A fire-spread simulation model developed as an extension of a dynamic percolation process model

Article Abstract:

A stochastic model of a fire-spreading process has been developed to simulate pertinent time-dependent changes. This model has been obtained by extending an existing stochastic model in which the fire-spreading process is described as a percolation process. The extended model considers the time period from ignition to the point at which flames have spread to an unburnt unit. In this model, the above two quantities (the time required for ignition and that required for reading an unburnt unit) are treated as continuous random variables dependent upon the respective probabilities of blaze up and fire spread. To evaluate this model, a Monte Carlo simulation system has been developed. Experiments on hypothetical and real city layouts show that this model is a useful simulation tool in studies concerned with firefighting. (Reprinted with permission of the publisher.)

Firefighting, Civil engineering, Environmental protection, Planning Applications, Fire Protection, Stochastic Model, Monte Carlo Methods, Fire extinction

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Linguistic dynamic simulation - a new approach

Article Abstract:

A new dynamic modeling methodology, SLIN, allows for the analysis of systems defined by linguistic variables. SLIN applies a set of logical rules which include base, tactical, strategic and structural change. To make the transition from qualitative to quantitative modes. logical rules are also used. SLIN is advantageously implemented in a very high-level language such as PROLOG. A simple ecological modeling problem illustrates SLIN's potential applications. (Reprinted with permission of the publisher.)

Linguistics, Dynamic programming, Dynamic Systems, PROLOG

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