 周平方 谢剑英 《Journal of Donghua University(English Edition)》 EI CAS 2006年第1期148-150,共3页
Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is pro... Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is proposed for MPC, according to the solving process of quadratic programming (QP) problem. In this algorithm, system stability is guaranteed even when computation resource is not enough to finish optimization completely. By this kind of graceful degradation, the behavior of real-time control systems is still predictable and determinate. The algorithm is demonstrated by experiments on servomotor, and the simulation results show its effectiveness. 展开更多
关键词 model predictive control fault tolerance imprecise computation real-Time control
暂未订购 下载PDF
Imprecise Probability Method with the Power-Normal Model for Accelerated Life Testing 认领 引用
6
作者 YIN Yichao HUANG Hongzhong LIU Zheng 《Journal of Shanghai Jiaotong university(Science)》 EI 2019年第6期805-810,共6页
We present a new nonparametric predictive inference(NPI)method using a power-normal model for accelerated life testing(ALT).Combined with the accelerating link function and imprecise probability theory,the proposed me... We present a new nonparametric predictive inference(NPI)method using a power-normal model for accelerated life testing(ALT).Combined with the accelerating link function and imprecise probability theory,the proposed method is a feasible way to predict the life of the product using ALT failure data.To validate the method,we run a series of simulations and conduct accelerated life tests with real products.The NPI lower and upper survival functions show the robustness of our method for life prediction.This is a continuous research,and some progresses have been made by updating the link function between different stress levels.We also explain how to renew and apply our model.Moreover,discussions have been made about the performance. 展开更多
关键词 accelerated life testing(ALT) power-normal model lower and upper survival functions nonparametric predictive inference(NPI) imprecise probability
暂未订购 下载PDF
Distributed QoS multicast routing in networks with imprecise state information 认领 引用 被引量：4
7
作者 Yan Xin Li Layuan 《Journal of Systems Engineering and Electronics》 2005年第4期866-874,共9页
The goal of quality-of-service （QoS） multicast routing is to establish a multicast tree which satisfies certain constraints on bandwidth, delay and other metrics. The network state information maintained at every no... The goal of quality-of-service （QoS） multicast routing is to establish a multicast tree which satisfies certain constraints on bandwidth, delay and other metrics. The network state information maintained at every node is often im- precise in a dynamic environment because of non-negligible propagation delay of state messages, periodic updates due to overhead concern, and hierarchical state aggregation. The existing QoS multicast routing algorithms do not provide satisfactory performance with imprecise state information. We propose a distributed QoS multicast routing scheme based on traffic lights, called QMRI algorithm, which can probe multiple feasible tree branches, and select the optimal or near-optimal branch through the UR or TL mode for constructing a multicast tree with QoS guarantees if it exists. The scheme is designed to work with imprecise state information. The proposed algorithm considers not only the QoS requirements but also the cost optimality of the multicast tree. The correctness proof and the complexity analysis about the QMRI algorithm are also given. In addition, we develop NS2 so that it is able to simulate the imprecise network state information. Extensive simulations show that our algorithm achieves high call-admission ratio and low-cost multicast trees with modest message overhead. 展开更多
关键词 quality-of-service muting multicast imprecise state traffic lights simulation.
