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Use of mathematical models in environmental research

Use of mathematical models in environmental research

Abstract

У цій статті представлено ґрунтовний огляд ключових типів математичних моделей, що застосовуються в екології для аналізу, моделювання та прогнозування змін у природних і антропогенних системах. Розглянуто як традиційні аналітичні, так і сучасні комп'ютеризовані підходи до моделювання, включаючи стохастичні, динамічні, просторово-часові моделі, моделі на основі нечіткої логіки, машинного навчання й штучного інтелекту. Наведено численні приклади використання моделей для вирішення завдань управління водними ресурсами, контролю якості повітря, дослідження популяційних процесів, оцінки кліматичних змін та розрахунку екосистемних послуг. Підкреслено роль міждисциплінарного підходу та цифрових технологій в удосконаленні інструментів екологічного моделювання. Визначено перспективи інтеграції моделей у процеси планування природокористування, управління ризиками та формування екологічної політики.

This article provides a thorough overview of the key types of mathematical models used in ecology to analyze, model, and predict changes in natural and anthropogenic systems. Both traditional analytical and modern computerized modeling approaches are considered, including stochastic, dynamic, spatio-temporal, fuzzy logic, machine learning, and artificial intelligence models. Numerous examples of the use of models for solving problems of water resources management, air quality control, study of population processes, climate change assessment, and calculation of ecosystem services are given. The role of an interdisciplinary approach and digital technologies in improving environmental modeling tools is emphasized. The prospects for integrating models into the processes of environmental planning, risk management and environmental policy formation are determined.

Keywords

ecological systems, екологічні системи, просторово-часові моделі, mathematical modeling, dynamic models, машинне навчання, математичне моделювання, decision making, нечітка логіка, прийняття рішень, spatio-temporal models, machine learning, динамічні моделі, fuzzy logic, stochastic models, стохастичні моделі

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold