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Tolerance framework for robust group multiple criteria decision making

Expert systems with Applications 2022年 208卷

作者： Yang, Yu Lin, Jun Fu, Yelin Huang, George Q. Huang, Weihao Fang, Chao School of Management Xi'an Jiaotong University Xi'an710049 China College of Economics Shenzhen University Shenzhen China Department of Industrial and Manufacturing Systems Engineering The University of Hong Kong Hong Kong

A tolerance framework is developed to address a group multiple criteria ranking problem with indirect preference information, which is referred to as the interaction, importance and tolerance of criteria as well as pairwise comparisons among alternatives and criteria. Choquet integral preference model is employed to capture the interaction, importance and tolerance of criteria, all of which are specific to decision makers (DMs). Some mandatory/sufficient requirements concerning criteria which are global or local, also called the tolerance attitudes of DMs, are quantified as tolerability constraints. Preference disaggregation analysis is extended to solve this type of tolerability constraints for preference elicitation. Confronted with the inconsistency issue (the feasibility of the whole preference constraints translated from indirect preference information), cause oriented strategy and consequence oriented strategy are established by regression-based mixed 0–1 integer linear programs with the objectives of the most credible minimal inconsistent preference constraints and the most credible maximal preference constraints in the context of group decision making. Considering a wide range of the minimal unsatisfied subsets of preference constraints responsible for the inconsistency and the maximum satisfied subsets of preference constraints as a consistent result, to reach a robust decision, stochastic multicriteria acceptability analysis (SMAA)-like simulation analysis is generated to examine the whole instances of compatible preference models in the modified feasible preference polyhedron and compute the result in a probabilistic form. Simulation experiment is conducted to investigate the influence of global tolerance attitudes of DMs on preference elicitation in conservative and radical scenarios. Finally, the application of the proposed approach to a credit ranking of small and medium-sized enterprises (SMEs) and the comparison analysis with objective methods are pr

关键词： Stochastic systems

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Social media-based online entrepreneurship approach on millennials: A measurement of job pursuit intention on multi-level marketing 6

Social media-based online entrepreneurship approach on mille...

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6th Information systems International Conference, ISICO 2021

作者： Nadlifatin, Reny Persada, Satria Fadil Clarinda, Mutiara Handiwibowo, Gogor Arif Laksitowati, Rr Ratih Prasetyo, Yogi Tri Redi, Anak Agung Ngurah Perwira Department of Information System Institut Teknologi Sepuluh Nopember Campus ITS Sukolilo Surabaya60111 Indonesia Department of Business Management Institut Teknologi Sepuluh Nopember Campus ITS Sukolilo Surabaya60111 Indonesia Department of Technology Management Institut Teknologi Sepuluh Nopember Campus ITS Sukolilo Surabaya60264 Indonesia School of Industrial Engineering and Engineering Management Mapúa University 658 Muralla St. Intramuros Manila1002 Philippines Industrial Engineering Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

The present research explores the behavioral perspective of the millennial generation on job pursuit intention on Multi-Level Marketing companies through social media. Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) are used to assess the job pursuit intention. The data were analyzed by Structural Equation Model (SEM). Analysis reveals the strong influence of attitude on job pursuit intention. The result in this research can be used as the theoretical basis that can be very beneficial for MLM companies, investors, and academicians in marketing. Further theoretical and practical suggestions are discussed. © 2021 The Authors. Published by Elsevier B.V.

关键词： Marketing

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Big data in healthcare:Conceptual network structure,key challenges and opportunities

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Digital Communications and Networks 2023年第4期9卷 856-868页

作者： Leonardo B.Furstenaua Pedro Leivas Michele Kremer Sott Michael S.Dohan Jose Ricardo Lopez-Robles Manuel J.Cobo Nicola Luigi Bragazzi Kim-Kwang Raymond Choo Post-Graduate Program in Industrial Engineering Federal University of Rio Grande Do SulPorto Alegre90035-190Brazil University of Santa Cruz Do Sul Av.Independencia 2293Santa Cruz Do SulRSBrazil Business School Unisinos UniversityAv.Dr.Nilo Peçanha 160091330-002Porto AlegreBrazil Faculty of Business Administration Lakehead UniversityThunder BayOntarioCanada Autonomous University of Zacatecas Av.Ramon Lopez Velarde Col.CentroZacatecas98000Mexico Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain York University ON M3J 1P3Canada Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249USA