暂未订购 下载PDF
Research on characterization methods for track irregularities 认领 引用 被引量：2
8
作者 Lifeng Xin Lei Xu +3 位作者 Jiaxin Zhang Menglin Pei Jianfeng Mao Dangxiong Wang 《Railway Engineering Science》 EI 2026年第1期25-39,共15页
The characterization of track irregularities is crucial in railway dynamics,as track irregularities are the primary source of internal excitation in railway systems.In this paper,three mathematical models are proposed... The characterization of track irregularities is crucial in railway dynamics,as track irregularities are the primary source of internal excitation in railway systems.In this paper,three mathematical models are proposed to characterize the track irregularities under different circumstances.The first model is a novel explicit track spectrum function,which performs better in reflecting the inherent periodic components of track irregularities than the existing track spectra.On this foundation,the second model,a parameterized track spectrum random model,is proposed to represent the vast measured track irregularities from the probabilistic perspective.Finally,the third model,an imprecise track spectrum interval model based on a neighborhood uniform sampling Bootstrap method,is presented to identify the confidential interval of the track spectra when the track irregularity data are limited.Three examples are illustrated to demonstrate the feasibility of the three track irregularity models in characterizing the track irregularities in different conditions.This research can help capture the railway deformation status and optimize track maintenance strategies. 展开更多
关键词 Railway Track irregularity Power spectral density Characterization Random model Imprecise track spectrum
暂未订购 下载PDF
A Fast Prediction Method in Deep Neural Networks for Three-Dimensional Ship Wave Field 认领 引用
9
作者 WANG Qiang ZHAN Cheng-sheng +1 位作者 FENG Bai-wei LI Heng 《China Ocean Engineering》 SCIE EI CSCD 2026年第2期357-368,共12页
This paper presents a novel fast prediction method for ship waves through the development of a neural network model called Ship Wave Residual Network(SWRN).The study employs a Wigley hull model for analysis,with datas... This paper presents a novel fast prediction method for ship waves through the development of a neural network model called Ship Wave Residual Network(SWRN).The study employs a Wigley hull model for analysis,with datasets generated through Computational Fluid Dynamics(CFD)simulations.A comprehensive validation study addresses simulation uncertainties through the grid convergence index(GCI),Monte Carlo method,and Chebyshev inequality.The SWRN framework is applied to datasets encompassing various ship form parameters and Froude numbers.The accuracy of the neural network is evaluated by comparing ship-generated wave field and total resistance predictions from SWRN and CFD for hull forms and Froude numbers beyond the training datasets.Results demonstrate that SWRN training requires only 40%of the computational resources needed for a single CFD simulation.The trained model generates predictions for ship wave fields and total resistance under calm water conditions within seconds,maintaining acceptable accuracy levels.This prediction technology establishes a foundation for AI-accelerated solutions in ship-generated flow field analysis. 展开更多
关键词 ship wave field deep learning fast prediction CFD imprecise probability
暂未订购 下载PDF
Bayesian Network Based Imprecise Probability Estimation Method for Wind Power Ramp Events 认领 引用 被引量：2
10
作者 Yuanchun Zhao Wenli Zhu +1 位作者 Ming Yang Mengxia Wang 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2021年第6期1510-1519,共10页
Although wind power ramp events(WPREs)are relatively scarce,they can inevitably deteriorate the stability of power system operation and bring risks to the trading of electricity market.In this paper,an imprecise condi... Although wind power ramp events(WPREs)are relatively scarce,they can inevitably deteriorate the stability of power system operation and bring risks to the trading of electricity market.In this paper,an imprecise conditional probability estimation method for WPREs is proposed based on the Bayesian network(BN)theory.The method uses the maximum weight spanning tree(MWST)and greedy search(GS)to build a BN that has the highest fitting degree with the observed data.Meanwhile,an extended imprecise Dirichlet model(IDM)is developed to estimate the parameters of the BN,which quantificationally reflect the ambiguous dependencies among the random ramp event and various meteorological variables.The BN is then applied to predict the interval probability of each possible ramp state under the given meteorological conditions,which is expected to cover the target probability at a specified confidence level.The proposed method can quantify the uncertainty of the probabilistic ramp event estimation.Meanwhile,by using the extracted dependencies and Bayesian rules,the method can simplify the conditional probability estimation and perform reliable prediction even with scarce samples.Test results on a real wind farm with three-year operation data illustrate the effectiveness of the proposed method. 展开更多
