A Systematic Study on Reinforcement Learning Based Applications

Energies, Journal Year: 2023, Volume and Issue: 16(3), P. 1512 - 1512

Published: Feb. 3, 2023

We have analyzed 127 publications for this review paper, which discuss applications of Reinforcement Learning (RL) in marketing, robotics, gaming, automated cars, natural language processing (NLP), internet things security, recommendation systems, finance, and energy management. The optimization use is critical today’s environment. mainly focus on the RL application Traditional rule-based systems a set predefined rules. As result, they may become rigid unable to adjust changing situations or unforeseen events. can overcome these drawbacks. learns by exploring environment randomly based experience, it continues expand its knowledge. Many researchers are working RL-based management (EMS). utilized such as optimizing smart buildings, hybrid automobiles, grids, managing renewable resources. contributes achieving net zero carbon emissions sustainable In context technology, be optimize regulation building heating, ventilation, air conditioning (HVAC) reduce consumption while maintaining comfortable atmosphere. EMS accomplished teaching an agent make judgments sensor data, temperature occupancy, modify HVAC system settings. has proven beneficial lowering usage buildings active research area buildings. used electric vehicles (HEVs) learning optimal control policy maximize battery life fuel efficiency. acquired remarkable position gaming applications. majority security-related operate simulated recommender provide good suggestions accuracy diversity. This article assists novice comprehending foundations reinforcement

Language: Английский

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Harnessing quantum computing for smart agriculture: Empowering sustainable crop management and yield optimization

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 218, P. 108680 - 108680

Published: Feb. 10, 2024

Language: Английский

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Navigating the impact of climate change in India: a perspective on climate action (SDG13) and sustainable cities and communities (SDG11)

Frontiers in Sustainable Cities, Journal Year: 2024, Volume and Issue: 5

Published: Jan. 11, 2024

Climate change is a global concern of the current century. Its rapid escalation and ever-increasing intensity have been felt worldwide, leading to dramatic impacts globally. The aftermath climate in India has brought about profound transformation India's environmental, socio-economic, urban landscapes. In 2019, ranked seventh, among most affected countries by extreme weather events caused due changing climate. This impact was evident terms both, human toll with 2,267 lives lost, economic damage, which accounted for 66,182 million US$ Purchasing power parities (PPPs). Over recent years, experienced significant increase number frequency events, causing vulnerable communities. country severe air pollution problems several metropolitan cities highlighted list world's polluted cities. Additionally, become populous nation globally, boasting population 1.4 billion people, equating ~18% population, experiencing an increased rate consumption natural resources. Owing country's scenario, various mitigation strategies, including nature-based solutions, must be implemented reduce such support target achieving Sustainable Development Goals (SDGs). review tries holistic understanding effects on different sectors identify challenges SDG 13 11. Finally, it also future recommendations change-related research from Indian perspective.

Language: Английский

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Application of the Lasso regularisation technique in mitigating overfitting in air quality prediction models

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 2, 2025

Language: Английский

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Rainfall Forecasting in India Using Combined Machine Learning Approach and Soft Computing Techniques : A HYBRID MODEL

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2025, Volume and Issue: 11(1)

Published: Jan. 9, 2025

Accurate rainfall prediction in India is crucial for agriculture, water management, and disaster preparedness, particularly due to the reliance on southwest monsoon. This paper examines historical trends from 1901 2022, highlighting significant anomalies changes identified through Pettitt test. The effectiveness of advanced machine learning techniques explored Artificial Neural Network-Multilayer Perceptron (ANN-MLP) enhancing forecasting accuracy compared with statistical methods. By integrating important climate variables—temperature, humidity, wind speed, precipitation into ANN-MLP model, its ability capture complex nonlinear relationships demonstrated. Additionally, analysis employs geo-statistical techniques, specifically Kriging, visualize spatial-temporal variability across different regions India. findings emphasize potential modern computational methods overcome traditional challenges, ultimately improving decision-making agricultural planning resource management face variability.

