Ensuring fire safety in facilities with high fire risk is one of the pressing problems of modern society. Nowadays, there is a great need for accurate and effective prediction systems for fire prevention and rapid response. Since traditional methods do not provide the ability to quickly analyze and predict in real time, the development of algorithms and modern approaches using modern technologies is of great importance. This article analyzes fire risk prediction algorithms, their principles of operation and effectiveness, and considers methods for assessing and predicting fire risk using Artificial Intelligence (AI), Machine Learning (ML), and Big Data technologies. The article highlights the advantages and disadvantages of fire risk assessment algorithms, taking into account weather conditions, the ecological state of the area, human factors, and other important parameters. The research results can be used to create effective systems aimed at quickly detecting and preventing fire hazards. At the same time, it helps to speed up the response of emergency services, reduce economic losses, and improve environmental protection. This article aims to explore advanced technological approaches to improving fire safety and presents practical solutions.
| Mualliflar | Mirzoyan Mirzaaxmedovich Kamilov, T. Nurmukhamedov, Oybek Zokirovich Koraboshev, Bakhodir Saydullayevich Achilov |
|---|---|
| Jurnal | Кимёвий технология. Назорат ва бошқарув |
| Nashr sanasi | 2025-04-30 |
| Jild | 2025 |
| Son | 2 |
| Betlar | 60-67 |
| Til | en |
| DOI | 10.59048/2181-1105.1669 |
DOI: 10.59048/2181-1105.1669 · Maqolaning asl sahifasi · PDF
This article analyzes biometric access control systems using fingerprints. The article considers the advantages of using biometric technologies, including solutions aimed at ensuring security, protecting users' personal…
This paper deals with the development and analysis of feature extraction and optimisation algorithms for object recognition operators. Different algorithms are used to improve the efficiency of recognition operators in…
This paper analyzes the effectiveness of Random Forest and SVM models for detecting HTTP Flood attacks. Experimental results demonstrate that both models achieve high accuracy. Evaluation was conducted using Precision…
The increasing global demand for renewable energy has highlighted the importance of grid-connected solar inverters in ensuring efficient and stable power conversion. However, challenges such as fluctuations in solar…
This article discusses the automation of the methanol-acetone mixture absorption process to improve control efficiency. The existing local automatic control system (ACS) was upgraded to a cascade system, reducing…
This article discusses the processes in the elements and structures of three-phase electromagnetic current sensors used in measuring and controlling three-phase asymmetric reactive power in power supply systems…
This article examines modern approaches to adaptive control of air purification processes in industrial facilities, particularly in paint shops for parts coating. The relevance of the study is driven by the need to…
This article investigates the dynamic characteristics of a time-pulsed ultrasonic sensor used to measure water flow in open channels. The operating principle of the sensor, its response time in various hydrodynamic…
At the moment, many scientific researches are being conducted all over the world on the economical use of water and energy resources. Most of the scientific research works are aimed at improving measurement techniques…
In modern artificial intelligence systems, there is an acute need to understand the decision-making logic of "black box" algorithms. Our research proposes an innovative method for increasing the transparency of such…