Forest Fire Danger Prediction Using Deterministic Probabilistic Approach
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Forest Fire Danger Prediction Using Deterministic-Probabilistic Approach
Author: Baranovskiy, Nikolay Viktorovich
language: en
Publisher: IGI Global
Release Date: 2021-05-21
Forest fires cause ecological, economic, and social damage to various states of the international community. The causes of forest fires are rather varied, but the main factor is human activity in settlements, industrial facilities, objects of transport infrastructure, and intensively developed territories (in other words, anthropogenic load). In turn, storm activity is also a basic reason for forest fires in remote territories. Therefore, scientists across the world have developed methods, approaches, and systems to predict forest fire danger, including the impact of human and storm activity on forested territories. An important and comprehensive point of research is on the complex deterministic-probabilistic approach, which combines mathematical models of forest fuel ignition by various sources of high temperature and probabilistic criteria of forest fire occurrence. Forest Fire Danger Prediction Using Deterministic-Probabilistic Approach provides a comprehensive approach of forest fire danger prediction using mathematical models of forest fuel with consideration to anthropogenic load, storm activity, and meteorological parameters. Specifically, it uses the deterministic-probabilistic approach to predict forest fire danger and improve forest protection from fires. The chapters will cover various tree types, mathematical models, and solutions for reducing the destructive consequences of forest fires on ecosystems. This book is ideal for professionals and researchers working in the field of forestry, forest fire danger researchers, executives, computer engineers, practitioners, government officials, policymakers, academicians, and students looking for a new system to predict forest fire danger.
Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks
Author: Baranovskiy, Nikolay Viktorovich
language: en
Publisher: IGI Global
Release Date: 2019-12-27
To understand the catastrophic processes of forest fire danger, different deterministic, probabilistic, and empiric models must be used. Simulating various surface and crown forest fires using predictive information technology could lead to the improvement of existing systems and the examination of the ecological and economic effects of forest fires in other countries. Predicting, Monitoring, and Assessing Forest Fire Dangers and Risks provides innovative insights into forestry management and fire statistics. The content within this publication examines climate change, thermal radiation, and remote sensing. It is designed for fire investigators, forestry technicians, emergency managers, fire and rescue specialists, professionals, researchers, meteorologists, computer engineers, academicians, and students invested in topics centered around providing conjugate information on forest fire danger and risk.
Applications of Nature-Inspired Computing in Renewable Energy Systems
Renewable energy is crucial to preserve the environment. This energy involves various systems that must be optimized and assessed to provide better performance; however, the design and development of renewable energy systems remains a challenge. It is crucial to implement the latest innovative research in the field in order to develop and improve renewable energy systems. Applications of Nature-Inspired Computing in Renewable Energy Systems discusses the latest research on nature-inspired computing approaches applied to the design and development of renewable energy systems and provides new solutions to the renewable energy domain. Covering topics such as microgrids, wind power, and artificial neural networks, it is ideal for engineers, industry professionals, researchers, academicians, practitioners, teachers, and students.