• Bulletin of the Korean Mathematical Society
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• v.37 no.2
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• pp.401-409
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• 2000

In this paper, we determine the structure of ${\kappa}-potent$ elements and regular elements of the semigroup ${\Omega}_n$of doubly stochastic matrices of order n. In connection with this, we find the structure of the matrices X satisfying the equation AXA = A. From these, we determine a condition of a doubly stochastic matrix A whose Moore-Penrose generalized is also a doubly stochastic matrix.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1305-1314
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• 2010

In this paper, we deal with a class of one-dimensional reflected backward stochastic differential equations driven by a Brownian motion and the martingales of Teugels associated with an independent L$\acute{e}$vy process having a stochastic Lipschitz coefficient. We derive the existence and uniqueness of solutions for these equations via Snell envelope and the fixed point theorem.

• Journal of the Chungcheong Mathematical Society
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• v.33 no.1
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• pp.103-112
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• 2020

This paper investigates the portfolio selection problem with flexible labor choice and stochastic income flow where the unit wage flow is governed by a stochastic process. The agent optimally chooses consumption, investment, and labor supply. We derive the closed-form solution by applying a martingale method even with the stochastic income flow.

• Journal of the Korean Mathematical Society
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• v.35 no.2
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• pp.259-268
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• 1998

In this paper the stochastic multiple objective programming problems where the right-hand-side of the constraints is stochastic are considered. We define the equivalent scalar-valued problem and study the stability of the equivalent scalar-valued problem with respect to the weight parameters and probability mesures under reasonable assumptions.

• Computers and Concrete
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• v.30 no.4
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• pp.237-242
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• 2022

This paper is concerned with exponential stability in mean square for stochastic static neutral neural networks with varying delays. By using Lyapunov functional method and with the help of stochastic analysis technique, the sufficient conditions to guarantee the exponential stability in mean square for the neural networks are obtained and some results of related literature are extended.

• East Asian mathematical journal
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• v.39 no.3
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• pp.319-329
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• 2023

In this paper, we consider a stochastic higher-order Kirchhoff-type equation with nonlinear damping and source terms. We prove the blow-up of solution for a stochastic higher-order Kirchhoff-type equation with positive probability or explosive in energy sense.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.61-73
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• 2006

This paper deals with traveling salesman problem(TSP) with the stochastic travel time. Practically, the travel time between demand points changes according to day and time zone because of traffic interference and jam. Since the almost pervious studies focus on TSP with the deterministic travel time, it is difficult to apply those results to logistics problem directly. But many logistics problems are strongly related with stochastic situation such as stochastic travel time. We need to develop the efficient solution method for the TSP with stochastic travel time. From the previous researches, we know that Q-learning technique gives us to deal with stochastic environment and neural network also enables us to calculate the Q-value of Q-learning algorithm. In this paper, we suggest an algorithm for TSP with the stochastic travel time integrating Q-learning and neural network. And we evaluate the validity of the algorithm through computational experiments. From the simulation results, we conclude that a new route obtained from the suggested algorithm gives relatively more reliable travel time in the logistics situation with stochastic travel time.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.2007-2013
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• 1999

A Newly proposed control methodology applied to the aeroelastic system experiencing flutter is investigated and its performance is verified experimentally. The flexible cantilever beam slicked with piezofilm sensor and piezoceramic actuator is modelled in physical domain. Dynamic moment equation for the system is derived via Ito's stochastic differential equation and F-P-K equation. Also system's characteristics in stochastic domain is analyzed simultaneously. LQG controller is designed and used in physical and stochastic domain. It is shown experimentally that the vibration of beam is controlled effectively by designed LQG controller in physical domain. By comparing the result with that of LQG controller designed in stochastic domain, it is shown that the new control method, called Heo-stochastic control technique, has better performance as a controller.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.411-419
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• 2016

This article investigates the problem of distributed channel selection in opportunistic spectrum access networks from a perspective of interference minimization. The traditional physical (PHY)-layer interference model is for information theoretic analysis. When practical multiple access mechanisms are considered, the recently developed binary medium access control (MAC)-layer interference model in the previous work is more useful, in which the experienced interference of a user is defined as the number of competing users. However, the binary model is not accurate in mathematics analysis with poor achievable performance. Therefore, we propose a real-valued one called stochastic MAC-layer interference model, where the utility of a player is defined as a function of the aggregate weight of the stochastic interference of competing neighbors. Then, the distributed channel selection problem in the stochastic MAC-layer interference model is formulated as a weighted stochastic MAC-layer interference minimization game and we proved that the game is an exact potential game which exists one pure strategy Nash equilibrium point at least. By using the proposed stochastic learning-automata based uncoupled algorithm with heterogeneous learning parameter (SLA-H), we can achieve suboptimal convergence averagely and this result can be verified in the simulation. Moreover, the simulated results also prove that the proposed stochastic model can achieve higher throughput performance and faster convergence behavior than the binary one.

• Coupled systems mechanics
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• v.7 no.6
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• pp.707-729
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• 2018

The semi-active optimal vibration control of nonlinear torsion-bar suspension vehicle systems under random road excitations is an important research subject, and the boundedness of MR dampers and the uncertainty of vehicle systems are necessary to consider. In this paper, the differential equations of motion of the coupling torsion-bar suspension vehicle system with MR damper under random road excitation are derived and then transformed into strongly nonlinear stochastic coupling vibration equations. The dynamical programming equation is derived based on the stochastic dynamical programming principle firstly for the nonlinear stochastic system. The semi-active bounded parametric optimal control law is determined by the programming equation and MR damper dynamics. Then for the uncertain nonlinear stochastic system, the minimax dynamical programming equation is derived based on the minimax stochastic dynamical programming principle. The worst-case disturbances and corresponding semi-active bounded parametric optimal control are obtained from the programming equation under the bounded disturbance constraints and MR damper dynamics. The control strategy for the nonlinear stochastic vibration of the uncertain torsion-bar suspension vehicle system is developed. The good effectiveness of the proposed control is illustrated with numerical results. The control performances for the vehicle system with different bounds of MR damper under different vehicle speeds and random road excitations are discussed.