Greening smart cities: An investigation of the integration of urban natural resources and smart city technologies for promoting environmental sustainability

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 99, P. 104985 - 104985

Published: Oct. 5, 2023

Language: Английский

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Accelerating the green hydrogen revolution: A comprehensive analysis of technological advancements and policy interventions

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 67, P. 458 - 486

Published: April 22, 2024

Promoting green hydrogen has emerged as a pivotal discourse in the contemporary energy landscape, driven by pressing environmental concerns and quest for sustainable solutions. This paper delves into multifaceted domain of C-Suite issues about hydrogen, encompassing both technological advancements policy considerations. The question whether is poised to become focal point upcoming race explored through an extensive analysis its potential clean versatile carrier. transition from conventional fossil fuels considered fundamental shift paradigms, with far-reaching implications global markets. provides comprehensive overview state-of-the-art technologies, including fuel cells, photocatalysts, photo electrocatalysts, panels. In tandem advancements, role strategy fostering development assumes paramount significance. elucidates critical interplay between government policies, market dynamics, corporate strategies shaping landscape. It mechanisms such subsidies, carbon pricing, renewable mandates, shedding light on their incentivize production adoption hydrogen. offers nuanced exploration surrounding painting picture considerations that underpin emergence transformative source. As community grapples imperatives climate change mitigation pursuit solutions, understanding these becomes imperative executives, policymakers, stakeholders alike.

Language: Английский

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Machine learning predictions of regional steel price indices for east China

Ironmaking & Steelmaking Processes Products and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: May 16, 2024

From 1 January 2010 to 15 April 2021, this study examines the challenging task of daily regional steel price index forecasting in east Chinese market. We train our models using cross-validation and Bayesian optimisations implemented through expected improvement per second plus algorithm, utilise Gaussian process regressions validate findings. Investigated parameters as part model training involve predictor standardisation status, basis functions, kernels standard deviation noises. The that were built accurately predicted indices between 8 2019 with an out-of-sample relative root mean square error 0.57%, 0.84, absolute 0.48, correlation coefficient 99.81%.

Language: Английский

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Renewable energy transition and sustainable development: Evidence from China

Energy Economics, Journal Year: 2025, Volume and Issue: unknown, P. 108232 - 108232

Published: Jan. 1, 2025

Language: Английский

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Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0317914 - e0317914

Published: Feb. 6, 2025

Regarding the transportation of people, commodities, and other items, aeroplanes are an essential need for society. Despite generally low danger associated with various modes transportation, some accidents may occur. The creation a machine learning model employing data from autonomous-reliant surveillance transmissions is detection prediction commercial aircraft accidents. This research included development abnormal categorisation models, assessment recognition quality, anomalies. methodology consisted following steps: formulation problem, selection labelling, construction prediction, installation, testing. tagging technique was based on requirements set by Global Aviation Organisation business jet-engine aircraft, which expert pilots then validated. 93% precision demonstrated excellent match most effective model, linear dipole Furthermore, "good fit" verified its achieved area-under-the-curve ratios 0.97 identification 0.96 daily detection.

Language: Английский

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Market orientation, technological opportunity, and new product innovation performance

Journal of Business Research, Journal Year: 2023, Volume and Issue: 162, P. 113841 - 113841

Published: April 1, 2023

Language: Английский

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Enhancing Robot Path Planning through a Twin-Reinforced Chimp Optimization Algorithm and Evolutionary Programming Algorithm

IEEE Access, Journal Year: 2023, Volume and Issue: unknown, P. 1 - 1

Published: Nov. 30, 2023

The importance of efficient path planning (PP) cannot be overstated in the domain robots, as it involves utilization intelligent algorithms to determine optimal trajectory for robot navigate between two given points.The main target PP is potential trajectories operating a complex environment containing various obstacles.The implementation these movements should facilitate traversing without encountering any collisions, starting from its initial location and reaching intended destination.In order address challenges associated with PP, this study applies chimp optimization algorithm (CHOA) local searching (LS) technique evolutionary programming (EPA) enhance route discovered via collection LSs.In CHOA's tendency converge minima, new updating called twin-reinforced (TR) developed.In assess effectiveness TRCHOA, we conducted comparative analysis other widely used meta-heuristic that are typically employed solving problems.Additionally, included conventional probabilistic roadmap method (PRM) our evaluation.We evaluated performances on standardized set benchmark problems.Our findings indicate TRCHOA outperforms terms performance.The evaluation encompasses several key criteria, namely length, consistency scheduled paths, time complexity, rate success.The experiments provide evidence statistically significant value enhancements obtained through proposed method.The derived compelling capacity accurately most within specified test map.

Language: Английский

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Assessment of future prediction of urban growth and climate change in district Multan, Pakistan using CA-Markov method

Urban Climate, Journal Year: 2023, Volume and Issue: 53, P. 101766 - 101766

Published: Nov. 25, 2023

Language: Английский

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Modeling and Estimating the Land Surface Temperature (LST) Using Remote Sensing and Machine Learning (Case Study: Yazd, Iran)

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(3), P. 454 - 454

Published: Jan. 24, 2024

The pressing issue of global warming is particularly evident in urban areas, where thermal islands amplify the effect. Understanding land surface temperature (LST) changes crucial mitigating and adapting to effect heat islands, ultimately addressing broader challenge warming. This study estimates LST city Yazd, Iran, field high-resolution image data are scarce. assessed through parameters (indices) available from Landsat-8 satellite images for two contrasting seasons—winter summer 2019 2020, then it estimated 2021. modeled using six machine learning algorithms implemented R software (version 4.0.2). accuracy models measured root mean square error (RMSE), absolute (MAE), logarithmic (RMSLE), standard deviation different performance indicators. results show that gradient boosting model (GBM) algorithm most accurate estimating LST. albedo NDVI features with greatest impact on both (with 80.3% 11.27% importance) winter 72.74% 17.21% importance). 2021 showed acceptable seasons. GBM each seasons useful modeling based learning, support decision-making related spatial variations temperatures. method developed can help better understand island mitigation strategies improve human well-being enhance resilience climate change.

Language: Английский

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Smart Energy Management System Using Machine Learning

Computers, materials & continua/Computers, materials & continua (Print), Journal Year: 2024, Volume and Issue: 78(1), P. 959 - 973

Published: Jan. 1, 2024

Energy management is an inspiring domain in developing of renewable energy sources. However, the growth decentralized production revealing increased complexity for power grid managers, inferring more quality and reliability to regulate electricity flows less imbalance between demand. The major objective system achieve optimum procurement utilization throughout organization, minimize costs without affecting production, environmental effects. Modern essential complex subject because excessive consumption residential buildings, which necessitates optimization user comfort. To address issue management, many researchers have developed various frameworks; while each framework was sustain a balance comfort consumption, this problem hasn’t been fully solved how difficult it solve it. An inclusive Intelligent Management System (IEMS) aims provide overall efficiency regarding generation, increase flexibility, generation systems, improve reduce carbon dioxide emissions, stability, costs. Machine Learning (ML) emerging approach that may be beneficial predict better way with assistance Internet (IoE) network. IoE network playing vital role sector collecting effective data usage, resulting smart resource management. In research work, IEMS proposed Smart Cities (SC) using ML technique resolve problem. minimized its intelligent nature provided outcomes than previous approaches terms 92.11% accuracy, 7.89% miss-rate.

Language: Английский

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