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Fires

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Improving Fire Detection Accuracy through Enhanced Convolutional Neural Networks and Contour Techniques.

Sensors (Basel, Switzerland)
In this study, a novel method combining contour analysis with deep CNN is applied for fire detection. The method was made for fire detection using two main algorithms: one which detects the color properties of the fires, and another which analyzes th...

Optimizing automated compliance checking with ontology-enhanced natural language processing: Case in the fire safety domain.

Journal of environmental management
The fire safety compliance checking (FSCC) plays a crucial role in ensuring the quality of fire engineering design and eliminating inherent fire hazards. It requires an objective and rational interpretation of fire regulations. However, the texts of ...

Cooperative control of environmental extremes by artificial intelligent agents.

Journal of the Royal Society, Interface
Humans have been able to tackle biosphere complexities by acting as ecosystem engineers, profoundly changing the flows of matter, energy and information. This includes major innovations that allowed to reduce and control the impact of extreme events....

Predicting burn probability: Dimensionality reduction strategies enable accurate and computationally efficient metamodeling.

Journal of environmental management
Predicting the probability that a given location will be burnt by a wildfire is an important part of understanding the risk that wildfires pose and how our management actions (e.g., prescribed burning) can reduce this risk. Existing methods to quanti...

U3UNet: An accurate and reliable segmentation model for forest fire monitoring based on UAV vision.

Neural networks : the official journal of the International Neural Network Society
Forest fires pose a serious threat to the global ecological environment, and the critical steps in reducing the impact of fires are fire warning and real-time monitoring. Traditional monitoring methods, like ground observation and satellite sensing, ...

GGSYOLOv5: Flame recognition method in complex scenes based on deep learning.

PloS one
The continuous development of the field of artificial intelligence, not only makes people's lives more convenient but also plays a role in the supervision and protection of people's lives and property safety. News of the fire is not uncommon, and fir...

Classification of soil contamination by heavy metals (Cr, Ni, Pb, Zn) in wildfire-affected areas using laser-induced breakdown spectroscopy and machine learning.

Environmental science and pollution research international
The assessment of soil contamination by heavy metals is of high importance due to its impact on the environment and human health. Standard high-sensitivity spectroscopic techniques for this task such as atomic absorption spectrometry (AAS) and induct...

Capsule neural network and adapted golden search optimizer based forest fire and smoke detection.

Scientific reports
Forest fires represent a major risk to both ecosystems and human health that rising frequency of it exacerbates global warming. This study introduces an innovative methodology for detecting forest fires and smoke using an enhanced capsule neural netw...

Spatial prediction of forest fires in India: a machine learning approach for improved risk assessment and early warning systems.

Environmental science and pollution research international
Forest fires pose a significant ecological and environmental threat globally, and India has seen a marked increase in both the frequency and severity of these events in recent years. This has led to extensive damage to natural resources, including fo...

Forest fire susceptibility mapping using multi-criteria decision making and machine learning models in the Western Ghats of India.

Journal of environmental management
Forest fires have significantly increased over the last decade due to shifts in rainfall patterns, warmer summers, and long spells of dry weather events in the coastal regions. Assessment of susceptibility to forest fires has become an important mana...