Article
Automation & Control Systems
Kai Zhang, Gary G. Yen, Zhenan He
Summary: In this article, a recursive evolutionary algorithm EvoKnee(R) is proposed to directly search for global knee solutions and multiple local knee solutions using the minimum Manhattan distance approach, instead of a large number of Pareto optimal solutions. Unlike traditional approaches, only nondominated solutions in rank one are preserved in each generation, reducing computational cost and allowing quick convergence to knee solutions.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Computer Science, Artificial Intelligence
Zhenan He, Gary G. Yen, Jinliang Ding
Summary: A novel knee-based decision-making method is proposed to search for solutions of interest from a large number of solutions on the Pareto front, ensuring the performance of these solutions approximates as much as possible the whole Pareto front. Additionally, a new visualization approach is developed to provide information about the shape, location, possible bulge, convergence degree, and distribution of solutions on MaOPs.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Public, Environmental & Occupational Health
Jeffrey M. Keisler, Igor Linkov
Summary: Recent guidelines for risk-informed decision making provide a standard for incorporating probabilistic risk models with other considerations, but quantifying risk is difficult when threats, vulnerabilities, and consequences are highly uncertain. Decision making informed by risk (DMIR) can be used as a flexible approach that combines risk and decision analytics. Multi-criteria decision analysis (MCDA) is commonly used as a basis for DMIR to accommodate varying levels of analytical detail.
Article
Engineering, Marine
Mohamed Shehata, Mohamed Abdelnaeem, Ossama Mokhiamar
Summary: This study proposes a novel multiple-criteria decision-making method for solving the multi-objective optimization problem of tuned mass dampers (TMD) applied to marine structures. Non-dominated TMD tuning parameters are found using NSGA-II, and the decision-makers' preferences are assessed using AHP and TOPSIS. Numerical simulations and analysis experiments demonstrate the efficiency of this method in selecting the best solution in various design scenarios.
Article
Thermodynamics
Daniele Lerede, Giuseppe Pinto, Mirko Saccone, Chiara Bustreo, Alfonso Capozzoli, Laura Savoldi
Summary: Energy system models based on the TIMES framework are used to evaluate the sensitivity of the European energy system's long-term evolution and assess alternative optimal configurations through Stochastic Multicriteria Acceptability Analysis. The results show that high penetration of electric vehicles is favored by economic, environmental, and energy-related priorities.
Article
Computer Science, Artificial Intelligence
Yuanxiang Dong, Xiaoting Cheng, Zeshui Xu, Weijie Chen, Hongbo Shi, Ke Gong
Summary: This paper proposes an approach to solve the preference problem in multicriteria group decision making using probabilistic linguistic term sets (PLTSs). By presenting a belief interval interpretation of PLTSs and two methods of belief interval measure, as well as constructing a visual algorithm based on Dempster's rule of combination and graph theory, the preference problem in MCGDM is effectively addressed. An illustrative example is provided to demonstrate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Forestry
Esther Ortiz-Urbina, Luis Diaz-Balteiro, Marta Pardos, Jacinto Gonzalez-Pachon
Summary: The correct aggregation of stakeholders' preferences is crucial in solving natural resource problems. This study analyzes and compares the importance weights of stakeholder groups using pairwise comparison matrices and the voting power notion. The results show different weight values and scenarios, and the influence of control parameter values on similarity of results is observed.
Article
Physics, Multidisciplinary
Amy E. Turner, Cameron W. Johnson, Pieter Kruit, Benjamin J. McMorran
Summary: In this experiment, interaction-free measurements with electrons were successfully demonstrated using a novel electron Mach-Zehnder interferometer. The electron interferometer utilized in this study offers flexibility, high contrast, tunability, and scanning capabilities for imaging, achieving a measurement efficiency of 14 +/- 1%. The implementation of this quantum protocol in electron imaging paves the way for interaction-free electron microscopy.