Language: Английский

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Machine Learning and Deep Learning Paradigms: From Techniques to Practical Applications and Research Frontiers

Computers, Journal Year: 2025, Volume and Issue: 14(3), P. 93 - 93

Published: March 6, 2025

Machine learning (ML) and deep (DL), subsets of artificial intelligence (AI), are the core technologies that lead significant transformation innovation in various industries by integrating AI-driven solutions. Understanding ML DL is essential to logically analyse applicability identify their effectiveness different areas like healthcare, finance, agriculture, manufacturing, transportation. consists supervised, unsupervised, semi-supervised, reinforcement techniques. On other hand, DL, a subfield ML, comprising neural networks (NNs), can deal with complicated datasets health, autonomous systems, finance industries. This study presents holistic view technologies, analysing algorithms application’s capacity address real-world problems. The investigates application which techniques implemented. Moreover, highlights latest trends possible future avenues for research development (R&D), consist developing hybrid models, generative AI, incorporating technologies. aims provide comprehensive on serve as reference guide researchers, industry professionals, practitioners, policy makers.

Language: Английский

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Article Context and Technological Integration: AI's Role in Climate Change Research

LatIA, Journal Year: 2025, Volume and Issue: 3, P. 85 - 85

Published: Feb. 19, 2025

This article explores the transformative role of artificial intelligence and machine learning in tackling climate change. It highlights how advanced computational techniques enhance our understanding response to environmental shifts. Machine algorithms process vast datasets, revealing patterns that traditional methods might overlook. Deep neural networks, particularly effective research, analyze satellite imagery, sensor data, indicators with unprecedented accuracy. Key applications include predictive modeling change impacts. Using convolutional recurrent researchers generate high-resolution projections temperature rises, sea-level changes, extreme weather events remarkable precision. AI also plays a vital data integration, synthesizing observations, ground-based measurements, historical records create more reliable models. Additionally, deep enable real-time monitoring, tracking changes like deforestation, ice cap melting, ecosystem The AI-powered optimization models mitigation efforts. These carbon reduction strategies, optimize renewable energy use, support sustainable urban planning. By leveraging learning, research demonstrates AI-driven approaches offer data-backed solutions for adaptation. innovations provide practical strategies address global challenges effectively.

Language: Английский

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Nowcasting extreme rain and extreme wind speed with machine learning techniques applied to different input datasets

Atmospheric Research, Journal Year: 2022, Volume and Issue: 282, P. 106548 - 106548

Published: Dec. 2, 2022

Predicting extreme weather events in a short time period and their developing localized areas is challenge. The nowcasting of severe an issue for air traffic management control because it affects aviation safety, determines delays diversions. This work part larger study devoted to rain wind speed the area Malpensa airport by merging different datasets. We use as reference station Novara develop machine learning model which could be reusable other locations. In this location we have availability ground-based sensors, Global Navigation Satellite System (GNSS) receiver, C-band radar lightning detectors. Our analysis shows that Long Short-Term Memory Encoder Decoder (LSTM E/D) approach well suited meteorological variables. predictions are based on 4 datasets configurations providing nowcast 1 h with step 10 min. results very promising probability detection higher than 90%, false alarms lower 2%, good performance first 30 configuration using just stations GNSS data input provides excellent performances should preferred ones, since refers pre-convective environment, thus can adaptable any conditions.

Language: Английский

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Advances and applications of machine learning and deep learning in environmental ecology and health

Environmental Pollution, Journal Year: 2023, Volume and Issue: 335, P. 122358 - 122358

Published: Aug. 9, 2023

Language: Английский

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A Systematic Literature Review on Identifying Patterns Using Unsupervised Clustering Algorithms: A Data Mining Perspective

Symmetry, Journal Year: 2023, Volume and Issue: 15(9), P. 1679 - 1679

Published: Aug. 31, 2023

Data mining is an analytical approach that contributes to achieving a solution many problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable information from massive datasets. Clustering in data used for splitting or segmenting items/points into meaningful groups clusters grouping the items are near each other based on certain statistics. This paper covers various elements of clustering, such as algorithmic methodologies, applications, clustering assessment measurement, researcher-proposed enhancements with their impact thorough grasp algorithms, its advances achieved existing literature. study includes literature search papers published between 1995 2023, including conference journal publications. The begins outlining fundamental techniques along algorithm improvements emphasizing advantages limitations comparison algorithms. It investigates evolution measures algorithms emphasis metrics gauge quality, F-measure Rand Index. variety clustering-related topics, approaches, practical evaluation, improvements. addresses numerous methodologies offered increase convergence speed, resilience, accuracy initialization procedures, distance measures, optimization strategies. work concludes active research area driven need identify significant patterns structures data, enhance knowledge acquisition, improve decision making across different domains. aims contribute broader base practitioners researchers, facilitating informed fostering advancements field through analysis enhancements, metrics,

Language: Английский

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