The Experts below are selected from a list of 55899 Experts worldwide ranked by ideXlab platform
Dug Hun Hong - One of the best experts on this subject based on the ideXlab platform.
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the law of large numbers and Renewal Process for t related weighted fuzzy numbers on rp
Information Sciences, 2013Co-Authors: Dug Hun HongAbstract:This paper considers the law of large numbers for T-related weighted fuzzy variables whose underlying spaces are R^p. We provide new sufficient conditions that do not depend on the shape of fuzzy numbers and the additive generator of a t-norm T for the law of large numbers for T-related weighted fuzzy variables. The results provide a far-reaching generalization of previous findings on the law of large numbers for T-related fuzzy numbers. In addition, we prove T-related fuzzy Renewal theorems in which the inter-arrival time is characterized as weighted fuzzy numbers under t-norm-based fuzzy operations on R^p by using the law of large numbers for weighted fuzzy variables on R^p. We also investigate the law of large numbers and the Renewal Process for T-related fuzzy numbers on R^p with respect to the credibility measure, the chance measure, and the expected value.
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note on fuzzy random Renewal Process and Renewal rewards Process
The International Journal of Fuzzy Logic and Intelligent Systems, 2009Co-Authors: Dug Hun HongAbstract:Recently, Zhao et al. [Fuzzy Optimization and Decision Making (2007) 6, 279-295] characterized the interarrival times as fuzzy random variables and presented a fuzzy random elementary Renewal theorem on the limit value of the expected Renewal rate of the Process in the fuzzy random Renewal Process. They also depicted both the interarrival times and rewards are depicted as fuzzy random variables and provided fuzzy random Renewal reward theorem on the limit value of the long run expected reward per unit time in the fuzzy random Renewal reward Process. In this note, we simplify the proofs of two main results of the paper.
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Renewal Process with t related fuzzy inter arrival times and fuzzy rewards
Information Sciences, 2006Co-Authors: Dug Hun HongAbstract:In this paper, we consider a Renewal Process in which the inter-arrival times and rewards are characterized as fuzzy variables under t-norm-based fuzzy operations. A T-related fuzzy Renewal theorem and a fuzzy Renewal reward theorem are proved using a law of large numbers for fuzzy variables.
Mark D Plumbley - One of the best experts on this subject based on the ideXlab platform.
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improved multiple birdsong tracking with distribution derivative method and markov Renewal Process clustering
International Conference on Acoustics Speech and Signal Processing, 2013Co-Authors: Dan Stowell, Saso Musevic, Jordi Bonada, Mark D PlumbleyAbstract:Segregating an audio mixture containing multiple simultaneous bird sounds is a challenging task. However, birdsong often contains rapid pitch modulations, and these modulations carry information which may be of use in automatic recognition. In this paper we demonstrate that an improved spectrogram representation, based on the distribution derivative method, leads to improved performance of a segregation algorithm which uses a Markov Renewal Process model to track vocalisation patterns consisting of singing and silences.
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segregating event streams and noise with a markov Renewal Process model
Journal of Machine Learning Research, 2013Co-Authors: Dan Stowell, Mark D PlumbleyAbstract:We describe an inference task in which a set of timestamped event observations must be clustered into an unknown number of temporal sequences with independent and varying rates of observations. Various existing approaches to multi-object tracking assume a fixed number of sources and/or a fixed observation rate; we develop an approach to inferring structure in timestamped data produced by a mixture of an unknown and varying number of similar Markov Renewal Processes, plus independent clutter noise. The inference simultaneously distinguishes signal from noise as well as clustering signal observations into separate source streams. We illustrate the technique via synthetic experiments as well as an experiment to track a mixture of singing birds. Source code is available.
