fire risk
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Safety is the premise of the stable and sustainable development of the chemical industry, safety accidents will not only cause casualties and economic losses, but also cause panic among workers and nearby residents. Robot safety inspection based on the fire risk level in a chemical industrial park can effectively reduce process accident losses and can even prevent accidents. The optimal inspection path is an important support for patrol efficiency, therefore, in this study, the fire risk level of each location to be inspected, which is obtained by the electrostatic discharge algorithm (ESDA)–nonparallel support vector machine evaluation model, is combined with the optimisation of the inspection path; that is, the fire risk level is used to guide the inspection path planning. The inspection path planning problem is a typical travelling salesman problem (TSP). The discrete ESDA (DESDA), based on the ESDA, is proposed. In view of the shortcomings of the long convergence time and ease of falling into the local optimum of the DESDA, further improvements are proposed in the form of the IDESDA, in which the greedy algorithm is used for the initial population, the 2-opt algorithm is applied to generate new solutions, and the elite set is joined to provide the best segment for jumping out of the local optimum. In the experiments, 11 public calculation examples were used to verify the algorithm performance. The IDESDA exhibited higher accuracy and better stability when solving the TSP. Its application to chemical industrial parks can effectively solve the path optimisation problem of patrol robots.

The article aims to study statistical data on the consequences of fires in the Republic of Buryatia from 2009 to 2020 using the methods of social and mathematical statistics. The study is relevant due to the current situation with fires and integral fire risk indicators in the municipalities. Man-made fires have been a source of increased danger to health and lives of the population, causing great material damage. Fires are a direct threat to the demographic situation in the region since they cause premature mortality. For households, fires undermine social status, destroy social units, cause moral harm aggravating stress, which provokes illnesses. From the technical point of view, man-made fires create risks for dilapidated houses and facilities that do not meet the fire safety requirements. The Republic of Buryatia is a region with a weak degree of industrial development and a vast territory with a low distribution of settlements, i.e. considerable remoteness from the regional centers. The impact of fires (which make up 99% of all types of emergency situation) on the social well-being of the population is studied. Based on the methodology and calculations of fire risks by the number of fires, injured and killed, material damage and destroyed buildings, it was established that the level of protection of residents of Buryatia from fire risks is insufficient. The indicators should encourage the government to develop and implement effective safety measures.

Abstract Geographical information system data has been used in forest fire risk zone mapping studies commonly. However, forest fires are caused by many factors, which cannot be explained only by geographical and meteorological reasons. Human-induced factors also play an important role in occurrence of forest fires and these factors depend on various social and economic conditions. This article aims to prepare a fire risk zone map by using a data set consisting of nine human-induced factors, three natural factors, and a temperature factor causing forest fires. Moreover, an artificial intelligence method, k-means, clustering algorithm was employed in preparation of the fire risk zone map. Turkey was selected as the study area as there are social and economic varieties among its zones. Therefore, the forestry zones in Turkey were separated into three groups as low, moderate, and high-risk categories and a map was provided for these risk zones. The map reveals that the forestry zones on the west coast of Turkey are under high risk of forest fire while the moderate risk zones mostly exist in the southeastern zones. The zones located in the interior parts, in the east, and on the north coast of Turkey have comparatively lower forest fire risks.

Abstract This article lists the principles of fire risk assessment and management of electrical installations, provides the main terms used in this subject area, and their meanings. The article also talks about factors affecting the magnitude of fire risk (risk-forming factors). Special attention is paid to the human factor. Formulas for probabilistic assessment of fire risks of electrical installations and an algorithm for assessing the fire hazard of electrical installations, as well as a scheme of the algorithm for calculating individual fire risk are given.

Fire risk is perhaps the most common risk in the category of special emergencies, being a phenomenon that affects important areas of economic and social life, such as buildings, industrial facilities, public spaces, forests, crops, or transportation. Scientific investigation of fires is constituted as a set of organized actions, of technical nature, undertaken to determine the causes that led to the occurrence of fires, the source of ignition, and the circumstances that favored the event. Numerical fire modeling is a widely recognized and accepted tool for analysis in fire research. The results of the investigation carried out on-site are compared with the results of fire evolution obtained by computer simulation, using numerical models based on known input data, to verify different hypotheses regarding the cause of the fire. The advantages over experimental methods are expressed by low costs and substantial time savings. Moreover, several simulations can be run simultaneously, for different scenarios of the event or the analysis of different consequences. The paper presents the main advantages that numerical modeling by FDS methods brings in the technical-scientific expertise of fire, with implications in the data analysis, development, and testing of hypotheses, respectively in the selection process of the final hypothesis. words.

Abstract The article considers approaches to the formation of a system of criteria for assessing the electrical installations fire condition of the agricultural and industrial complex. Based on the analysis of the literature, the conclusion is made about the appropriateness of the use of expert assessments. To implement the decision, a group of experts was assembled, on the basis of whose knowledge a list of 42 parametersζ characterizing the fire condition of the electrical installation was determined. To identify the relationships and form a method for calculating the estimated value of fire risk, experts assessed the fire condition of 70 electrical installations of the agricultural and industrial complex of the region. A knowledge base was formed from the resulting values. As a method of data analysis, it was decided to use neural networks, but the available sample is not sufficient for high-quality training of a neural network. Therefore, the correlation method and the principal component method were considered, and based on the calculations, it was decided to use a training sample consisting of 6 principal components for training a neural network. A neural network was trained on these data and the values of the average error were obtained sufficiently low, which may indicate sufficient accuracy of the generated model. The article also presents a conceptual scheme of a software package for automating calculations in accordance with the developed model.

Long-term care hospitals for the elderly have a high risk of fire. To reduce this risk, the installation of a horizontal refuge area has been stipulated since 2015. However, most hospitals are still at risk due to the lack of retroactive regulations. Therefore, in this study, the efficiency of the horizontal refuge area was analyzed through evacuation safety evaluation using fire and evacuation simulations. As a result of evacuation safety evaluation for the two hospitals, the reduction ratio of evacuation time was 70% (day time) and 77% (night time). In addition, evacuation safety can be secured through the installation of a horizontal refuge area. The results of this study are expected to be used as a basis for preparing retroactive regulations for horizontal refuge areas in long-term care hospitals for the elderly in the future.