Big data is a concept that deals with large or complex data sets by using data analysis tools(e.g.,data mining,machine learning)to analyze information extracted from several sources *** data has attracted wide attention from academia,for example,in supporting patients and health professionals by improving the accuracy of decision-making,diagnosis and disease *** research aimed to perform a Bibliometric Performance and Network Analysis(BPNA)supported by a Scoping Review(SR)to depict the strategic themes,thematic evolution structure,main challenges and opportunities related to the concept of big data applied in the healthcare *** this goal in mind,4857 documents from the Web of Science covering the period between 2009 to June 2020 were analyzed with the support of SciMAT *** bibliometric performance showed the number of publications and citations over time,scientific productivity and the geographic distribution of publications and research *** strategic diagram yielded 20 clusters and their relative importance in terms of centrality and *** thematic evolution structure presented the most important themes and how it changes over ***,we presented the main challenges and future opportunities of big data in healthcare.

关键词： Big data Healthcare digitalization Bibliometric Strategic intelligence Co-word analysis SciMAT

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Queue management Priority-Based Traffic engineering Method

Queue Management Priority-Based Traffic Engineering Method

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International Scientific-Practical Conference Problems of Infocommunications Science and Technology

作者： Oleksandr Lemeshko Oleksandra Yeremenko Anatoliy Persikov Maryna Yevdokymenko Amal Mersni Serhii Harkusha V.V. Popovskyy Department of Infocommunication Engineering Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Engineering Computer Sciences and Engineering Program International University of Sarajevo Sarajevo Bosnia and Herzegovina Department of Document Studies and Information Activities in Economic Systems Poltava University of Economics and Trade Poltava Ukraine

The work proposes the improvement of queue management priority-based Traffic engineering method. It is based on the interaction prediction principle to coordinate decisions at various levels. The lower level of calculations is responsible, firstly, for the distribution and aggregation of packet flows between the macro queues and sub-queues organized on the router interface (congestion management task), and, secondly, for the balanced distribution of interface bandwidth among sub-queues, weighted relative to their priorities (resource allocation task). The upper level of the method's calculations is accountable for distributing the interface's bandwidth between macro queues by performing the iterative procedure. The numerical research results of the proposed two-level queue management method confirmed its effectiveness in ensuring high scalability, balanced priority- based distribution of packet flows and interface bandwidth between the macro queues and sub-queues organized on it. The method demonstrated high coordination procedure convergence and the final quality of centralized calculations.

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Implementing Green Infrastructure for Urban Stormwater management: A Systematic Review to Identify Future Challenges for Japan

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SSRN 2023年

作者： Uchiyama, Shun Bhattacharya, Yasmin Nakamura, Hitoshi Course of System Engineering and Science Graduate School of Engineering and Science Shibaura Institute of Technology Fukasaku 307 Minuma-ku Saitama-shi Saitama-ken 330-0073 Japan Department of Planning Architecture and Environmental Systems Shibaura Institute of Technology Fukasaku 307 Minuma-ku Saitama-shi Saitama-ken 330-0073 Japan

In recent years, Green Infrastructure (GI) has been widely advocated as a measure against urban flooding due to urbanization and climate change. Decentralized small-scale GI in urban areas has been widely promoted as a measure for urban stormwater management for more than 20 years, mainly in Europe and the United States, and examples of its practice have gradually emerged in recent years. However, it is still a new concept in Japan and is pending wide-scale implementation. The purpose of this study is to identify the challenges and suggest a process of GI implementation for the purpose of urban stormwater management in Japan. This study consists of two phases: First, key factors and a basic process for GI implementation are identified based on the experiences of some countries (i.e., China, Australia, the United Kingdom, and the United States). Second, by comparing them with the current situation in Japan, we identified the challenges for GI implementation in Japan in the future. As a result, eight key factors, including "quantitative performance analysis", "land use policy/law", and "interdisciplinary approach/ watershed-scale stakeholder collaboration", were identified. Moreover, we propose a basic process for GI implementation with an interdisciplinary approach, which starts with "selection of GI implementation areas", followed by "determination of implementation strategy with technical and financial support to stakeholders", and "long-term operation". The most important part of the process is how to incorporate GI into the existing urban development strategy, taking into account the topographical and climatic characteristics, social challenges, urban planning systems, and existing stormwater management plans. © 2023, The Authors. All rights reserved.

