Yan Shi

Tokai University, Hiratuka, Kanagawa, Japan

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Publications (71)62.63 Total impact

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    ABSTRACT: In this paper, we develop the necessary conditions of optimality for a new class of mixed regular-singular control problem for nonlinear forward-backward stochastic systems with Poisson jump processes of McKean-Vlasov type. The coefficients of the system and the performance functional depend not only on the state process but also its marginal law of the state process through its expected value. The control variable has two components, the first being absolutely continuous and the second singular control. Our optimality conditions for these McKean-Vlasov’s systems are established by means of convex perturbation techniques for both continuous and singular parts. In our class of McKean-Vlasov control problem, there are two types of jumps for the state processes, the inaccessible ones which come from the Poission martingale part and the predictable ones which come from the singular control part.
    No preview · Article · May 2016 · Neurocomputing
  • Yingqi Zhang · Yan Shi · Peng Shi
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    ABSTRACT: This paper investigates the non-fragile and robust finite-time H∞ control problem for a class of uncertain Markovian jump nonlinear systems with bounded parametric uncertainties and norm-bounded disturbance. By employing stochastic analysis and linear matrix inequality techniques, sufficient criteria of stochastic finite-time boundedness and stochastic H∞ finite-time boundedness are first provided for the class of stochastic jump systems. Then, a controller is designed such that the class of stochastic nonlinear dynamics are stochastically finite-time bounded and have an H∞ attention performance level by utilizing matrix decomposition approach. Furthermore, the analysis and design of non-fragile and robust finite-time controller are provided to guarantee that the class of uncertain stochastic systems are stochastically finite-time boundeded with a prescribed attention index by using non-fragile control technique. In addition, we also deal with the analysis and design of stochastic finite-time stability and stochastic finite-time stabilization. All criterions can be characterized in terms of linear matrix inequalities. Finally, two examples are also given to illustrate the effectiveness of obtained results.
    No preview · Article · Apr 2016 · Applied Mathematics and Computation
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    ABSTRACT: This paper is concerned with the problems of finite-time filter analysis and design for discrete time-delay neural networks with Markovian jump parameters and sector-bounded activation functions represented by Takagi-Sugeno fuzzy model. Firstly, a sufficient admissibility criterion is presented to guarantee that the augmented fuzzy jump neural network without parameter uncertainties is stochastically finite-time bounded in a prescribed time interval. From the admissibility criterion obtained, a sufficient condition on stochastic finite-time boundedness is provided for the augmented fuzzy jump neural networks. Then, a sufficient criterion to design a finite-time fuzzy filter is presented with uncertain parameters and Markovian jumps for discrete time-delay fuzzy neural networks. Moreover, conditions on stochastic finite-time stability are also established for nominal and uncertain delayed fuzzy jump neural networks without the presence of external disturbance. All criteria obtained can be represented as the form of linear matrix inequalities. Finally, numerical examples are given to illustrate the effectiveness of the obtained results.
    No preview · Article · Jan 2016 · Neurocomputing
  • Haijiao Yang · Peng Shi · Xudong Zhao · Yan Shi
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    ABSTRACT: This paper focuses on the problem of adaptive neural output-feedback control for a class of nonstrict-feedback nonlinear systems where the system coefficient functions are unknown. First, the original system is transformed into a new defined system by a linear state transformation. Then, by using the dynamic surface control (DSC) technique, an improved input-driven filter is proposed. Based on this filter and the approximation property of radial basis function (RBF) neural networks, an adaptive neural output-feedback controller is designed via backstepping technique, which can guarantee that all the signals in the closed-loop system are ultimately bounded. The main contribution of this paper lies in that a simpler and more effective design procedure of adaptive neural output-feedback tracking controller is proposed for the underlying system which is more general than some existing ones in literature. Finally, simulation results are given to demonstrate the feasibility and effectiveness of the new design algorithm.
