Journal of the Asia Pacific Economy, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 28
Published: July 8, 2024
Language: Английский
Journal of the Asia Pacific Economy, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 28
Published: July 8, 2024
Language: Английский
The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 906, P. 167536 - 167536
Published: Oct. 2, 2023
Language: Английский
Citations
42Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 449, P. 140842 - 140842
Published: Feb. 9, 2024
Language: Английский
Citations
24The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 916, P. 170210 - 170210
Published: Jan. 20, 2024
Language: Английский
Citations
22Economic Analysis and Policy, Journal Year: 2024, Volume and Issue: 83, P. 42 - 59
Published: June 12, 2024
Language: Английский
Citations
14Advances in civil and industrial engineering book series, Journal Year: 2024, Volume and Issue: unknown, P. 136 - 165
Published: June 24, 2024
The chapter explores the integration of nanotechnology, energy harvesting, and smart highways into global transportation infrastructure, aiming to create sustainable efficient systems. Nanotechnology enhances road surface durability functionality, offering increased strength, resilience, self-healing properties. Energy harvesting techniques, such as piezoelectric solar technologies, harness kinetic from vehicular motion sunlight, powering streetlights, even grid. Smart highways, enabled by interconnected sensors communication systems, monitor traffic flow, adjust speed limits, provide real-time updates, autonomously manage These innovations not only promise a ecosystem but also catalyze economic growth, environmental preservation, enhanced quality life for communities worldwide.
Language: Английский
Citations
14Renewable Energy, Journal Year: 2024, Volume and Issue: 232, P. 121108 - 121108
Published: July 31, 2024
Language: Английский
Citations
14IEEE Transactions on Engineering Management, Journal Year: 2024, Volume and Issue: 71, P. 7681 - 7700
Published: Jan. 1, 2024
Carbon neutrality policies are of great importance for the transportation sector. Thus, some issues need to be taken into consideration increase effectiveness carbon in this However, biggest disadvantage these improvements is that they costs. Instead improving a large number factors, it more financially feasible take action on ones important. Nevertheless, there limited studies which priority analysis made factors affecting process. Therefore, main missing part literature new study should weights variables determined. The purpose evaluate industry with novel decision-making model. First, selected indicators evaluated by quantum picture fuzzy row sets-based multi-step wise weight assessment ratio (M-SWARA) technique. Secondly, alternatives ranked. For purpose, multi-objective optimization basis (MOORA) methodology considered sets. motivation making and comprehensive reason behind situation most existing models could not consider causal directions among indicators. Due situation, proposed model created using causality relationships between industry. contribution integrating theory rough This has positive make sensitive evaluations. Additionally, approach criteria so relationship determinants can findings demonstrate infrastructure development important factor effective Cost another critical indicator respect. On other hand, according ranking results, determined reducing traditional fuels zero-carbon essential alternative transportation. It would appropriate companies attach use electric vehicles. In context, government incentives vehicles offered. example, tax reduction may as will provide significant cost advantage.
Language: Английский
Citations
12Sensors, Journal Year: 2024, Volume and Issue: 24(9), P. 2833 - 2833
Published: April 29, 2024
The problem of energy depletion has brought wind under consideration to replace oil- or chemical-based energy. However, the breakdown turbines is a major concern. Accordingly, unsupervised learning was performed using vibration signal power generator achieve an outlier detection performance 97%. We analyzed data through wavelet packet conversion and identified specific frequency band that showed large difference between normal abnormal data. To emphasize these bands, high-pass filters were applied maximize difference. Subsequently, dimensions reduced principal component analysis, giving unique characteristics preprocessing process. Normal collected from farm located in northern Sweden first preprocessed trained long short-term memory (LSTM) autoencoder perform detection. LSTM Autoencoder model specialized for time-series learns patterns detects other as outliers. Therefore, we propose method learning, utilizing signals generators. This will facilitate quick accurate failures provide alternatives depletion.
Language: Английский
Citations
10Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 111790 - 111790
Published: Jan. 1, 2025
Language: Английский
Citations
1Economic Analysis and Policy, Journal Year: 2025, Volume and Issue: 85, P. 2207 - 2218
Published: March 1, 2025
Language: Английский
Citations
1