关键词： Climate change

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Waste Valorization from Brazilian Nepheline Syenite Processing as a Strategic Approach to Advancing the Circular Economy

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SSRN 2023年

作者： Santos, Diego Haltiery Rosa, Laura Pereira Alves, Cleidson Rosa Simão, Lisandro Arcaro, Sabrina Klegues Montedo, Oscar Rubem Raupp-Pereira, Fabiano Graduate Program in Materials Science and Engineering University of the Extreme South of Santa Catarina Criciúma88806-000 Brazil Department of Civil Engineering Federal Institute of Santa Catarina Criciúma88813-600 Brazil Research Group on Sustainability and Waste Management Postgraduate Program in Environmental Technology University of Ribeirão Preto Ribeirão Preto14096-900 Brazil Brazil

The growing disparity between the high extraction of natural resources and low use of waste as alternative mineral resources will aggravate the scarcity of natural reserves. Therefore, the current linear economy model must be converted to sustainable economic models, such as the circular economy. To achieve this transition, it is important that waste recovery strategies are implemented with a continuous search for solutions for these materials. Thus, this study investigates the waste from the processing of nepheline syenite stone, to promote its valorization as an alternative mineral resource. The classification, potentiality, quantity/viability and applicability (CPQvA) criteria are used as tools to aid decision-making for the waste valorization. The environmental, physical, chemical, morphological, and durability characteristics of nepheline syenite waste (NSW) are analyzed. The results showed evidence for the substitution of NSW for up to 100% of fine aggregates and 25% of Portland cement in civil construction. Furthermore, NSW yields recoveries of more than 90% of potassium for use in agriculture, and up to 70% of iron ore for use in steelworks. Therefore, the results indicate that NSW is viable for different applications, contributing to industrial symbiosis and a strategy for advancing the circular economy. © 2023, The Authors. All rights reserved.

关键词： Sustainable development

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An Innovative Smart Irrigation Using Embedded and Regression-Based Machine Learning Technologies for Improving Water Security and Sustainability

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IEEE Access 2025年 13卷 100731-100751页

作者： Abdennabi Morchid Abdennacer Elbasri Zahra Oughannou Hassan Qjidaa Rachid El Alami Badre Bossoufi Saleh Mobayen Paweł Skruch LIMAS Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah (SMBA) University Fes Morocco Department of Data Science Mundiapolis University of Casablanca Campus Nouaceur Casablanca Morocco Innovation in Mathematics and Intelligent Systems (IMIS) Laboratory Ibn Zohr University Agadir Morocco Systems and Sustainable Environment Laboratory (SED) Faculty of Engineering Sciences (FSI) Private University of Fez (UPF) Fes Morocco Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Douliu Taiwan Energy Systems Research Center Khazar University Baku Azerbaijan Department of Automatic Control and Robotics AGH University of Science and Technology Kraków Poland

Global agriculture is facing major challenges such as food security, sustainable water management, and the preservation of natural resources. Water scarcity, exacerbated by climate change, requires adopting more efficient agricultural practices. Traditional irrigation systems, often imprecise, contribute to water wastage. The use of embedded systems and machine learning offers a solution for optimizing irrigation according to local conditions and actual crop needs while contributing to food security and environmental sustainability. This study proposes an innovative approach to irrigation management, integrating real-time data and predictive models to improve irrigation efficiency. This study proposes an irrigation system based on embedded systems, using sensors and algorithms to collect and analyze data in order to optimize water management. The system adjusts irrigation levels according to specific crop needs, thus contributing to more sustainable water management. Using ML algorithms like linear regression algorithms to model the relationships between environmental factors and crop water requirements, enabling accurate prediction of required irrigation levels based on data collected by sensors. The use of embedded systems such as the ESP32, combined with temperature, humidity, and water level sensors, has enabled the development of an autonomous and efficient system for collecting data in real-time and processing it for decision-making. The proposed model has an MAE of 0.8434, an RMSE of 0.8434, and a coefficient (R2 Score) of 0.4044, offering soil moisture prediction accuracy. Furthermore, the training time of our model is 0.00253 seconds, while the prediction time is 0.00117 seconds. These results show not only the performance of the proposed model in terms of accuracy but also its computational efficiency, outperforming some of the studies mentioned. The results of the study show a significant reduction in water consumption, with a marked improvement in water

关键词： Climate change Embedded systems Smart agriculture Irrigation Food security Optimization methods Machine learning Machine learning algorithms Sustainable development Water resources Water monitoring Environmental management

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A Model-Driven Approach for Interoperability Among SaaS and DaaS/DBaaS: The MIDAS Case

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SN Computer Science 2022年第4期3卷 1-18页

作者： Mane, Babacar Mascarenhas, Ana Patrícia F. Magalhães Quinteiro, Gustavo Maciel, Rita Suzana Pitangueira Claro, Daniela Barreiro Formalisms and Semantic Applications Research Group (FORMAS) Institute of Computing Federal University of Bahia Av. Milton Santos Ondina Bahia Salvador 40170-110 Brazil Models for Software Engineering (MAtisse) Department of Exact Sciences and Earth State University of Bahia 2555 Silveira Martins St. Cabula Bahia Salvador Brazil Post Graduate Program in Computing and Systems Salvador University 251 Dr. Jose Peroba St. Bahia Salvador Brazil Models for Software Engineering (MAtisse) Institute of Computing Federal University of Bahia Av. Milton Santos Ondina Bahia Salvador 40170-110 Brazil

