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Scientometric review on multiple climate-related hazards indices

Science of the Total Environment 2024年 945卷 174004页

作者： Laino, Emilio Paranunzio, Roberta Iglesias, Gregorio School of Engineering and Architecture & Environmental Research Institute MaREI University College Cork Cork Ireland National Research Council of Italy Institute of Atmospheric Sciences and Climate Corso Fiume 4 Torino10133 Italy University of Plymouth School of Engineering Computing and Mathematics Marine Building Drake Circus United Kingdom

As the spectre of climate change looms large, there is an increasing imperative to develop comprehensive risk assessment tools. The purpose of this work is to evaluate the evolution and current state of research on multi-hazard indices associated with climate-related hazards, highlighting their crucial role in effective risk assessment amidst the growing challenges of climate change. A notable gap in cross-regional comparative studies persists, presenting an opportunity for future research to enhance global understanding and foster universal resilience strategies. However, a significant surge in research output is apparent, following key global milestones related to climate change action. The research landscape is shown to be highly responsive to international policy developments, increasingly adopting interdisciplinary approaches that integrate physical, social, and technological dimensions. Findings reveal a robust emphasis on geospatial analysis and the development of various indices that transform abstract climate risks into actionable data, underscoring a trend towards localized, context-specific vulnerability assessments. Based on dataset systematically curated under the PRISMA guidelines, the review explores how prevailing research themes are reflected in influential journals and author networks, mapping out a dynamic and expanding academic community. Moreover, this work provides critical insights into the underlying literature by conducting a thematic analysis on the typology of studies, the focus on coastal areas, the inclusion of climate change scenarios, the geographical coverage, and the types of climate-related hazards. The practical implications of this review are profound, providing policymakers and practitioners with meaningful insights to enhance climate change mitigation and adaptation efforts through the application of index-based methodologies. By charting a course for future scholarly endeavours, this article aims to strengthen the scientific fo

关键词： Climate change

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Reinforcement Learning for Sustainable Business Model Development in Social Entrepreneurship 2

Reinforcement Learning for Sustainable Business Model Develo...

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2nd International Conference Computational and Characterization Techniques in engineering and Sciences, IC3TES 2024

作者： Rathod, Umesh Santoshkumar Thomas, Sanjose A Maruti, Fulsundar Shrikant Balasaheb Kadam, Pratima Jadhav, Harshad Laxman Jamal Bdair, Mohammad Mumbai400081 India Department of Sociology Thevara India Mandalas Arts Commerce & Science College Department of Economics Gramonnati Narayangaon Pune410504 India Rayat Shikshan Sansthas Mahatma Phule Mahavidyalaya Department of Economics Pimpri Pune411017 India Department of Economics Navi Mumbai400703 India University of East School of Architecture Computing and Engineering London United Kingdom

ISBN: (纸本)9798350364699

The purpose of this investigation is to investigate the incorporation of underlying literacy (RL) in the process of developing sustainable business models within the context of social entrepreneurship. Traditional methods of developing business models frequently face difficulties in striking a balance between the social impact and the commercial viability of their ideas. The purpose of this study is to present a new framework that makes use of support vector machine techniques to robustly adapt and optimise business strategies, hence ensuring alignment with sustainability pretensions. By utilising RL methods, social enterprises can simulate functional scripts, gain knowledge from feedback received from the real world, and iterate to improve their models to improve both their social value and their financial performance. The paper demonstrates the potential for RL to address difficult decision-making challenges that are vital in social entrepreneurship. It also guides perpetration and offers practical perspectives on the subject. The investigation reveals, via the use of empirical analysis and case studies, how RL may be used to push further successful and sustainable business practices, which will ultimately contribute to the larger goal of producing a positive social impact. © 2024 IEEE.

关键词： Adaptive Optimization Economic Sustainability Impact Assessment Model Innovation Reinforcement Learning Social Entrepreneurship Sustainable Business Models

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Automatic Anomaly Detection for Swarm Observations

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Journal of Geodesy and Geoinformation Science 2021年第1期4卷 94-108页

作者： Yaxin BI Vyron CHRISTODOULOU George WILKIE Guoze ZHAO Peter NICHOLL Mingjun HUANG Bin HAN Ji TANG School of Computing Faculty of ComputingEngineering and the Built EnvironmentUlster UniversityNewtownabbeyBT367UK School of Architecture and the Built Environment Ulster UniversityNewtownabbeyBT367UK Institute of Geology China Earthquake AdministrationBeijing 100029China

