Journal of the Asia Pacific Economy, Год журнала: 2024, Номер unknown, С. 1 - 28
Опубликована: Июль 8, 2024
Язык: Английский
Journal of the Asia Pacific Economy, Год журнала: 2024, Номер unknown, С. 1 - 28
Опубликована: Июль 8, 2024
Язык: Английский
The Science of The Total Environment, Год журнала: 2023, Номер 906, С. 167536 - 167536
Опубликована: Окт. 2, 2023
Язык: Английский
Процитировано
42Journal of Cleaner Production, Год журнала: 2024, Номер 449, С. 140842 - 140842
Опубликована: Фев. 9, 2024
Язык: Английский
Процитировано
24The Science of The Total Environment, Год журнала: 2024, Номер 916, С. 170210 - 170210
Опубликована: Янв. 20, 2024
Язык: Английский
Процитировано
22Economic Analysis and Policy, Год журнала: 2024, Номер 83, С. 42 - 59
Опубликована: Июнь 12, 2024
Язык: Английский
Процитировано
14Advances in civil and industrial engineering book series, Год журнала: 2024, Номер unknown, С. 136 - 165
Опубликована: Июнь 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.
Язык: Английский
Процитировано
14Renewable Energy, Год журнала: 2024, Номер 232, С. 121108 - 121108
Опубликована: Июль 31, 2024
Язык: Английский
Процитировано
14IEEE Transactions on Engineering Management, Год журнала: 2024, Номер 71, С. 7681 - 7700
Опубликована: Янв. 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.
Язык: Английский
Процитировано
12Sensors, Год журнала: 2024, Номер 24(9), С. 2833 - 2833
Опубликована: Апрель 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.
Язык: Английский
Процитировано
10Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 111790 - 111790
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1Economic Analysis and Policy, Год журнала: 2025, Номер 85, С. 2207 - 2218
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
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