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segregating event streams and noise with a markov Renewal Process model
arXiv: Artificial Intelligence, 2012Co-Authors: Dan Stowell, Mark D PlumbleyAbstract:We describe an inference task in which a set of timestamped event observations must be clustered into an unknown number of temporal sequences with independent and varying rates of observations. Various existing approaches to multi-object tracking assume a fixed number of sources and/or a fixed observation rate; we develop an approach to inferring structure in timestamped data produced by a mixture of an unknown and varying number of similar Markov Renewal Processes, plus independent clutter noise. The inference simultaneously distinguishes signal from noise as well as clustering signal observations into separate source streams. We illustrate the technique via a synthetic experiment as well as an experiment to track a mixture of singing birds.
Ruiqing Zhao - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy random Renewal Process and Renewal reward Process
Fuzzy Optimization and Decision Making, 2007Co-Authors: Ruiqing Zhao, Wansheng Tang, Cheng WangAbstract:So far, there have been several concepts about fuzzy random variables and their expected values in literature. One of the concepts defined by Liu and Liu (2003a) is that the fuzzy random variable is a measurable function from a probability space to a collection of fuzzy variables and its expected value is described as a scalar number. Based on the concepts, this paper addresses two Processes--fuzzy random Renewal Process and fuzzy random Renewal reward Process. In the fuzzy random Renewal Process, the interarrival times are characterized as fuzzy random variables and a fuzzy random elementary Renewal theorem on the limit value of the expected Renewal rate of the Process is presented. In the fuzzy random Renewal reward Process, both the interarrival times and rewards are depicted as fuzzy random variables and a fuzzy random Renewal reward theorem on the limit value of the long-run expected reward per unit time is provided. The results obtained in this paper coincide with those in stochastic case or in fuzzy case when the fuzzy random variables degenerate to random variables or to fuzzy variables.
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random fuzzy Renewal Process
European Journal of Operational Research, 2006Co-Authors: Ruiqing Zhao, Wansheng Tang, Huaili YunAbstract:Abstract This paper attempts to discuss a random fuzzy Renewal Process based on random fuzzy theory. The interarrival times are characterized as nonnegative random fuzzy variables which is a more reasonable consideration in the real world. Under this setting, the rate of the random fuzzy Renewal Process is discussed and a random fuzzy elementary Renewal theorem is presented. Furthermore, the expected value of Renewals in an arbitrary interval is investigated and Blackwell’s theorem in random fuzzy sense is also established.
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fuzzy Renewal Process fuzzy Renewal reward Process and their applications
IEEE International Conference on Fuzzy Systems, 2004Co-Authors: Ruiqing Zhao, Wansheng Tang, Huaili YunAbstract:This work extends the work in Zhao and Liu on fuzzy Renewal Process and Renewal reward Process from continuous case to more general case. Fuzzy elementary Renewal theorem and fuzzy Renewal reward theorem are developed and shown how they can be applied to maintenance policies. Three kinds of maintenance policies- fuzzy age replacement policy, fuzzy block replacement policy and fuzzy inspection policy are discussed. The optimality functions studied are the long run expected costs per unit of time. Finally, a hybrid intelligent algorithm is employed to solve the models proposed in maintenance policies and to arrive at optimum policies. A numerical example is enumerated and the result indicates that the algorithm is effective.
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Renewal Process with fuzzy interarrival times and rewards
International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 2003Co-Authors: Ruiqing Zhao, Baoding LiuAbstract:This paper considers a Renewal Process in which the interarrival times and rewards are characterized as fuzzy variables. A fuzzy elementary Renewal theorem shows that the expected number of Renewals per unit time is just the expected reciprocal of the interarrival time. Furthermore, the expected reward per unit time is provided by a fuzzy Renewal reward theorem. Finally, a numerical example is presented for illustrating the theorems introduced in the paper.
Min Xie - One of the best experts on this subject based on the ideXlab platform.
