Applying Fuzzy Differential Equations to the Performance Analysis of Service Composition

2010 ◽  
pp. 118-125 ◽  
Author(s):  
Zuohua Ding ◽  
Hui Shen
Keyword(s):  
Performance Analysis ◽  
Differential Equations ◽  
Service Composition

scholarly journals Covid-19 Prediction in USA using modified SIR derived model

2020 ◽  
Author(s):  
Jathin desan
Keyword(s):  
Markov Chain ◽  
Performance Analysis ◽  
Differential Equations ◽  
Sir Model ◽  
Disease Dynamics ◽  
Analytical Results ◽  
Proposed Model ◽  
The Usa ◽  
Death Cases ◽  
Discrete Markov Chain

AbstractThe Covid-19 pandemic is rapidly extended into the extraordinary crisis. Based on the SIR model and published datasets the Covid-19 spread is assessed and predicted in USA in terms of susceptible, recovered and infected in the communities is focused on this study. For modelling the USA pandemic prediction several variants have been utilized. The SIR model splits the whole population into three components such as Susceptible (S), Infected (I) and Recovered or Removed (R). A collection of differential equations have been utilized to propagate the model and resolve the disease dynamics. In the proposed study, the prediction of covid-19 based on time is performed using the modified SIR derived model SIR-D with discrete markov chain. This proposed technique analyse and forecasting the covid-19 spread in 19 states of USA. The performance analysis of the proposed Analytical results revealed that though the probable uncertainty of the proposed model provides prediction, it becomes difficult to determine the death cases in future.

scholarly journals Performance Analysis of Biscuit Manufacturing Plant in Steady State Using Fuzzy Availability

2013 ◽  
Vol 11 (4) ◽  
pp. 2422-2439
Author(s):  
Pawan Kumar
Keyword(s):  
Steady State ◽  
Performance Analysis ◽  
Markov Process ◽  
Differential Equations ◽  
Mathematical Formulation ◽  
Manufacturing Plant ◽  
Coverage Factor ◽  
In Series ◽  
Fuzzy Availability

This paper deals with the performance analysis of biscuit manufacturing plant consisting of six sub-systems using fuzzy availability in the steady state. These six sub-systems are arranged in series and parallel configurations. Mathematical formulation of the problem is carried out using Markov process and the governing differential equations are solved in steady state using normalizing condition. The effect of variations of fuzzy availability for different failure, repair rates and system coverage factor for each sub-system in steady state is also studied.

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