关键词 Bayesian network(BN) conditional probability imprecise Dirichlet model(IDM) imprecise probability wind power ramp events
Decomposition for a new kind of imprecise information system 认领 引用 被引量：1
11
作者 Shaobo DENG Sujie GUAN +2 位作者 Min LI Lei WANG Yuefei SUI 《Frontiers of Computer Science》 SCIE EI CSCD 2018年第2期376-395,共20页
In this paper, we first propose a new kind of imprecise information system, in which there exist conjunctions （∧＇s）, disjunctions （∨＇s） or negations （ ＇s）. Second, this paper discusses the relation that onl... In this paper, we first propose a new kind of imprecise information system, in which there exist conjunctions （∧＇s）, disjunctions （∨＇s） or negations （ ＇s）. Second, this paper discusses the relation that only contains ∧＇s based on relational database theory, and gives the syntactic and semantic interpretation for A and the definitions of decomposition and composition and so on. Then, we prove that there exists a kind of decomposition such that if a relation satisfies some property then it can be decomposed into a group of classical relations （relations do not contain ∧） that satisfy a set of functional dependencies and the original relation can be synthesized from this group of classical relations. Meanwhile, this paper proves the soundness theorem and the completeness theorem for this decomposition. Consequently, a relation containing ∧＇s can be equivalently transformed into a group of classical relations that satisfy a set of functional dependencies. Finally, we give the definition that a relation containing ∧＇s satisfies a set of functional dependencies. Therefore, we can introduce other classical relational database theories to discuss this kind of relation. 展开更多
关键词 imprecise information systems decomposition composition soundness and completeness
暂未订购 下载PDF
MERGING FUZZY STATISTICAL DATA WITH IMPRECISE PRIOR INFORMATION 认领 引用
12
作者 Olgierd HRYNIEWICZ 《Journal of Systems Science and Systems Engineering》 SCIE EI 2006年第1期70-82,共13页
Solving complex decision problems requires the usage of information from different sources. Usually this information is uncertain and statistical or probabilistic methods are needed for its processing. However, in man... Solving complex decision problems requires the usage of information from different sources. Usually this information is uncertain and statistical or probabilistic methods are needed for its processing. However, in many cases a decision maker faces not only uncertainty of a random nature but also imprecision in the description of input data that is rather of linguistic nature. Therefore, there is a need to merge uncertainties of both types into one mathematical model. In the paper we present methodology of merging information from imprecisely reported statistical data and imprecisely formulated fuzzy prior information. Moreover, we also consider the case of imprecisely defined loss functions. The proposed methodology may be considered as the application of fuzzy statistical methods for the decision making in the systems analysis. 展开更多
关键词 Bayes decisions imprecise information fuzzy statistical data possibilistic decisions
暂未订购 下载PDF
Importance measures for imprecise probability distributions and their sparse grid solutions 认领 引用 被引量：2
13
作者 WANG Pan LU ZhenZhou CHENG Lei 《Science China(Technological Sciences)》 SCIE EI CAS 2013年第7期1733-1739,共7页
For the imprecise probability distribution of structural system, the variance based importance measures (IMs) of the inputs are investigated, and three IMs are defined on the conditions of random distribution paramete... For the imprecise probability distribution of structural system, the variance based importance measures (IMs) of the inputs are investigated, and three IMs are defined on the conditions of random distribution parameters, interval distribution parameters and the mixture of those two types of distribution parameters. The defined IMs can reflect the influence of the inputs on the output of the structural system with imprecise distribution parameters, respectively. Due to the large computational cost of the variance based IMs, sparse grid method is employed in this work to compute the variance based IMs at each reference point of distribution parameters. For the three imprecise distribution parameter cases, the sparse grid method and the combination of sparse grid method with genetic algorithm are used to compute the defined IMs. Numerical and engineering examples are em-ployed to demonstrate the rationality of the defined IMs and the efficiency of the applied methods. 展开更多
关键词 imprecise probability distribution importance measure sparse grid method genetic algorithm
暂未订购 下载PDF
An Interval-valued Approach to Calculation ofNonequilibriumThermodynamics with Imprecise Information 认领 引用
14
作者 XU Jiuping LUO Jiuli 《Systems Science and Systems Engineering》 1999年第1期119-128,共10页
The research of the imprecision of a nonequilibrium thermodynamic system is justifiedby the structural and parametric uncertainties of such systems. The paper gives an interval-valuedformulation of the phenomenologica... The research of the imprecision of a nonequilibrium thermodynamic system is justifiedby the structural and parametric uncertainties of such systems. The paper gives an interval-valuedformulation of the phenomenological equations and shows a realistic approach for studying the entropyproduction in Physical systems, the time trajectories of chemical reactions, etc. Using algorithms derivedfor special reaction systems, bundles of time trajectories with prescribed boundary possibility measuresare calculated. 展开更多