The Swarm satellite mission was launched on 22 November 2013,it is the first European Space Agency’s constellation of three satellites,dedicated to monitoring geomagnetic field *** measurements delivered by the three satellites are very valuable for a range of applications,including the earthquake prediction ***,for more than 5 years,relatively little advancement has been achieved in establishing a systematic approach for detecting anomalies from the satellite measurements for predicting *** paper presents the challenges of developing a pragmatic framework for automatic anomaly detection and highlights innovative features of functional components *** a case study we demonstrate a functionality pipeline of the system in detecting anomalies,and present our solutions to coping with data sparsity and parameter tuning as well as insights into the differences between discovering seismic anomalies from periodic and non-periodic data observed by the Swarm satellites.

关键词： anomaly detection Swarm satellites earthquake prediction study

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Performance Evaluation of Metaheuristic Optimization Techniques in Insulation Problem 8

Performance Evaluation of Metaheuristic Optimization Techniq...

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8th International Conference on Information Technology Trends, ITT 2022

作者： Gunal, Ozen Akpinar, Mustafa Akpinar, Kevser Ovaz Turgutlu Vocational School Manisa Celal Bayar University Department of Computer Programming Manisa Turkey Sakarya University Department of Software Engineering Sakarya Turkey School of Engineering Architecture and Interior Design Amity University Dubai Dubai United Arab Emirates Rochester Institute of Technology Department of Computing Security Dubai United Arab Emirates

ISBN: (数字)9781665487429

ISBN: (纸本)9781665487412

Selection of insulation material and determination of its thickness are the two most important parameters that prevent heat loss. Too much thickness complicates the price and use. The low coefficient of thermal conductivity of the insulation material reduces heat loss and increases the cost. One of the most important factors when determining the material thickness and conductivity coefficient is the price. In this study, two cases were examined under certain conditions, independent of the price. In the first case, the insulation material is determined, whereas the material thickness is determined in the second case. Six different current metaheuristic algorithms were used to calculate the two cases. It has been observed that harris hawks optimization (HHO), salp swarm optimization (SSO), and whale optimization (WO) algorithms determine the global optimum point without any error in determining the targets of the problem while the processing times were short. Overall, it has been seen that all six algorithms can create solutions to heat transfer problems with very low errors. © 2022 IEEE.

关键词： Optimization

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A Unified Approach for Dynamic Optimization of AIoT Stream Processing

A Unified Approach for Dynamic Optimization of AIoT Stream P...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Mouad Rahmouni Ouassim Karrakchou Majdoulayne Hanifi Claudio Savaglio Giancarlo Fortino Mounir Ghogho TICLab College of Engineering & Architecture International University of Rabat Morocco Institute for High-Performance Computing and Networking (ICAR) University of Calabria Italy National Research Council (CNR) of Italy School of Electronic and Electrical Engineering University of Leeds UK

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Artificial Intelligence of Things (AIot) has made Stream Processing (SP) an essential element for data analytics. However, the dynamic nature of AIoT data streams incurs significant challenges in SP systems, especially when real-time data processing is required. While traditional approaches rely on resource scaling to meet the AIoT application requirements, our work explores a complementary approach by optimizing in real-time the configuration of SP systems to balance operational and resource efficiencies with data throughput and latency considerations. At the core of our work is the application of a Q-learning algorithm, enabling dynamic and responsive tuning of the SP system configuration parameters to adapt to the fluctuating demands of real-time data processing. Through empirical testing, our approach’s ability to improve SP efficiency in various data environments is demonstrated, providing insights into its practical application and effectiveness. The research concludes by highlighting the potential of extending this optimization approach to broader real-time data processing scenarios, suggesting avenues for future exploration in SP optimization.

关键词： Q-learning Heuristic algorithms Throughput Real-time systems Internet of Things Global communication Artificial intelligence Optimization Tuning Testing

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One family of 13315 stable periodic orbits of non-hierarchical unequal-mass triple systems

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Science China(Physics,Mechanics & Astronomy) 2021年第1期64卷 108-113页

作者： XiaoMing Li XiaoChen Li ShiJun Liao MOE Key Laboratory of Disaster Forecast and Control in Engineering School of Mechanics and Construction EngineeringJinan UniversityGuangzhou510632China Department of Earth Atmospheric and Planetary SciencesMassachusetts Institute of TechnologyCambridge02139USA School of Civil Engineering and Transportation South China University of TechnologyGuangzhou510641China Department of Engineering Science University of OxfordOxfordOX13PJUK Center of Advanced Computing School of Naval ArchitectureOcean and Civil EngineeringShanghai Jiao Tong UniversityShanghai200240China School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai200240China

