Depicting the Distribution of Two Discrete Variables

2018 ◽  
pp. 275-316
Author(s):  
Kevin J. Keen
Keyword(s):  
2020 ◽  
Author(s):  
Tamás Tóth ◽  
István Majzik

AbstractAlgorithms and protocols with time dependent behavior are often specified formally using timed automata. For practical real-time systems, besides real-valued clock variables, these specifications typically contain discrete data variables with nontrivial data flow. In this paper, we propose a configurable lazy abstraction framework for the location reachability problem of timed automata that potentially contain discrete variables. Moreover, based on our previous work, we uniformly formalize in our framework several abstraction refinement strategies for both clock and discrete variables that can be freely combined, resulting in many distinct algorithm configurations. Besides the proposed refinement strategies, the configurability of the framework allows the integration of existing efficient lazy abstraction algorithms for clock variables based on $${\textit{LU}}$$ LU -bounds. We demonstrate the applicability of the framework and the proposed refinement strategies by an empirical evaluation on a wide range of timed automata models, including ones that contain discrete variables or diagonal constraints.


2014 ◽  
Vol 599-601 ◽  
pp. 1350-1356
Author(s):  
Ming Ming Jia ◽  
Hai Qin Qin ◽  
Yong Qi Wang ◽  
Ke Jun Xu

A new neighborhood variable precision rough set modal is presented in this paper. The modal possesses the characteristics of neighborhood rough set and variable precision rough set, so it can overcome shortcomings of classic rough set which only be fit for discrete variables and sensitive to noise. Based on giving the definitions of approximate reduction, lower and upper approximate reduction, lower and upper distribution reduction, two kinds of algorithms to confirm lower and upper distribution reduction were advanced. The modal was applied to diagnose one frequency modulated water pump vibration faults. The result shows the modal is more suitable to engineering problems, because it can not only deal with continues variables but also be robust to noise.


1989 ◽  
Vol 111 (1) ◽  
pp. 130-136 ◽  
Author(s):  
J. Z. Cha ◽  
R. W. Mayne

A discrete recursive quadratic programming algorithm is developed for a class of mixed discrete constrained nonlinear programming (MDCNP) problems. The symmetric rank one (SR1) Hessian update formula is used to generate second order information. Also, strategies, such as the watchdog technique (WT), the monotonicity analysis technique (MA), the contour analysis technique (CA), and the restoration of feasibility have been considered. Heuristic aspects of handling discrete variables are treated via the concepts and convergence discussions of Part I. This paper summarizes the details of the algorithm and its implementation. Test results for 25 different problems are presented to allow evaluation of the approach and provide a basis for performance comparison. The results show that the suggested method is a promising one, efficient and robust for the MDCNP problem.


Author(s):  
Leonard P. Pomrehn ◽  
Panos Y. Papalambros

Abstract Techniques to be employed for nonlinear design optimization with discrete variables are studied in the context of a particular problem arising from the design of a gear train. The mathematical model formulation was presented in an earlier article. In this sequel, a solution derivation is described, patterned as a multistage process. After certain reformulation and relaxation, a variety of infeasibility and non-optimality tests are performed, greatly reducing the size of the space containing the global optimum. Methods used to investigate the remaining space do not guarantee a global optimum, but could be replaced by more costly methods that do provide such guarantees. A global infimum is generated, bounding any improvements on the best known solution.


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