Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Yoshio Sugasawa"'
Publikováno v:
INTELLIGENCE MANAGEMENT. 3:3-14
Publikováno v:
INTELLIGENCE MANAGEMENT. 2:37-48
Autor:
Fumiyuki Takahashi, Yoshio Sugasawa
Publikováno v:
INTELLIGENCE MANAGEMENT. 1:47-54
Publikováno v:
Pacific Economic Review. 9:371-376
This paper describes innovation from the viewpoint of biologic evolution, a complex adaptive system. First, three characteristics of complex adaptive systems – variation, interaction and selection – are explained. Second, we propose that variatio
Autor:
Yoshio Sugasawa, Qun Jin
Publikováno v:
Mathematical and Computer Modelling. 22:109-118
This paper proposes a new approach to visually represent the behavior of multiprocess in a computer network system using stochastic Petri net (SPN) and an aggregate approach of SPN and Markov renewal process (MRP) to conduct behavior analysis and per
Publikováno v:
Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications. 1995:155-160
Autor:
Yoshio Sugasawa, Qun Jin
Publikováno v:
Computers & Industrial Engineering. 27:497-500
This paper proposes an aggregate approach of extended stochastic Petri net and Markov renewal process to conduct behavior analysis and reliability performance evaluation for distributed/parallel systems. Petri net is used because of its highly visual
Publikováno v:
Computers & Industrial Engineering. 27:501-504
Stochastic Petri Net is applied to model a shift processing system with repair and of distributed processing configuration, in which the states of the modeled system can be defined with ease. Moreover, the behavior of the system can be identified mor
Publikováno v:
Computers & Industrial Engineering. 24:523-529
Petri Net is very descriptive and flexible in modeling systems of concurrency and asynchronization. In this paper, it is used to model a co-operative motion system. A Markov Renewal Process with some non-regeneration points is applied to analyze the
Publikováno v:
Microelectronics Reliability. 31:933-939
Stochastic Petri Nets have been developed to model and analyze systems involving concurrent activities. However, the firing times of a Stochastic Petri Net model are always exponentially distributed. This paper presents an aggregate approach on how t