PHYSICAL REVIEW LETTERS
(2021)
Article
Automation & Control Systems
Enrique Herrera-Viedma, Ivan Palomares, Cong-Cong Li, Francisco Javier Cabrerizo, Yucheng Dong, Francisco Chiclana, Francisco Herrera
Summary: The article provides an overview of fuzzy and linguistic decision-making trends, studies, methodologies, and models developed in the last 50 years. It discusses core decision-making frameworks and new complex decision-making frameworks that have emerged in recent years. The challenges associated with these frameworks and key guidelines for future research in the field are highlighted.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Review
Computer Science, Artificial Intelligence
M. A. Alsalem, A. H. Alamoodi, O. S. Albahri, K. A. Dawood, R. T. Mohammed, Alhamzah Alnoor, A. A. Zaidan, A. S. Albahri, B. B. Zaidan, F. M. Jumaah, Jameel R. Al-Obaidi
Summary: This study explores the lack of decision mechanisms during the COVID-19 outbreak and presents a comprehensive review and analysis of the application of different MCDM theories in complex case studies related to COVID-19. The research discusses the development and evaluation directions of MCDM in COVID-19, and utilizes Bibliometrics for analysis and visualization. The study highlights important facts and percentages related to the application of MCDM theory in COVID-19 studies. A recommended MCDM theory solution is proposed as a future direction in COVID-19 studies. This study provides an overview of the current status of MCDM evaluation and development methods, motivating researchers to harness the potential of MCDM in accurate decision-making for different fields against COVID-19.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Multidisciplinary Sciences
O. S. Albahri, A. A. Zaidan, A. S. Albahri, H. A. Alsattar, Rawia Mohammed, Uwe Aickelin, Gang Kou, FM. Jumaah, Mahmood M. Salih, A. H. Alamoodi, B. B. Zaidan, Mamoun Alazab, Alhamzah Alnoor, Jameel R. Al-Obaidi
Summary: This study proposes a novel homogeneous Pythagorean fuzzy framework for distributing COVID-19 vaccine doses by integrating a new formulation of the PFWZIC and PFDOSM methods. The findings of this study are expected to ensure equitable protection against COVID-19 and help accelerate global vaccine progress.
JOURNAL OF ADVANCED RESEARCH
(2022)
Article
Ergonomics
Hamad Rashid, Salaheddine Bendak
Summary: Human fatigue directly contributes to aviation accidents, but selecting the most suitable fatigue measurement methods for each aviation operator poses a challenge. A new multicriteria decision model was proposed based on aviation safety literature and expert opinions, which was found to be sensitive to user preferences and effective through scenario-based simulations.
INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS
(2022)
Review
Computer Science, Artificial Intelligence
Mohammed Assim Alsalem, Rawia Mohammed, Osamah Shihab Albahri, Aws Alaa Zaidan, Abdullah Hussein Alamoodi, Kareem Dawood, Alhamzah Alnoor, Ahmed Shihab Albahri, Bilal Bahaa Zaidan, Hassan Alsattar, Mamoun Alazab, Fawaz Jumaah
Summary: This study focuses on analyzing the rise of MADM techniques in combating COVID-19 by presenting a systematic literature review of state-of-the-art applications. It emphasizes the current standpoint and opportunities for MADM in the midst of the COVID-19 pandemic, promoting additional efforts towards understanding and providing new potential future directions in this study field.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Mathematics
Rui Yong, Jun Ye, Shigui Du
Summary: This study proposes trapezoidal neutrosophic Z-numbers (TrNZNs), their basic operations, and aggregation operators, along with establishing an MDM method for solving MDM problems with TrNZN information. The research demonstrates that the established approach not only makes assessment information continuous and reliable, but also strengthens decision rationality and efficiency in the setting of TrNZNs.
