Enhanced Energy Conservation and Response Accuracy of a Pneumatic Control System DOI Creative Commons
Zhonglin Lin, Haitao Wang, Xinglong Zhang

и другие.

iScience, Год журнала: 2024, Номер 27(9), С. 110797 - 110797

Опубликована: Авг. 26, 2024

The energy consumption of pneumatic systems is occupying an increasingly considerable proportion in the industrial systems. However, due to response characteristics actuators, control system generally has a low utilization efficiency. How improve accuracy while reducing remains key problem be solved. In this paper, three-voltage acceleration waveform and its generation method are proposed, circuit designed. A multi-mode switching strategy backstepping sliding mode controller (BSMC) applied. test results show that compared traditional methods, BSMC respectively saves 26.27% air consumption, as well 32.35% valve group power consumption. It also achieves lowest root-mean-square error (RMSE), 4.8421 kPa. All experiments prove proposed can effectively efficiency maintaining high tracking precision.

Язык: Английский

Integrated BIM-IoT platform for carbon emission assessment and tracking in prefabricated building materialization DOI
Xiaojuan Li, Ming Jiang, Chengxin Lin

и другие.

Resources Conservation and Recycling, Год журнала: 2025, Номер 215, С. 108122 - 108122

Опубликована: Янв. 8, 2025

Язык: Английский

Процитировано

3

Global semiconductor supply chain resilience challenges and mitigation strategies: A novel integrated decomposed fuzzy set Delphi, WINGS and QFD model DOI
Md. Abdul Moktadir, Jingzheng Ren

International Journal of Production Economics, Год журнала: 2024, Номер 273, С. 109280 - 109280

Опубликована: Май 13, 2024

Язык: Английский

Процитировано

12

Leveraging Artificial Intelligence for Enhanced Sustainable Energy Management DOI Creative Commons

Swapandeep Kaur,

Raman Kumar, Kanwardeep Singh

и другие.

Journal of Sustainability for Energy, Год журнала: 2024, Номер 3(1), С. 1 - 20

Опубликована: Фев. 4, 2024

The integration of Artificial Intelligence (AI) into sustainable energy management presents a transformative opportunity to elevate the sustainability, reliability, and efficiency systems. This article conducts an exhaustive analysis critical aspects concerning AI-sustainable nexus, encompassing challenges in technological facilitation intelligent decision-making processes pivotal for frameworks. It is demonstrated that AI applications, ranging from optimization algorithms predictive analytics, possess revolutionary capacity bolster energy. However, this not without its challenges, which span complexities socio-economic impacts. underscores imperative deploying manner transparent, equitable, inclusive. Best practices solutions are proposed navigate these effectively. Additionally, discourse extends recent advancements AI, including edge computing, quantum explainable offering insights evolving landscape Future research directions delineated, emphasizing importance enhancing explainability, mitigating bias, advancing privacy-preserving techniques, examining ramifications, exploring models human-AI collaboration, fortifying security measures, evaluating impact emerging technologies. comprehensive aims inform academics, practitioners, policymakers, guiding creation resilient future.

Язык: Английский

Процитировано

11

Fermatean fuzzy sets and its extensions: a systematic literature review DOI Creative Commons
Gülçin Büyüközkan, Deniz Uztürk, Öykü Ilıcak

и другие.

Artificial Intelligence Review, Год журнала: 2024, Номер 57(6)

Опубликована: Май 9, 2024

Abstract The Fermatean Fuzzy Set (FFS) theory emerges as a crucial and prevalent tool in addressing uncertainty across diverse domains. Despite its recognized utility managing ambiguous information, recent research lacks comprehensive analysis of key FFS areas, applications, gaps, outcomes. This study, conducted through the Scientific Procedures Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol, delves into an exploration literature, reviewing 135 relevant articles. documents are meticulously analyzed based on their integrated methodologies, Aggregation Operators (AOs), linguistic sets, extensions. Additionally, thematic analysis, facilitated by Bibliometrix tool, is presented to provide nuanced insights future directions areas within literature. study unveils valuable findings, including integration variables with interval-valued FFS, fostering robust environments dynamic decision-making—a mere glimpse potential research. gaps section further articulates recommendations, offering structured foundation researchers enhance understanding chart studies confidently.

Язык: Английский

Процитировано

10

Industry 4.0 technologies in support of circular Economy: A 10R-based integration framework DOI Creative Commons
Maria Pia Ciano, Mirco Peron, Luigi Panza

и другие.

Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 110867 - 110867

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

Sustainable waste valorization process selection through AHP and advanced Interval Valued Fermatean Fuzzy with integrated CODAS DOI
Yousaf Ayub, Md. Abdul Moktadir, Jingzheng Ren

и другие.

Process Safety and Environmental Protection, Год журнала: 2024, Номер 185, С. 408 - 422

Опубликована: Март 8, 2024

Язык: Английский

Процитировано

8

Sustainability assessment during machining processes: Evidence from the econ-environmental modelling DOI

Hengzhou Edward Yan,

Feng Guo, Baolong Zhang

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 448, С. 141612 - 141612

Опубликована: Март 4, 2024

Язык: Английский

Процитировано

7

Towards green logistics: An innovative decision support model for zero-emission transportation modes development DOI
Md. Abdul Moktadir, Jingzheng Ren

Transportation Research Part E Logistics and Transportation Review, Год журнала: 2024, Номер 189, С. 103648 - 103648

Опубликована: Июль 21, 2024

Язык: Английский

Процитировано

5

Urban resilience assessment from the perspective of cross-media carbon metabolism DOI
Dan Qiao, Shuo Shen, Jiaxuan Chen

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 445, С. 141383 - 141383

Опубликована: Фев. 20, 2024

Язык: Английский

Процитировано

4

Big Data and AI for Smart Maintenance: Literature review on the impact on plants Resilience DOI Open Access
Marco Mosca, Roberto Mosca, Mattia Braggio

и другие.

Procedia Computer Science, Год журнала: 2025, Номер 253, С. 1959 - 1971

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0