The three-body problem can be traced back to Newton in 1687,but it is still an open question *** that only a few periodic orbits of three-body systems were found in 300 years after Newton mentioned this famous *** triple systems are common in astronomy,practically all observed periodic triple systems are hierarchical(similar to the Sun,Earth and Moon).It has traditionally been believed that non-hierarchical triple systems would be unstable and thus should disintegrate into a stable binary system and a single star,and consequently stable periodic orbits of non-hierarchical triple systems have been expected to be rather ***,we report here one family of 135445 periodic orbits of non-hierarchical triple systems with unequal masses;13315 among them are *** with the narrow mass range(only 10-5)in which stable"Figure-eight"periodic orbits of three-body systems exist,our newly found stable periodic orbits have fairly large mass *** find that many of these numerically found stable non-hierarchical periodic orbits have mass ratios close to those of hierarchical triple systems that have been measured with astronomical *** implies that these stable periodic orbits of non-hierarchical triple systems with distinctly unequal masses quite possibly can be observed in *** investigation also suggests that there should exist an infinite number of stable periodic orbits of non-hierarchical triple systems with distinctly unequal *** that our approach has general meaning:in a similar way,every known family of periodic orbits of three-body systems with two or three equal masses can be used as a starting point to generate thousands of new periodic orbits of triple systems with distinctly unequal masses.

关键词： three-body problem non-hierarchical system periodic orbits

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Darcy-Forchheimer mangetized flow based on differential type nanoliquid capturing Ohmic dissipation effects

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Propulsion and Power Research 2023年第3期12卷 443-455页

作者： M.Waqas Yunjie Xu M.Nasir Md Mottahir Alam Amjad Ali Pasha Kashif Irshad Bandar M.Fadhl M.S.Kausar NUTECH School of Applied Science and Humanities National University of TechnologyIslamabad 44000Pakistan Department of Mechanical Engineeing Lebanese American UniversityBeirutLebanon School of Engineering Huzhou UniversityHuzhou 313000China Faculty of Informatics and Computing University Sultan Zainal AbidinBesut Campus22200 BesutTereng-ganuMalaysia Department of Electrical and Computer Engineering King Abdulaziz UniversityJeddah 21589Saudi Arabia Aerospace Engineering Department King Abdulaziz UniversityJeddah 21589Saudi Arabia Interdisciplinary Research Centre for Renewable Energy and Power System(IRC-REPS) Research InstituteKing Fahd University of Petroleum and Minerals(KFUPM)Dhahran 31261Saudi Arabia Mechanical Engineering Department College of Engineering and Islamic ArchitectureUmm Al-Qura UniversityP.O.Box 5555Makkah 21955Saudi Arabia

Hydromagnetic nanoliquid establish an extraordinary category of nanoliquids that unveil both liquid and magnetic *** interest in the utilization of hydromagnetic nanoliquids as a heat transporting medium stem from a likelihood of regulating its flow along with heat transportation process subjected to an externally imposed magnetic *** analysis reports the hydromagnetic nanoliquid impact on differential type(second-grade)liquid from a convectively heated extending *** well-known Darcy-Forchheimer aspect capturing porosity characteristics is introduced for nonlinear *** conditions elaborating heat-mass transportation effect are *** addition,Ohmic dissipation and suction/injection aspects are also a part of this *** analysis is done by implementing the basic relations of fluid *** modeled physical problem is simplified through order *** resulting systems(partial differential expressions)are rendered to the ordinary ones by utilizing the apposite *** solutions are constructed employing homotopy *** and numeric result are addressed comprehensively to elaborate the nature of sundry parameters against physical *** velocity profile is suppressed with increasing Hartmann number(magnetic parameter)whereas it is enhanced with increment in material parameter(second-grade).With the elevation in thermophoresis parameter,temperature and concentration of nanoparticles are accelerated.

关键词： Darcy-Forchheimer magnetized flow Differential type nanoliquid Ohimc dissipation Robin conditions Homotopy algorithm

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Evaluation of Domestic Thermoelectric Cogeneration in Regions with Temperate Climate

Evaluation of Domestic Thermoelectric Cogeneration in Region...