    No preview · Article · Dec 2015
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    Yanbing Yang · Junhu Ruan · Bin Liu · Yi Liu · Yan Shi
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    ABSTRACT: Evolutionary spatial game is a promising way to unravel the mystery of cooperation, and it has been well recognized that spatial structure could enable cooperation to persist. Schweitzer et al’s lattice model provides an innovative method to solve the problem. In this paper, we conduct simulations using the same von Neumann neighborhood with [25], and observe the effect of initial population and lattice size on the evolution of cooperation. Then, we extend the model with a more complicated Moore neighborhood and self-playing rule for each central player. Simulation results not only provide new evidence for the persistence of cooperation in the evolution with spatial structures, but also investigate critical conditions for the spatial coexistence or the invasion of cooperators and defectors with the more complicated neighborhood.
    Full-text · Article · Jan 2015 · Discrete Dynamics in Nature and Society

  • No preview · Article · Jan 2015 · IEEE Transactions on Fuzzy Systems
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    Junhu Ruan · Xuping Wang · Yan Shi
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    ABSTRACT: We present a two-stage approach for the “helicopters and vehicles” intermodal transportation of medical supplies in large-scale disaster responses. In the first stage, a fuzzy-based method and its heuristic algorithm are developed to select the locations of temporary distribution centers (TDCs) and assign medial aid points (MAPs) to each TDC. In the second stage, an integer-programming model is developed to determine the delivery routes. Numerical experiments verified the effectiveness of the approach, and observed several findings: (i) More TDCs often increase the efficiency and utility of medical supplies; (ii) It is not definitely true that vehicles should load more and more medical supplies in emergency responses; (iii) The more contrasting the traveling speeds of helicopters and vehicles are, the more advantageous the intermodal transportation is.
    Full-text · Article · Nov 2014 · International Journal of Environmental Research and Public Health
  • Chenxia Jin · Meng Yang · Yan Shi · Fachao Li
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    ABSTRACT: Fuzzy programming approach has wide application in many fields such as project management, multi-attribute decision making, and comprehensive evaluation. Its solving methods have attracted many attentions. In this paper we present a new approach, based on the genetic algorithm, for dealing with a programming problem with fuzzy-valued objective function and constraints. Firstly, we propose the concept of generalized equilibrium value of fuzzy number, and analyze the properties, further give the operation rules; secondly, we establish a generalized equilibrium value-based fuzzy programming method combined with genetic algorithm; finally, we analyze the characteristic of the above mentioned method through a nonlinear fuzzy programming problems.
    No preview · Article · Sep 2014 · IEEE International Conference on Fuzzy Systems
  • Junhu Ruan · Yan Shi
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    ABSTRACT: Prompt medical service and supplies are very important to reduce the life loss in response to disasters. In this work, we focus on how to allocate the limited medical supplies to affected areas in different situations with fuzzy triangular values. Using the a-cut method and Giove's acceptability index, we first propose a method of comparing fuzzy triangular numbers. Then, based on our previous work, we develop a situation-based approach for allocating medical supplies with fuzzy triangular values. A simple example shows the effectiveness of the developed approach.
    No preview · Conference Paper · Jul 2014
  • Li Zou · Xin Wen · Hamid Reza Karimi · Yan Shi
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    ABSTRACT: The necessary and sufficient condition of convex function is significant in nonlinear convex programming. This paper presents the identification of convex function on Riemannian manifold by use of Penot generalized directional derivative and the Clarke generalized gradient. This paper also presents a method for judging whether a point is the global minimum point in the inequality constraints. Our objective here is to extend the content and proof the necessary and sufficient condition of convex function to Riemannian manifolds.
    No preview · Article · Jan 2014 · Mathematical Problems in Engineering
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    Junhu Ruan · Xuping Wang · Yan Shi
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    ABSTRACT: With the widespread application of computer and communication technologies, more and more real-time systems are implemented whose large amounts of time-stamped data consequently require more efficient processing approaches. For large-scale time series, precise values are often hard or even impossible to predict in limited time at limited costs. Meanwhile, precision is not absolutely necessary for human to think and reason, so credible changing ranges of time series are satisfactory for some decision-making problems. This study aims to develop fast interval predictors for large-scale, nonlinear time series with noisy data using fuzzy granular support vector machines (FGSVMs). Six information granulation methods are proposed which can granulate large-scale time series into subseries. FGSVM predictors are developed to forecast credible changing ranges of large-scale time series. Five performance indicators are presented to measure the quality and efficiency of FGSVMs. Four time series are used to examine the effectiveness and efficiency of the proposed granulation methods and the developed FGSVMs, whose results show the effectiveness and advantages of FGSVMs for large-scale, nonlinear time series with noisy data.
