Research on the Non-Probabilistic Reliability Based on Interval Model

2012 ◽  
Vol 166-169 ◽  
pp. 1908-1912 ◽  
Author(s):  
Ai Rong Zhang ◽  
Xiao Liu
Keyword(s):  
Minimum Distance ◽  
Fuzzy Model ◽  
Uncertain Parameters ◽  
Reliability Model ◽  
Probabilistic Theory ◽  
Interval Model ◽  
Uncertain Variables ◽  
Sample Data ◽  
Failure Region ◽  
Robust Reliability

Due to the dependence of the sample data for a probabilistic reliability model and the fuzzy model, the interval model was used to describe the uncertain parameters through which a new measure of non-probabilistic reliability was established. Studying the model with the non-probabilistic theory, a new measure of non-probabilistic reliability was established which was the minimum distance between the failure region and the total region constructed by all uncertain variables. This kind of measure not only is consistent with the criterion of the non-probabilistic robust reliability, but also has a clearer meaning. The validity and the feasibility were proved through a computational example.

scholarly journals Task Assignment Algorithm Based on Trust in Volunteer Computing Platforms

Information ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 244 ◽  
Author(s):  
Ling Xu ◽  
Jianzhong Qiao ◽  
Shukuan Lin ◽  
Ruihua Qi
Keyword(s):  
Completion Time ◽  
Fuzzy Model ◽  
Task Assignment ◽  
Experimental Results ◽  
Volunteer Computing ◽  
Time Interval ◽  
Reliability Model ◽  
Assignment Algorithm ◽  
Computing Platforms ◽  
Task Segmentation

In volunteer computing (VC), the expected availability time and the actual availability time provided by volunteer nodes (VNs) are usually inconsistent. Scheduling tasks with precedence constraints in VC under this situation is a new challenge. In this paper, we propose two novel task assignment algorithms to minimize completion time (makespan) by a flexible task assignment. Firstly, this paper proposes a reliability model, which uses a simple fuzzy model to predict the time interval provided by a VN. This reliability model can reduce inconsistencies between the expected availability time and actual availability time. Secondly, based on the reliability model, this paper proposes an algorithm called EFTT (Earliest Finish Task based on Trust, EFTT), which can minimize makespan. However, EFTT may induce resource waste in task assignment. To make full use of computing resources and reduce task segmentation rate, an algorithm IEFTT (improved earliest finish task based on trust, IEFTT) is further proposed. Finally, experimental results verify the efficiency of the proposed algorithms.

T–S FUZZY ADAPTIVE DELAYED FEEDBACK SYNCHRONIZATION FOR TIME-DELAYED CHAOTIC SYSTEMS WITH UNCERTAIN PARAMETERS

2011 ◽  
Vol 25 (23n24) ◽  
pp. 3253-3267 ◽  
Author(s):  
CHOON KI AHN ◽  
PYUNG SOO KIM
Keyword(s):  
Chaotic Systems ◽  
Lorenz System ◽  
Fuzzy Model ◽  
Delayed Feedback ◽  
Delayed Feedback Control ◽  
Adaptive Synchronization ◽  
Linear Matrix ◽  
Uncertain Parameters ◽  
Takagi Sugeno ◽  
Fuzzy Adaptive

In this paper, we propose a new adaptive synchronization method, called a fuzzy adaptive delayed feedback synchronization (FADFS) method, for time-delayed chaotic systems with uncertain parameters. An FADFS controller that is based on the Lyapunov–Krasovskii theory, Takagi–Sugeno (T–S) fuzzy model, and delayed feedback control is developed to guarantee adaptive synchronization. The proposed controller can be obtained by solving the linear matrix inequality (LMI) problem. A numerical example using a time-delayed Lorenz system is discussed to assess the validity of the proposed FADFS method.

Non-Probabilistic Reliability Analysis Based on Interval Interference & Disjoint Model

2011 ◽  
Vol 338 ◽  
pp. 166-170 ◽  
Author(s):  
Xiao Liu ◽  
Ge Ning Xu ◽  
Ping Yang
Keyword(s):  
Design Parameter ◽  
Reliability Index ◽  
Uncertain Parameters ◽  
Propeller Shaft ◽  
Calculation Methods ◽  
Mechanical Device ◽  
Interval Model ◽  
Transmission Shaft ◽  
Parameters Analysis ◽  
Distribution Type

According to the distribution type of the uncertain parameters not acquired accurately in the probabilistic reliability, the interval model was used to describe the uncertain parameters. Various calculation methods were used to research the non-probabilistic reliability responding to different condition between the stress interval and the resistance interval. The reliability index of the transmission shaft of a mechanical device was compared between probabilistic reliability and non-probabilistic reliability. And the corresponding changes of the non-probabilistic reliability index were observed with different deviation of the uncertain parameters, analysis of non-probabilistic index has shown that with the increasing uncertain level of the parameter, the non-probabilistic reliability of propeller shaft was gradually reducing. And uncertain level of the different design parameter had a distinct influence on reliability index.

scholarly journals Direct Estimation of Inhomogeneous Markov Interval Models of Spike Trains

2009 ◽  
Vol 21 (8) ◽  
pp. 2105-2113 ◽  
Author(s):  
Daniel K. Wójcik ◽  
Gabriela Mochol ◽  
Wit Jakuczun ◽  
Marek Wypych ◽  
Wioletta J. Waleszczyk
Keyword(s):  
Probabilistic Model ◽  
General Model ◽  
Neural Coding ◽  
Direct Method ◽  
Spike Trains ◽  
Spike Time ◽  
Precise Description ◽  
Interval Model ◽  
Sample Data ◽  
A Direct Method

A necessary ingredient for a quantitative theory of neural coding is appropriate “spike kinematics”: a precise description of spike trains. While summarizing experiments by complete spike time collections is clearly inefficient and probably unnecessary, the most common probabilistic model used in neurophysiology, the inhomogeneous Poisson process, often seems too crude. Recently a more general model, the inhomogeneous Markov interval model (Berry & Meister, 1998 ; Kass & Ventura, 2001 ), was considered, which takes into account both the current experimental time and the time from the last spike. Several techniques were proposed to estimate the parameters of these models from data. Here we propose a direct method of estimation that is easy to implement, fast, and conceptually simple. The method is illustrated with an analysis of sample data from the cat's superior colliculus.