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monitoring the shape parameter of a weibull Renewal Process
IISE Transactions, 2017Co-Authors: Cai Wen Zhang, Min XieAbstract:This research arose from a challenge faced in real practice—monitoring changes to the Weibull shape parameter. From first-hand experience, we understand that a mechanism for such a purpose is very useful. This article is primarily focused on monitoring the shape parameter of a Weibull Renewal Process. We derive a novel statistic on the Weibull shape parameter making use of maximum likelihood theory, which is demonstrated to follow an approximately normal distribution. This desirable normality property makes the statistic well suited for use in monitoring the Weibull shape parameter. It also allows for a simple approach to constructing a Shewhart-type control chart, named the Beta chart. The parameter values required to design a Beta chart are provided. A self-starting procedure is also proposed for setting up the Phase I Beta chart. The Average Run Length (ARL) performance of the Beta chart is evaluated through Monte Carlo simulation. A comparison with a moving range exponentially weighted moving average (EWMA) chart from the literature shows that the Beta chart has much better ARL performance when properly designed. Application examples, using both simulated and real data, demonstrate that the Beta chart is effective and makes good sense in real practice.
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monitoring the shape parameter of a weibull Renewal Process
IISE Transactions, 2017Co-Authors: Cai Wen Zhang, Min XieAbstract:This research arose from a challenge faced in real practice—monitoring changes to the Weibull shape parameter. From first-hand experience, we understand that a mechanism for such a purpose is very ...
Wansheng Tang - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy random Renewal Process and Renewal reward Process
Fuzzy Optimization and Decision Making, 2007Co-Authors: Ruiqing Zhao, Wansheng Tang, Cheng WangAbstract:So far, there have been several concepts about fuzzy random variables and their expected values in literature. One of the concepts defined by Liu and Liu (2003a) is that the fuzzy random variable is a measurable function from a probability space to a collection of fuzzy variables and its expected value is described as a scalar number. Based on the concepts, this paper addresses two Processes--fuzzy random Renewal Process and fuzzy random Renewal reward Process. In the fuzzy random Renewal Process, the interarrival times are characterized as fuzzy random variables and a fuzzy random elementary Renewal theorem on the limit value of the expected Renewal rate of the Process is presented. In the fuzzy random Renewal reward Process, both the interarrival times and rewards are depicted as fuzzy random variables and a fuzzy random Renewal reward theorem on the limit value of the long-run expected reward per unit time is provided. The results obtained in this paper coincide with those in stochastic case or in fuzzy case when the fuzzy random variables degenerate to random variables or to fuzzy variables.
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random fuzzy Renewal Process
European Journal of Operational Research, 2006Co-Authors: Ruiqing Zhao, Wansheng Tang, Huaili YunAbstract:Abstract This paper attempts to discuss a random fuzzy Renewal Process based on random fuzzy theory. The interarrival times are characterized as nonnegative random fuzzy variables which is a more reasonable consideration in the real world. Under this setting, the rate of the random fuzzy Renewal Process is discussed and a random fuzzy elementary Renewal theorem is presented. Furthermore, the expected value of Renewals in an arbitrary interval is investigated and Blackwell’s theorem in random fuzzy sense is also established.
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fuzzy Renewal Process fuzzy Renewal reward Process and their applications
IEEE International Conference on Fuzzy Systems, 2004Co-Authors: Ruiqing Zhao, Wansheng Tang, Huaili YunAbstract:This work extends the work in Zhao and Liu on fuzzy Renewal Process and Renewal reward Process from continuous case to more general case. Fuzzy elementary Renewal theorem and fuzzy Renewal reward theorem are developed and shown how they can be applied to maintenance policies. Three kinds of maintenance policies- fuzzy age replacement policy, fuzzy block replacement policy and fuzzy inspection policy are discussed. The optimality functions studied are the long run expected costs per unit of time. Finally, a hybrid intelligent algorithm is employed to solve the models proposed in maintenance policies and to arrive at optimum policies. A numerical example is enumerated and the result indicates that the algorithm is effective.