    Full-text · Article · Sep 2013 · Applied Soft Computing
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    Junhu Ruan · Xuping Wang · Yan Shi
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    ABSTRACT: The transportation networks often become uncertain due to the occurrence and development of disasters. In order to select proper paths under uncertain infor- mation, we propose a novel scenario-based approach for emergency path selection. The scenario factors are �rstly analyzed and combined to describe the uncertainty of each path section between two adjacent intersections in emergency transportation networks. Then, according to the fuzzy properties of path sections, the membership transformation algorithm M(1,2,3) is applied in fuzzy evaluation on the scenarios of path sections, which can determine the satisfaction degrees of each path section. Combining the highest sat- isfaction of each section under various scenarios, an optimal multi-attribute vector is constructed to build the scenario-based optimization model for emergency path selection. Finally, a numerical example is shown to illustrate the solution of this approach, whose results show that this approach can produce the paths with maximized overall satisfaction degree in a given con�dence and that the satisfaction degree will increase as the given con�dence decreases.
    Full-text · Article · Aug 2013 · International journal of innovative computing, information & control: IJICIC
  • Junhu Ruan · Xuping Wang · Yan Shi
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    ABSTRACT: The allocation of relief supplies should be based on the situations of affected areas. Taking relief medical supplies as the research objects, we develop a scenario-based relief supplies allocating approach for large-scale disasters. After constructing decisionmaking scenarios of relief medical supplies allocation from eight factors, three relative similarity measurement methods are developed to assess the scenarios of affected areas, and then a scenario-based optimization model is built which aims at minimizing the total response time of relief medical supplies on the condition that all the supplies are allocated to affected areas in accordance with their scenarios. Lastly, an example is illustrated to show the feasibility and effectiveness of the developed approach.
    No preview · Article · Jul 2013 · ICIC Express Letters
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    ABSTRACT: In this work, input-to-state stability of Lur’e hyperbolic distributed complex-valued parameter control systems has been addressed. Using comparison principle, delay-dependent sufficient conditions for the input-to-state stability in complex Hilbert spaces are established in terms of linear operator inequalities. Finally, numerical computation illustrates our result.
    Preview · Article · Feb 2013 · Mathematical Problems in Engineering
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    ABSTRACT: Numerous items, small order, and frequent delivery are the characteristics of many distribution centers. Such characteristics generally increase the operating costs of the distribution center. To remedy this problem, this study employs the Entry-Item-Quantity (EIQ) method to identify the characteristic of the cigarette distribution center and further analyzes the importance degree of customers and the frequently ordered products by means of EQ/EN/IQ-B/IK statistic charts. Based on these analyses as well as the total replenishment cost optimization model, multipicking strategies and combined multitype picking equipment allocation is then formulated accordingly. With such design scheme, the cigarette picking costs of the distribution center are expected to reduce. Finally, the specific number of equipment is figured out in order to meet the capability demand of the case cigarette distribution center.
    Preview · Article · Nov 2012 · Mathematical Problems in Engineering
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    ABSTRACT: Because clean energy and traditional energy have different advantages and disadvantages, it is of great significance to evaluate comprehensive benefits for hybrid power systems. Based on thorough analysis of important characters on hybrid power systems, an index system including security, economic benefit, environmental benefit, and social benefit is established in this paper. Due to advantages of processing abundant uncertain and fuzzy information, vague set is used to determine the decision matrix. Convert vague decision matrix to real one by vague combination ruleand determine uncertain degrees of different indexes by grey incidence analysis, then the mass functions of different comment set in different indexes are obtained. Information can be fused in accordance with Dempster-Shafer (D-S) combination rule and the evaluation result is got by vague set and D-S evidence theory. A simulation of hybrid power system including thermal power, wind power, and photovoltaic power in China is provided to demonstrate the effectiveness and potential of the proposed design scheme. It can be clearly seen that the uncertainties in decision making can be dramatically decreased compared with existing methods in the literature. The actual implementation results illustrate that the proposed index system and evaluation model based on vague set and D-S evidence theory are effective and practical to evaluate comprehensive benefit of hybrid power system.