关键词 interval-valued number measure of imprecision nonequilibrium thermodynamics imprecise dynamic systems
Building a directed evolution-genome editing pipeline for metabolic traits in specialty crop breeding 认领 引用
15
作者 Anuran K.Gayen Laura M.Carmona Rojas +3 位作者 Zhen Fan Seonghee Lee Vance M.Whitaker Andrew D.Hanson 《Horticulture Research》 SCIE CSCD 2025年第11期381-388,共8页
CRISPR/Cas genome editing(GE)technology has opened unprecedented opportunities for breeding specialty and commodity crops[1-3].The advent of base editors and prime editors is enabling multiple precise edits within a g... CRISPR/Cas genome editing(GE)technology has opened unprecedented opportunities for breeding specialty and commodity crops[1-3].The advent of base editors and prime editors is enabling multiple precise edits within a gene,which have far more potential than the imprecise insertions or deletions(indels)made by first-generation GE technology.Indels typically just knock out genes or gene domains[1,2].Examples of such loss-of-function GE in a specialty crop(tomato)are raising sugar content by knocking out two protein kinases[4]and raisingγ-aminobutyrate(GABA)content by deleting the autoinhibitory domain of glutamate decarboxylases[5]. 展开更多
关键词 base editors breeding specialty commodity crops genome editing knocking two prote raising sugar content prime editors knock genes gene domains examples imprecise insertions deletions indels made
暂未订购 下载PDF
The First-Order Comprehensive Sensitivity Analysis Methodology (1st-CASAM) for Scalar-Valued Responses: I. Theory 认领 引用 被引量：2
16
作者 Dan Gabriel Cacuci 《American Journal of Computational Mathematics》 2020年第2期275-289,共15页
This work presents the first-order comprehensive adjoint sensitivity analysis methodology (1st-CASAM) for computing efficiently, exactly, and exhaustively, the first-order sensitivities of scalar-valued responses (res... This work presents the first-order comprehensive adjoint sensitivity analysis methodology (1st-CASAM) for computing efficiently, exactly, and exhaustively, the first-order sensitivities of scalar-valued responses (results of interest) of coupled nonlinear physical systems characterized by imprecisely known model parameters, boundaries and interfaces between the coupled systems. The 1st-CASAM highlights the conclusion that response sensitivities to the imprecisely known domain boundaries and interfaces can arise both from the definition of the system’s response as well as from the equations, interfaces and boundary conditions defining the model and its imprecisely known domain. By enabling, in premiere, the exact computations of sensitivities to interface and boundary parameters and conditions, the 1st-CASAM enables the quantification of the effects of manufacturing tolerances on the responses of physical and engineering systems. Ongoing research will generalize the methodology presented in this work, aiming at computing exactly and efficiently higher-order response sensitivities for coupled systems involving imprecisely known interfaces, parameters, and boundaries. 展开更多
关键词 Adjoint Sensitivity Analysis (1st-CASAM) Response Sensitivities for Coupled Nonlinear Systems Imprecisely Known Interfaces Imprecisely Known Parameters Imprecisely Known Boundaries
暂未订购 下载PDF
Novel dynamic evidential Petri net for system reliability analysis 认领 引用 被引量：3
17
作者 Wensheng Peng Jianguo Zhang Jinyang Zhang 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2017年第5期1019-1027,共9页
This paper proposes a novel dynamic Petri net (PN) model based on Dempster-Shafer (D-S) evidence theory, and this improved evidential Petri net (EPN) model is used in knowledge inference and reliability analysis of co... This paper proposes a novel dynamic Petri net (PN) model based on Dempster-Shafer (D-S) evidence theory, and this improved evidential Petri net (EPN) model is used in knowledge inference and reliability analysis of complex mechanical systems. The EPN could take epistemic uncertainty such as interval information, subjective information into account by applying D-S evidence quantification theory. A dynamic representation model is also proposed based on the dynamic operation rules of the EPN model, and an improved artificial bee colony (ABC) algorithm is employed to proceed optimization calculation during the complex systems' learning process. The improved ABC algorithm and D-S evidence theory overcome the disadvantage of extremely subjective in traditional knowledge inference efficiently and thus could improve the accuracy of the EPN learning model. Through a simple numerical case and a satellite driving system analysis, this paper proves the superiority of the EPN and the dynamic knowledge representation method in reliability analysis of complex systems. 展开更多
关键词 evidence theory Petri net knowledge representation improved ABC algorithm imprecise information reliability
