Stochastic Simulation Method for Reasoning of Dynamic Uncertain Causality Graph (DUCG)

2021 ◽  
Author(s):  
Hao Nie ◽  
Qin Zhang
Keyword(s):  
Stochastic Simulation ◽  
Simulation Method ◽  
Dynamic Uncertain Causality Graph

Stochastic simulation for determining the design flood of cascade reservoir systems

2012 ◽  
Vol 43 (1-2) ◽  
pp. 54-63 ◽  
Author(s):  
Baohong Lu ◽  
Huanghe Gu ◽  
Ziyin Xie ◽  
Jiufu Liu ◽  
Lejun Ma ◽  
...  
Keyword(s):  
Simulation Model ◽  
Stochastic Simulation ◽  
Southern China ◽  
Flow Simulation ◽  
Simulation Method ◽  
Simulation Approach ◽  
Design Flood ◽  
Design Values ◽  
Stochastic Simulation Model ◽  
The Impact

Stochastic simulation is widely applied for estimating the design flood of various hydrosystems. The design flood at a reservoir site should consider the impact of upstream reservoirs, along with any development of hydropower. This paper investigates and applies a stochastic simulation approach for determining the design flood of a complex cascade of reservoirs in the Longtan watershed, southern China. The magnitude of the design flood when the impact of the upstream reservoirs is considered is less than that without considering them. In particular, the stochastic simulation model takes into account both systematic and historical flood records. As the reliability of the frequency analysis increases with more representative samples, it is desirable to incorporate historical flood records, if available, into the stochastic simulation model. This study shows that the design values from the stochastic simulation method with historical flood records are higher than those without historical flood records. The paper demonstrates the advantages of adopting a stochastic flow simulation approach to address design-flood-related issues for a complex cascade reservoir system.

scholarly journals Numerical studies of higher order tau-leaping methods

2021 ◽  
Author(s):  
Anuj Dhoj Thapa
Keyword(s):  
Stochastic Simulation ◽  
Computational Cost ◽  
Practical Interest ◽  
Stochastic Simulation Algorithm ◽  
Simulation Method ◽  
Equation Model ◽  
Fast Reactions ◽  
Biochemical Systems ◽  
Computationally Intensive ◽  
Reacting Systems

Gillespie's algorithm, also known as the Stochastic Simulation Algorithm (SSA), is an exact simulation method for the Chemical Master Equation model of well-stirred biochemical systems. However, this method is computationally intensive when some fast reactions are present in the system. The tau-leap scheme developed by Gillespie can speed up the stochastic simulation of these biochemically reacting systems with negligible loss in accuracy. A number of tau-leaping methods were proposed, including the explicit tau-leaping and the implicit tau-leaping strategies. Nonetheless, these schemes have low order of accuracy. In this thesis, we investigate tau-leap strategies which achieve high accuracy at reduced computational cost. These strategies are tested on several biochemical systems of practical interest.

Estimating Weights of Evaluation Factors on Basis of Monte Carlo Simulation

2012 ◽  
Vol 268-270 ◽  
pp. 1735-1740
Author(s):  
Yan Fei Tian ◽  
Li Wen Huang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Random Process ◽  
Stochastic Simulation ◽  
Research Work ◽  
Simulation Method ◽  
Distribution Functions ◽  
Probability Process ◽  
Evaluation Work

Although the value of factor weight in an evaluation work is deterministic, the solving process is random, so connection between weight solution with digital characteristics or distribution functions of specific random variables or random process could be build. Using stochastic simulation method to get a lot of random solutions to the problem, expectation of the random solutions can be used as a estimation solution. On basis of idea of Monte Carlo simulation, this paper analyzed the probability process of calculating factor weight, and provided the procedures of estimating factor weight by means of Monte Carlo simulation. Through discussion and example in this paper, feasibility and validity of this method were proved, which may make foreshadowing for follow-up research work.

scholarly journals Tau Leaping Stochastic Simulation Method in P Systems

2006 ◽  
pp. 298-313 ◽  
Author(s):  
Paolo Cazzaniga ◽  
Dario Pescini ◽  
Daniela Besozzi ◽  
Giancarlo Mauri
Keyword(s):  
Stochastic Simulation ◽  
Simulation Method ◽  
P Systems

Nonstationary stochastic simulation method for the risk assessment of water allocation

2021 ◽  
Vol 7 (1) ◽  
pp. 212-221
Author(s):  
Shu Chen ◽  
Jijun Xu ◽  
Qingqing Li ◽  
Yongqiang Wang ◽  
Zhe Yuan ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Stochastic Simulation ◽  
Water Allocation ◽  
Simulation Method ◽  
First Time

It is the first time to consider the hydrological nonstationary in water allocation risk assessment.

Stochastic Simulation of Bus Traveling Time

2011 ◽  
Vol 186 ◽  
pp. 556-559
Author(s):  
Lian Xue ◽  
Dan Jie Zhao ◽  
Gui Mei Liu
Keyword(s):  
Travel Time ◽  
Stochastic Simulation ◽  
Public Transportation ◽  
Simulation Method ◽  
Service Level ◽  
Transportation Systems ◽  
Travel Time Reliability ◽  
Public Transport System ◽  
Public Transportation Systems ◽  
Bus Travel Time

The development of the city's public transport system has an indispensable role to alleviate the pressure of urban roads. Bus travel time reliability is an important evaluation index of the bus operation service level. The simulation of bus travel time helps us understand the reliability of bus running time. In this paper, we use Monte Carlo stochastic simulation method to calculate the reliability of bus travel time. On this basis, we establish a model of the reliability of public transportation systems to research the reliability of bus travel time.

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