    No preview · Article · Nov 2012 · Mathematical Problems in Engineering
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    Xuping Wang · Junhu Ruan · Yan Shi
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    ABSTRACT: The existence of uncertainties may result in various unexpected disruption events in logistics delivery, which often makes actual delivery operations deviate from intended plans. The purpose of the paper is to develop a combinational disruption recovery model for vehicle routing problem with time windows (VRPTW), trying to handle a variety and a combination of delivery disruption events. Firstly, a novel approach to measure new-adding customer disruption, which considers the real-world participators (mainly including customers, drivers and logistics providers) in VRPTW, is developed. Then the paper proposes methods of transforming various delivery disruptions into the new-adding customer disruption, and determines the optimal starting times of delivery vehicles from the depot to provide a new rescue strategy (called starting later policy) for disrupted VRPTW. Based on the above, a combinational disruption recovery model for VRPTW is constructed and nested partition method (NPM) is designed to solve the proposed model. Finally, computational results are reported and compared with those of previous works, which verifies the effectiveness of the proposed solution and draws some interesting conclusions.
    Full-text · Article · Nov 2012 · International Journal of Production Economics
  • Chenxia Jin · Fachao Li · Yan Shi · Lei Zhou
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    ABSTRACT: Stochastic programming is a well-known optimization problem in resource allocation, optimization decision, etc. In this paper, we first analyze the essential features of stochastic programming and the deficiencies of the existing methods. To systematically process the objective function and constraints, we give the principles we should obey in seeking for the optimal decision, and further we give an axiomatic system for synthesis effect function. Based on synthesis effect function, we establish a general solution model (simply denoted as BSE-SGM) for stochastic programming problem, discuss the concavity of BSE-SGM, and analyze the effectiveness of BSE-SGM by an example. The results indicate that our method includes the existing stochastic programming methods, which can integrate the decision consciousness into the solution process effectively.
    No preview · Article · Oct 2012 · International journal of innovative computing, information & control: IJICIC
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    Xiaoli Luan · Yan Shi · Fei Liu
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    ABSTRACT: A stochastic unscented Kalman filter is designed in an attempt to solve the state estimation problem of the greenhouse climate control systems with missing measure-ments. The missing measurements are described by a binary switching sequence satisfying a conditional probability distribution. In order to accommodate the effects of randomly varying arrival of measurement data, the stochastic unscented transformation coupled with certain parts of the classic Kalman filter is applied to estimate the greenhouse states and filter out the noises, where some or all measurements are lost in a random fash-ion. The simulation results demonstrate the performance degradation of state estimation caused by random measurement data loss.
    Preview · Article · Mar 2012 · International journal of innovative computing, information & control: IJICIC
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    Fachao Li · Li Wang · Yan Shi
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    ABSTRACT: As a kind of particular programming, transportation problem draws much attention in many fields such as energy development, materials management, etc. In this paper, by analyzing the essence of stochastic programming and the deficiencies of existing methods, we propose a comparison method based on synthesizing effect for the standard to judge an objective value is good or not, and give the axiom system of stochastic synthe-sizing effect function, further, we introduce a quasi-linear pattern based on expectation and variance for the satisfaction of random constraints. Moreover, using synthesizing effect and quasi-linear pattern, we establish a stochastic programming pattern (general-ized expected value model, and denoted by GEM for short) with good operability, and for the stochastic transportation problem, we also establish its corresponding generalized expected value model. Finally, we analyze the performance of GEM by combining with a transportation case under random environment. All these indicate that GEM includes the existing methods, and it can effectively solve the stochastic transportation problem un-der complex environment or with incomplete information, in addition, GEM can merge decision consciousness into solution through quantitative way.
    Preview · Article · Jun 2011 · International journal of innovative computing, information & control: IJICIC