A Non-Probabilistic Model for Structural Reliability Analysis

2014 ◽  
Vol 496-500 ◽  
pp. 2737-2741
Author(s):  
Xin Zhou Qiao ◽  
Yuan Ying Qiu
Keyword(s):  
Reliability Analysis ◽  
Probabilistic Model ◽  
Structural Reliability ◽  
Uncertain Parameters ◽  
Reliability Model ◽  
Numerical Examples ◽  
Structural Reliability Analysis ◽  
Basic Interval ◽  
Interval Variables

By representing uncertain parameters as interval variables, a novel structural non-probabilistic reliability model is proposed, which can deal with the case that the domain constructed by the basic interval variables locates in the safe domain. Two numerical examples are conducted to illustrate the validity and feasibility of the proposed non-probabilistic model.

scholarly journals Hydraulic performance analysis of sewer systems with uncertain parameters

2011 ◽  
Vol 14 (3) ◽  
pp. 682-696 ◽  
Author(s):  
Seyed Mahmood Hosseini ◽  
Ali Ghasemi
Keyword(s):  
Performance Analysis ◽  
Expert Knowledge ◽  
Fuzzy Model ◽  
Hydraulic Performance ◽  
Uncertain Parameters ◽  
Design Quality ◽  
Design Engineers ◽  
Sewer Systems ◽  
Discharge Velocity ◽  
Proposed Model

In this paper, a flexible fuzzy model is proposed for the hydraulic performance analysis of separate domestic sewer systems. In the proposed model, all modeling outputs such as discharge, velocity and depth are developed as fuzzy numbers by taking into account all the available information and expert knowledge about the basic design/analysis parameters. The fuzzy outputs are then combined with performance assessment curves to calculate the hydraulic performance values. The proposed model was applied to a part of the sewer system of a city in Iran, and performance graphs were plotted. Such graphs can be used by design engineers and operation managers to improve the design quality, reliability and the performance of a system with uncertain parameters. The analysis results can also be used in decision-making and identifying priorities to develop rehabilitation strategies.

Non-Probabilistic Failure Assessment Methodology About Titanium Pipes With Cracks

2011 ◽  
Author(s):  
Qiao Dai ◽  
Changyu Zhou ◽  
Jian Peng
Keyword(s):  
Probabilistic Method ◽  
Assessment Method ◽  
Interval Model ◽  
Interval Parameters ◽  
Failure Assessment ◽  
Failure Region ◽  
Practical Engineering ◽  
Partial Safety Factors ◽  
Titanium Pipe ◽  
Level 2

In this paper, the non-probabilistic failure assessment method for a pipe with crack was proposed, and interval model was applied in this assessment method. Compared with the deterministic approach, the assessment parameters were regarded as interval parameters in the non-probabilistic method, which could reflect the uncertainty of data and avoid the unsafety of results caused by the scatter of these parameters. On the other hand, compared with traditional probabilistic method, the non-probabilistic method only needs the range or bound of the parameters rather than detailed statistics information of the parameters which may be uneasy to be obtained from practical engineering. So the new assessment method reduces the request for detailed statistics properties of parameters. In this paper, load, material mechanical properties and the size of crack were treated as interval parameters, and the non-probabilistic failure assessment method was established based on the level 2 normal assessment of the BS 7910:2005. In this case, the assessment point (Lr, Kr) is not a deterministic value, Lr and Kr would vary in a certain interval. As a consequence, the assessment point was changed into a rectangle zone, and the non-probabilistic failure measure for pipe with crack could be obtained by the variation of the rectangle. The non-probabilistic failure measure can be defined as the ratio of the area of failure region to the total area of the rectangle. At last, the non-probabilistic failure assessment method was used to evaluate a titanium pipe, and the analysis results were compared with the results of deterministic method, probabilistic method according to Monte-Carlo and partial safety factors method, respectively. The analysis results sufficiently demonstrated that the new non-probabilistic failure assessment method proposed in this paper was feasible and available.

The Robust Reliability Optimization of Steering Mechanism for Trucks Based on Non-Probabilistic Interval Model

2011 ◽  
Vol 467-469 ◽  
pp. 296-299 ◽  
Author(s):  
Xian Fu Cheng ◽  
Xin Zhang
Keyword(s):  
Optimization Design ◽  
Optimization Theory ◽  
Optimization Approach ◽  
Reliability Optimization ◽  
Interval Model ◽  
Controllable Factors ◽  
Steering Mechanism ◽  
Noise Factors ◽  
The Impact ◽  
Robust Reliability

In the optimization design for steering mechanism of trucks, considering the impact of controllable factors and noise factors, based on the reliability optimization theory, the stable reliability sensitivity method and the robust design method, the robust reliability design for steering mechanism of trucks is extensively discussed. Compared with the conventional probabilistic reliability optimization approach, the proposed method does not require a presumed probability distribution of the uncertain parameters and only the bounds or ranges of their variations are required. The movement precision is chosen as objective function and kingpins distance, axle base, the bottom angle of trapezoid and the arm length are chosen as design variables.

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