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2021智慧城市与智能建造高端论坛

作者： Xiaofeng Zheng Yuying Yan Hoy-yen Chan Department of Architecture and Built Environment Faculty of EngineeringUniversity of Nottingham School of Built Environment Engineering and ComputingLeeds Beckett University

Research in thermoelectric material and application has been extensively performed due to its various ***,its poor economic viability limits the applications to niche industrial areas due to the low conversion efficiency given by current commercially available thermoelectric *** the absence of fundamental breakthrough in materials performance,its wide and feasible application remains challenging.A thermoelectric cogeneration of electrical power and hot water designed for residential houses is proposed and tests have been carried out on a bench scale prototype to investigate its *** viability has been discussed based on the availability of domestic boiler waste heat and solar *** economic and environmental benefit of employing thermoelectric generators in domestic environment has been evaluated on the basis of experimental studies to the usage in the regions with temperate *** analysis shows that the proposed system concept potentially offers a reasonable cost recovery period(less than 5 years).

关键词： Evaluation of Domestic Thermoelectric Cogeneration in Regions with Temperate Climate

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THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CONSTRUCTION COSTING PRACTICE 39

THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CONSTRUCTION COSTIN...

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39th Annual ARCOM Conference, ARCOM 2023

作者： Ayinla, Kudirat Saka, Abdullahi Seidu, Rafiu Madanayake, Upeksha School of the Built Environment and Architecture London South Bank University Borough Road LondonSE1 0AA United Kingdom School of Built Environment and Computing Leeds Beckett University LeedsLS2 8AG United Kingdom School of Construction Management and Engineering University of Reading Chancellors Way ReadingRG6 6AG United Kingdom

Cost estimation is a crucial process in the construction sector as the efficiency of the overall project cost serves as one metric in determining project success. Prevailing traditional approach suffers from human subjectivity and bias which affect accuracy. With the development and adoption of Artificial Intelligence (AI) such as the use of machine learning (ML) and deep learning (DL) algorithms, the construction industry is experiencing brisk technological change and new ways of working, particularly in terms of cost predictions and estimations. However, the application of AI is still in its infancy and the industry still prioritises traditional cost modelling approaches in determining early estimates. This research explores the application of the various ML methods for costing and assesses their usage and application in the costing practice via an exploratory critical review. Findings indicate that ML algorithms would improve the accuracy and efficiency of costing practice but cannot replace the professionals and data availability. © ARCOM *** rights reserved.

关键词： Computational cost

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Advanced techniques for electricity consumption prediction in buildings using comparative correlation analysis, data normalization, and Long Short-Term Memory (LSTM) networks: A case study of a U.S. commercial building

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Energy Reports 2025年 14卷 56-65页

作者： Kim, Moon Keun Kim, Yang-Seon Fu, Nuodi Liu, Jiying Wang, Junqi Lee, Sanghyuk Srebric, Jelena Department of Built Environment Oslo Metropolitan University OsloN-0130 Norway Mechanical Engineering Department College of Engineering Wichita State University WichitaKS67260 United States School of Architecture Southeast University 2 Sipailou Nanjing210096 China School of Thermal Engineering Shandong Jianzhu University Jinan250101 China School of Computing New Uzbekistan University Tashkent100007 Uzbekistan Department of Mechanical Engineering University of Maryland College ParkMD20742 United States

This study introduces innovative assessment techniques to comprehend the effect of six data normalization methods, implemented through the LSTM algorithm, on predicting electricity consumption in commercial buildings. The focus lies on analyzing the relationship between various normalization process and its integration with LSTM method concerning building electricity consumption. The LSTM model incorporates input nodes from diverse sources, including weather data, plug load data, and occupancy ratio. Six distinct normalization process—Min-Max, Mean, Z-score, Gaussian, VSS, and IQR—are applied to assess the model's evaluation on both training and test datasets. The study found that combining the LSTM method with Min-Max and IQR achieves lower figures, representing better performance and greater stability in comparison to alternative normalization techniques. These results described the critical role of data normalization in improving the performance of LSTM models, highlighting the importance of choosing suitable normalization techniques for specific applications while balancing improved accuracy against computational complexity. Furthermore, the study explores the correlation impact of variations in average input elements, particularly with a 5% increase and decrease in value, on electricity consumption in commercial buildings across different seasons. Plug loads emerge as dominant contributors to electricity consumption across various normalization methods and raw data, with temperature and humidity ratio exerting notable influence in specific seasons. © 2025 The Authors

关键词： Higher order statistics

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