CAUSIM: a rule-based causal simulation system
Article Abstract:
Researchers have felt that expert performance must also rest on knowledge of deep models which relate underlying causal variables to observable facts. Simulation based upon causal knowledge is an important method to infer possible consequences from given situations. This paper presents a rule-based causal simulation system called CAUSIM, which basically offers two kinds of simulation: backward simulation and forward simulation. Backward simulation is used to infer the instant behavior of specific attributes, whereas forward simulation is taken to arrive at possible overall scenarios. In addition, CAUSIM invokes constraint rules which describe incompatible behavior and values among related variables before applying simulation rules in order to obviate the inconsistencies between the simulation result and existing facts. The strength of CAUSIM lies in the capability of performing both qualitative and quantitative causal simulation in an integrated environment. (Reprinted by permission of the publisher.)
Publication Name: SIMULATION
Subject: Engineering and manufacturing industries
ISSN: 0037-5497
Year: 1991
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Simulation of epiphytic bacterial growth under field conditions
Article Abstract:
A model of the growth of bacteria on leaf surfaces was developed using a combined continuous and discrete simulation approach. It is important to understand the population dynamics of these bacteria under field conditions because of their role in causing disease and frost damage to plants, and their potential as biological control agents and enhancers of precipitation. The model incorporates many of the necessary field variables, and is designed to be part of a larger ecological model involving arrivals and departures, inimical organisms, and involvement in atmospheric processes. Historical validation indicates a reasonable correlation between predicted and observed population levels in the field. Analysis of simulation results suggests an explanation for the observed lognormal distribution of bacteria in the simuland. (Reprinted by permission of the publisher.)
Publication Name: SIMULATION
Subject: Engineering and manufacturing industries
ISSN: 0037-5497
Year: 1991
User Contributions:
Comment about this article or add new information about this topic:
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