ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING ALGORITHMS FOR ENVIRONMENTAL MANAGEMENT STRATEGIES

Aug 3, 2026

Uploaded by Maeve

The study report highlights how artificial intelligence and machine learning can support environmental management and climate-change decision-making. It focuses on AI-driven forecasting of climate dynamics, identification of likely trends, and selection of optimal management strategies. Emphasis is placed on analyzing large datasets to improve predictions of extreme weather events and long-term shifts in climate behavior, enabling the design of energy-efficient systems and more adaptive solutions for reducing risks.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages2

Reading Time5 min

AccessFree to download

Introduction

Results and discussion

Forecasting extreme weather and climate patterns

Energy efficiency and environmental optimization

Industrial and institutional applications

E.R.A – Modern science: electronics, robotics and automation blood-testis barrier in male mice fed with diet minced with insecticide Bifenthrin. Adv. Life Sci. 10(4): 593-599. 2. Sarni, R, Souza,F.(2007) . Tratamento da desnutrição energéticoprotéico moderado e grave In Nobrega FJ (Ed) . Distúrbios da nutrição:na infância e na adolescência. Rio de Janeiro., 210. 3. Aeffner F, Wilson K, Bolon B, et al. Commentary: roles for pathologists in a highthroughput image analysis team. Toxicol Pathol. 2016; 44:825–834. ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING ALGORITHMS FOR ENVIRONMENTAL MANAGEMENT STRATEGIES Kurianovich N.A. (student of group No. 3) Belorussian State University, Minskl, Belarus Scientific Supervisors – Svetlana Vidisheva, Tatiana Sitnikova (Senior teachers of the Department of English Language for Natural Sciences FSK, Belorussian State University) Abstract: In this study report, we shed light on the possibilities of the Artificial Intelligence application in the field of environment and climate change, as well as the help of machine learning algorithms in predicting climate change, determining optimal environmental management strategies and developing new energy-efficient systems. Key words Artificial Intelligence, machine learning, ML algorithms, and environment Introduction During the past few decades, humankind has been facing growing environmental problems that require urgent solutions to improve the situation in the world. The necessity to employ new technologies, which could effectively deal with environmental threats, has come to the forefront. Artificial Intelligence (AI) is one of these technologies, providing extensive opportunities for solving environmental issues. Results and discussion Having analyzed vast datasets, AI algorithms enhance our understanding of climate patterns, enabling accurate predictions of extreme weather events, sea-level rise, and ecosystem shifts. Machine learning (ML) algorithms have all the possibilities to analyze large volumes of weather and climate data to predict future climate conditions. For example, DeepMind, a subsidiary of Google, has developed an Artificial Intelligence system that can predict wind energy distribution 36 hours ahead, allowing for the optimization of wind turbine use. As a part of the project in Burundi, Chad, and Sudan, based on the use of AI, the analysis of preceding changes in the environment is being conducted to provide forecasts of these changes in the future. At the sametime Belarusian, specialists, together with their counterparts from the Arctic and Antarctic Research Institute (AARI), are set to develop a new system for long-term climate change prediction based on Artificial Intelligence. Dr. Sergey Soldatenko, a member of AARI, a Doctor of Physics and Mathematics, and a professor, shared: “By applying artificial intelligence methods to analyze past and present climate system observations, we aim to construct a self-learning Earth system modeling system and utilize this system for ultra-long-term weather and climate forecasting.” AARI specialists and the Institute of Natural Resources Use of the National Academy of Sciences of Belarus will concentrate in their work on simulating the model of the climate conditions in the Union State territory over a 20-year time horizon. The outcomes of the developments are planned to be implemented in Roshydromet institutions. As Sergey Soldatenko elucidates, current traditional methods fall short in adequately considering hard-to-predict factors and sudden shifts in various aspects of Earth’s climate, which complicate weather forecasting from months to 20 years ahead. The scientist affirms that digital self-learning systems should address this issue. Artificial intelligence also plays a crucial role in weather forecasting. With the help of AI, weather forecasts can be improved and the accuracy of predictions can be increased. For instance, The Weather Company used AI to foreca

FAQs

How can AI improve climate change and environmental forecasting?

AI algorithms analyze large datasets of weather and climate information to predict future conditions and extreme events with higher accuracy. This enables more informed planning for environmental management.

What environmental management strategies can benefit from machine learning?

Machine learning can help determine effective strategies for mitigating carbon dioxide emissions and adapting to climate change. It supports more efficient, data-driven decision processes.

How do AI systems contribute to energy efficiency in environmental applications?

AI can automate and optimize energy consumption, such as managing power use in data centers and improving wind turbine operations. These applications aim to reduce waste and increase operational efficiency.

Aug 3, 2026

Uploaded by Maeve