Development of the Method of Operational Forecasting of Fire in the Premises of Objects Under Real Conditions

A method for operational forecasting of fires is proposed that enables the sequential implementation of five procedures. The method development is necessary to predict early fires in premises in order to take measures to prevent them from escalating into an uncontrolled combustion phase ‒ a fire. As a result of research, it was found that a short-term forecast of the recurrence of increments of the air conditions by one step, based on the current measure of recurrence, is an effective indicator of early fires in premises. At the same time, it was found that before the moment of ignition of the material, the state of the air environment is characterized by dynamic stability, which is described by an irregular and time-dependent random change in the recurrence of the states of the vector of current increments of the state of the air environment. The values of the indicated levels of recurrence of the state increments are determined by the probability levels of 0.67 and 0.1, respectively. The probability of recurrence of state increments of 0.67 is characteristic of a larger number of measured states. When the material is ignited, the dynamics of the probability of recurrence of state increments change abruptly. There is a transition from two to one level of recurrence, close to zero probability ‒ the loss of dynamic stability (in the region of count 250). Further dynamics are characterized by the appearance of separate random recurrent increments corresponding to the instability of the air environment in the premises. In the course of the experiment, it was found that the accuracy of predicting a fire by the proposed method ranges from 4.48 % to 12.79 %, which generally indicates its efficiency. The obtained data prove useful in the development of new systems that early warn of fire in premises, as well as in the modernization of existing systems and means of fire protection of premise

Investigating Errors When Forecasting Processes with Uncertain Dynamics and Observation Noise by the Self-adjusting Brown's Zero-order Model

This paper reports a study into the errors of process forecasting under the conditions of uncertainty in the dynamics and observation noise using a self-adjusting Brown's zero-order model. The dynamics test models have been built for predicted processes and observation noises, which make it possible to investigate forecasting errors for the self-adjusting and adaptive models. The test process dynamics were determined in the form of a rectangular video pulse with a fixed unit amplitude, a radio pulse of the harmonic process with an amplitude attenuated exponentially, as well as a video pulse with amplitude increasing exponentially. As a model of observation noise, an additive discrete Gaussian process with zero mean and variable value of the mean square deviation was considered. It was established that for small values of the mean square deviation of observation noise, a self-adjusting model under the conditions of dynamics uncertainty produces a smaller error in the process forecast. For the test jump-like dynamics of the process, the variance of the forecast error was less than 1 %. At the same time, for the adaptive model, with an adaptation parameter from the classical and beyond-the-limit sets, the variance of the error was about 20 % and 5 %, respectively. With significant observation noises, the variance of the error in the forecast of the test process dynamics for the self-adjusting and adaptive models with a parameter from the classical set was in the range from 1 % to 20 %. However, for the adaptive model, with a parameter from the beyond-the-limit set, the variance of the prediction error was close to 100 % for all test models. It was established that with an increase in the mean square deviation of observation noise, there is greater masking of the predicted test process dynamics, leading to an increase in the variance of the forecast error when using a self-adjusting model. This is the price for predicting processes with uncertain dynamics and observation noises

Development of the Method of Operational Forecasting of Fire in the Premises of Objects Under Real Conditions

A method for operational forecasting of fires is proposed that enables the sequential implementation of five procedures. The method development is necessary to predict early fires in premises in order to take measures to prevent them from escalating into an uncontrolled combustion phase ‒ a fire. As a result of research, it was found that a short-term forecast of the recurrence of increments of the air conditions by one step, based on the current measure of recurrence, is an effective indicator of early fires in premises. At the same time, it was found that before the moment of ignition of the material, the state of the air environment is characterized by dynamic stability, which is described by an irregular and time-dependent random change in the recurrence of the states of the vector of current increments of the state of the air environment. The values of the indicated levels of recurrence of the state increments are determined by the probability levels of 0.67 and 0.1, respectively. The probability of recurrence of state increments of 0.67 is characteristic of a larger number of measured states. When the material is ignited, the dynamics of the probability of recurrence of state increments change abruptly. There is a transition from two to one level of recurrence, close to zero probability ‒ the loss of dynamic stability (in the region of count 250). Further dynamics are characterized by the appearance of separate random recurrent increments corresponding to the instability of the air environment in the premises. In the course of the experiment, it was found that the accuracy of predicting a fire by the proposed method ranges from 4.48 % to 12.79 %, which generally indicates its efficiency. The obtained data prove useful in the development of new systems that early warn of fire in premises, as well as in the modernization of existing systems and means of fire protection of premise