JOURNAL OF MATHEMATICS
(2021)
Article
Social Sciences, Interdisciplinary
Pinar Mic, Z. Figen Antmen
Summary: The study focuses on supporting the new university location decision in a region in Turkey with high population density but relatively low number of universities, applying various multicriteria decision-making techniques. The results obtained are intended to aid decision makers in making informed choices.
Article
Engineering, Multidisciplinary
Wen-Jun Cao, Shanli Zhang, Numa J. Bertola, I. F. C. Smith, C. G. Koh
Summary: The study uses a model updating strategy to identify the size of wheel flats, and proposes a model-falsification approach that explicitly includes uncertainties, which is essential for accurately evaluating the wheel-flat size.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Computer Science, Interdisciplinary Applications
Nizar Bel Hadj Ali, Ziyun Kan, Haijun Peng, Landolf Rhode-Barbarigos
Summary: This paper investigates the importance of considering sliding-induced friction in the static analysis of tensile structures and proposes an improved approach. Through several examples, it demonstrates the significant impact of friction on the mechanical behavior of structures, and shows that the proposed formulations do not affect the computational time for static analyses.
ENGINEERING WITH COMPUTERS
(2021)
Article
Computer Science, Artificial Intelligence
Sai G. S. Pai, Ian F. C. Smith
Summary: This paper explores the optimal performance of civil infrastructure through a validated methodology combining physics-based models with monitoring data to support asset managers in extrapolating current performance for future needs. Three model-based data-interpretation methods are compared using a full-scale case study, with validation conducted using cross-validation and joint-entropy metric. Accurate identification of structural behavior allows for predictions of remaining fatigue life of the bridge.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Sai G. S. Pai, Masoud Sanayei, Ian F. C. Smith
Summary: Using physics-based models for structural identification and subsequent prediction can enhance civil infrastructure asset-management decision-making. A novel model-class selection method is proposed to obtain computationally optimal and identifiable model classes, improving the efficiency and effectiveness of interpreting monitoring information. The model-based clustering method helps select an identifiable and computationally efficient model class, achieving good application results in engineering practice.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2021)
Article
Engineering, Civil
Numa J. Bertola, Sai G. S. Pai, Ian F. C. Smith
Summary: Managing existing civil infrastructure is challenging due to changing requirements and aging, but sensor measurements can enhance understanding of structural behavior. Designing monitoring systems involves selecting the most appropriate model class for optimal sensor placement. Adjusting sensor configurations can reduce sensor numbers without compromising information gain.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2021)
Article
Engineering, Civil
Wen-Jun Cao, C. G. Koh, I. F. C. Smith
Summary: The development of new materials and advanced technologies has led to longer, taller, and lighter footbridges with increasing aesthetic requirements. Vibration serviceability often governs the design of footbridges due to their susceptibility to vibrations. This paper utilizes the EDMF method to assess vibration serviceability of two pedestrian bridges and highlights its accuracy in comparison to other data interpretation methodologies.
JOURNAL OF BRIDGE ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Ze Zhou Wang, Numa Joy Bertola, Siang Huat Goh, Ian F. C. Smith
Summary: The paper proposes a hierarchical algorithm based on a joint-entropy objective function to systematically evaluate the knowledge gained from wall deflections measured by inclinometers at an excavation site. By corroborating the algorithm's predictions with back analysis results, it is shown that the method can aid in the judicious selection of field response measurements to obtain useful knowledge of material parameter values. The hierarchical algorithm allows for predictions to be made at the early stages of a project, even before the commencement of site activities, without the need for actual measurements.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Slah Drira, Sai G. S. Pai, Yves Reuland, Nils F. H. Olsen, Ian F. C. Smith
Summary: Occupant detection and recognition in buildings support functional goals such as security, healthcare, and energy management. Traditional sensing approaches like smartphones and cameras are privacy invasive, leading to the development of a non-intrusive technique using floor-vibration measurements induced by footstep impacts. Challenges such as ambient noise and overlapping signals from multiple occupants walking simultaneously affect the accuracy of occupant detection using footstep-induced vibrations.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Engineering, Civil
Imane Bayane, Sai G. S. Pai, Ian F. C. Smith, Eugen Bruhwiler
Summary: A new methodology is presented to evaluate fatigue safety of existing bridges by conducting onsite measurements and interpreting data using physics-based behavior models. The methodology combines nondestructive measurements with structural models to develop feasible models accurately describing structural behavior. This methodology is useful for evaluating nonaccessible elements of civil infrastructure and making decisions related to actions such as strengthening and retrofit.