Cloud Platforms are heterogeneous, and users may face interoperability issues migrating applications or exchanging data among distinct clouds due, for instance, to the lack of standards solutions. Several solutions have been proposed to overcome lock-in situations, and middleware platforms are one of them. A semantic interoperability solution named middleware for Data as a Service (DaaS)/Database as a Service (DBaaS) and Software as a Service (SaaS)—MIDAS has been developed to overcome this lock-in issue. It is an intermediate communication layer to retrieve data from DaaS or DBaaS through a Structured Query Language (SQL) or a Not Only SQL (NoSQL) created at the SaaS level. MIDAS is a platform for software execution, but software development needs support for its entire life cycle. Therefore, we propose the Model drIven Approach for MIDAS (MIAMI), which enables the specification of platform-independent middleware models and their use to generate code on different cloud platforms. MIAMI comprises a Domain-Specific Modeling Language (DSML) that enables middleware models and a transformation specification, which defines how these models can be converted to code. MIAMI offers a strategy for MIDAS specification and code generation phases to help middleware developers’ activities. MIAMI was applied to code generation specifications in Cloud Foundry, Amazon Web Services, OpenShift, and Heroku providers to evaluate our approach. This specification shows MIAMI’s feasibility and points out that MDD is a promising approach to improving cloud interoperability solutions. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Cloud computing Interoperability Metamodel Model-driven development

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The z-directional dc electrical conductivity of carbon nanofiber z-threaded porous cfrp composites manufactured by radial flow alignment technique

The z-directional dc electrical conductivity of carbon nanof...

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International SAMPE Conference and Exhibition 2020

作者： Ranabhat, Bikash Kirmse, Sebastian Johnson, Michael Hsiao, Kuang-Ting University of South Alabama Department of Mechanical Engineering 150 Jaguar Drive Shelby Hall Suite 3130 MobileAL36608 United States Department of Mechanical Engineering United States Systems Engineering Program

The non-conductive polymer matrix impedes carbon fiber's excellent electrical conductivity in the carbon fiber reinforced polymer (CFRP) composites. Due to its low z-directional DC electrical conductivity, CFRP composites has limited application capabilities in lightning strike protection (LSP) and electromagnetic shielding. This research demonstrates the ability to manufacture lightweight and electrically conductive (i.e., z-direction) CNFs z-threaded porous CFRP composite utilizing just 50 % of epoxy used in the traditional composites. In this study, the radial flow alignment technique was used to z-thread carbon nanofibers (CNFs) into the carbon fiber fabric. Experimental results showed the z-directional DC electrical conductivity in the 0.85 wt% CNF z-threaded porous (P-ZT-CFRP) was 21.06 S/m, which is an increase of 778 % and 107 % compared to the traditional composite sample and P-CFRP (without nano-reinforcement) laminate, respectively. © 2020 Soc. for the Advancement of Material and Process engineering. All rights reserved.

关键词： Carbon nanofibers

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Multi-Criteria Fuzzy Portfolio Selection Based on Three-Way Decisions and Cumulative Prospect Theory

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SSRN 2022年

作者： Wang, Xianhe Wang, Bo Li, Tiantian Li, Huaxiong Watada, Junzo Department of Industrial and System Engineering The Hong Kong Polytechnic University Hung Hom999077 Hong Kong School of Management and Engineering Nanjing University Nanjing210093 China Envision Digital Shanghai210000 China Graduate School of Information Production and Systems Waseda University Kitakyushu808-0135 Japan

Compared with traditional two-way decisions, the introduction of a boundary region into the three-way decisions theory makes it possible to reduce decision risk. In this study, we propose a novel three-way decisions model based on cumulative prospect theory and outranking relations. By constructing an outranked set for each alternative and a hybrid multi-criteria decision making matrix, three strategies are proposed by us to design the three-way decisions model. In order to test the effectiveness of the proposed model, we introduce it into a fuzzy multi-period portfolio selection case and design an improved particle swarm optimization as the solution algorithm. Finally, the effectiveness of the algorithm is validated by some test functions and an experiment based on real market data validates the effectiveness of the multi-period portfolio selection model in increasing investment return and reducing risk. © 2022, The Authors. All rights reserved.

关键词： Decision theory

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