暂未订购 下载PDF
RBF neural network regression model based on fuzzy observations 认领 引用 被引量：3
18
作者 朱红霞 沈炯 苏志刚 《Journal of Southeast University(English Edition)》 EI CAS 2013年第4期400-406,共7页
A fuzzy observations-based radial basis function neural network （FORBFNN） is presented for modeling nonlinear systems in which the observations of response are imprecise but can be represented as fuzzy membership fu... A fuzzy observations-based radial basis function neural network （FORBFNN） is presented for modeling nonlinear systems in which the observations of response are imprecise but can be represented as fuzzy membership functions. In the FORBFNN model, the weight coefficients of nodes in the hidden layer are identified by using the fuzzy expectation-maximization （ EM ） algorithm, whereas the optimal number of these nodes as well as the centers and widths of radial basis functions are automatically constructed by using a data-driven method. Namely, the method starts with an initial node, and then a new node is added in a hidden layer according to some rules. This procedure is not terminated until the model meets the preset requirements. The method considers both the accuracy and complexity of the model. Numerical simulation results show that the modeling method is effective, and the established model has high prediction accuracy. 展开更多
关键词 radial basis function neural network （RBFNN） fuzzy membership function imprecise observation regression model
暂未订购 下载PDF
Quasi-Bayesian software reliability model with small samples 认领 引用 被引量：2
19
作者 张金 涂俊翔 +1 位作者 陈卓宁 严晓光 《Journal of Shanghai University(English Edition)》 2009年第4期301-304,共4页
In traditional Bayesian software reliability models, it was assume that all probabilities are precise. In practical applications the parameters of the probability distributions are often under uncertainty due to stron... In traditional Bayesian software reliability models, it was assume that all probabilities are precise. In practical applications the parameters of the probability distributions are often under uncertainty due to strong dependence on subjective information of experts＇ judgments on sparse statistical data. In this paper, a quasi-Bayesian software reliability model using interval-valued probabilities to clearly quantify experts＇ prior beliefs on possible intervals of the parameters of the probability distributions is presented. The model integrates experts＇ judgments with statistical data to obtain more convincible assessments of software reliability with small samples. For some actual data sets, the presented model yields better predictions than the Jelinski-Moranda （JM） model using maximum likelihood （ML）. 展开更多
关键词 software reliability model imprecise probability quasi-Bayesian analysis expert judgment
暂未订购 下载PDF
An efficient uncertainty propagation method for nonlinear dynamics with distribution-free P-box processes 认领 引用 被引量：1
20
作者 Licong ZHANG Chunna LI +3 位作者 Hua SU Yuannan XU Andrea Da RONCH Chunlin GONG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2024年第12期116-138,共23页
The distribution-free P-box process serves as an effective quantification model for timevarying uncertainties in dynamical systems when only imprecise probabilistic information is available.However,its application to ... The distribution-free P-box process serves as an effective quantification model for timevarying uncertainties in dynamical systems when only imprecise probabilistic information is available.However,its application to nonlinear systems remains limited due to excessive computation.This work develops an efficient method for propagating distribution-free P-box processes in nonlinear dynamics.First,using the Covariance Analysis Describing Equation Technique(CADET),the dynamic problems with P-box processes are transformed into interval Ordinary Differential Equations(ODEs).These equations provide the Mean-and-Covariance(MAC)bounds of the system responses in relation to the MAC bounds of P-box-process excitations.They also separate the previously coupled P-box analysis and nonlinear-dynamic simulations into two sequential steps,including the MAC bound analysis of excitations and the MAC bounds calculation of responses by solving the interval ODEs.Afterward,a Gaussian assumption of the CADET is extended to the P-box form,i.e.,the responses are approximate parametric Gaussian P-box processes.As a result,the probability bounds of the responses are approximated by using the solutions of the interval ODEs.Moreover,the Chebyshev method is introduced and modified to efficiently solve the interval ODEs.The proposed method is validated based on test cases,including a duffing oscillator,a vehicle ride,and an engineering black-box problem of launch vehicle trajectory.Compared to the reference solutions based on the Monte Carlo method,with relative errors of less than 3%,the proposed method requires less than 0.2% calculation time.The proposed method also possesses the ability to handle complex black-box problems. 展开更多
关键词 Nonlinear dynamics Uncertainty propagation Imprecise probability Distribution-free P-box processes Chebyshev method
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