JOURNAL OF BRIDGE ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Alberto Costa, Ze-Zhou Wang, Siang Huat Goh, Ian F. C. Smith
Summary: This research proposes a new framework that combines Error-Domain Model Falsification (EDMF) and an optimization algorithm to efficiently identify soil parameter values in excavation. Experimental results on a excavation site in Singapore demonstrate that the new framework is robust, accurate, and has the potential to improve current practice.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Mechanical
Slah Drira, Ian F. C. Smith
Summary: This paper presents a non-intrusive and inexpensive method for occupant detection and tracking in buildings using floor-vibration measurements. The method outperforms existing threshold-based methods and successfully distinguishes footsteps from spurious events. It uses support vector-machine classifiers and structural-mechanics models to detect occupants and track their movements. The framework has been tested and validated on two full-scale case studies, demonstrating its utility for buildings with sparse sensor configurations measuring floor vibrations.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Materials Science, Composites
Nada Ben-Ltaief, Franck NGuyen, Toufik Kanit, Abdellatif Imad, Nizar Bel-Hadj-Ali
Summary: Seashell waste, composed of calcium carbonate and a complex microstructure, is increasingly used as a bio-filler for composite materials. This study investigates the effect of particle size, shape, and inter-phase properties on the elastic properties of seashell particle-reinforced bio-composites. The results show that the addition of seashell particles significantly improves the elastic properties of the composites, while seashell particle morphology and inter-phase structure have a negligible effect. However, the inter-phase thickness has a considerable impact on the elastic properties of the bio-composites.
JOURNAL OF COMPOSITE MATERIALS
(2023)
Article
Engineering, Civil
Numa Bertola, Ze Zhou Wang, Wen-jun Cao, Ian F. C. Smith
Summary: Information collected through sensor measurements has the potential to improve knowledge of complex-system behavior, leading to better decisions related to system management. This study presents a methodology for selecting informative measurements within large data sets for a given model-updating task, which significantly refines data sets and improves data-interpretation efficiency.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2023)
Article
Construction & Building Technology
Soufien Moula, Amor Ben Fraj, Thomas Wattez, Marwen Bouasker, Nizar Bel Hadj Ali
Summary: This paper discusses an innovative approach for developing a more sustainable Ultra-High Performance Concrete (UHPC) using ground granulated blast furnace slag (GGBS). Partially replacing ordinary Portland cement (OPC) with GGBS improves workability, promotes cement hydration, and accelerates setting. Finer GGBS particles result in a greater acceleration of setting and hydration. A more sustainable UHPC with reduced shrinkage has been successfully produced by incorporating a high level of superfine slag.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Construction & Building Technology
Soufien Moula, Amor Ben Fraj, Thomas Wattez, Marwen Bouasker, Nizar Bel Hadj Ali
Summary: This study investigates the possibility of formulating low-carbon UHPC by replacing cement with ground granulated blast furnace slag (GGBS). The results show that reducing silica fume content allows for the production of UHPC with satisfactory mechanical properties. The incorporation of a certain percentage of GGBS accelerates the hydration process and improves compressive strength, while a high level of slag dilutes the mixture and decreases strength. Moreover, the use of superfine slag instead of silica fume results in high strength UHPC. The evaluation also indicates that the UHPC with superfine slag has a low carbon index but a higher cost.
JOURNAL OF BUILDING ENGINEERING
(2023)