Article
Computer Science, Artificial Intelligence
Sena Aydogan, Gul E. Okudan Kremer, Diyar Akay
Summary: The study introduces a linguistic summarization approach based on fuzzy sets for describing a realistic complex network of a bike supply chain, calculating the truth degree of generated summaries using fuzzy cardinality-based methods to overcome inherent disadvantages.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Engineering, Environmental
Carolina Calero Preciado, Stewart Husband, Joby Boxall, Gonzalo del Olmo, Victor Soria-Carrasco, Sung Kyu Maeng, Isabel Douterelo
Summary: Intermittent water supplies have a significant impact on biofilm growth and can lead to water quality degradation, especially events lasting more than 6 hours which generate more turbidity responses and hence discolouration risk. Additionally, shorter times of non-water supply may increase the risk of aromatic organic compounds and potential pathogenic microorganisms, highlighting the importance of managing microbial interactions to ensure continued safe water supply.
Article
Computer Science, Artificial Intelligence
Iurii Konovalenko, Andre Ludwig
Summary: Real-time temperature monitoring is crucial in cold pharmaceutical supply chains to prevent product quality deterioration from extreme temperature exposure. A new hybrid k-NN algorithm, based on principles of local similarity and neighborhood homogeneity, outperforms traditional k-NN in accuracy and precision for temperature alarms in pharmaceutical supply chains.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics, Applied
Fernando Chacon-Gomez, M. Eugenia Cornejo, Jesus Medina, Eloisa Ramirez-Poussa
Summary: The use of decision rules allows for reliable extraction of information and inference of conclusions from relational databases, but the concepts of decision algorithms need to be extended in fuzzy environments.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2024)
Article
Engineering, Chemical
Oscar T. Vegas Nino, Fernando Martinez Alzamora, Velitchko G. Tzatchkov
Summary: This paper introduces two new methodologies for water supply system decentralization through distribution network sectorization, implemented in a freely available software tool online. The results show that these methods outperform other proposed methodologies in the literature for decentralizing water supply systems.
Article
Computer Science, Artificial Intelligence
Ali Asghar, Khuram A. Khan, Marwan A. Albahar, Abdullah Alammari
Summary: Supplier selection is a critical decision-making process that directly affects the quality, cost, and reliability of products and services. To deal with uncertainties and vagueness, multi-criteria decision analysis and fuzzy logic have been used to select suppliers, helping organizations make informed decisions and mitigate risks associated with supplier selection.
PEERJ COMPUTER SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Pei-Yi Hao, Jung-Hsien Chiang, Yu-De Chen
Summary: This paper proposes a novel possibilistic classification algorithm using support vector machines (SVMs) to effectively handle uncertain information and improve classification performance. The algorithm aims at finding a maximal-margin fuzzy hyperplane based on possibility theory and solves a fuzzy mathematical optimization problem. The proposed algorithm retains the advantages of fuzzy set theory and SVM theory, and it is more robust for handling outliers. Experimental results demonstrate the satisfactory generalization accuracy and ability to describe inherent vagueness in the given dataset.
Article
Green & Sustainable Science & Technology
Shuo Gao, Ming Kim Lim, Renlu Qiao, Chensi Shen, Chentao Li, Li Xia
Summary: This study proposes a comprehensive framework to explore and understand the failure factors of GSCM in China's SMEs to improve the opportunities of GSCM. Collaboration and support are identified as the most critical perspectives for GSCM, with interrelationships affecting knowledge, technology, and economy perspectives. Critical failure factors include lack of top management support, poor guidance from authorities, difficulty in supplier selection, and inadequate supplier commitment.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2022)
Article
Mathematics
Yu-Cheng Kao, Kao-Yi Shen, San-Ting Lee, Joseph C. P. Shieh
Summary: This study constructed a hybrid decision model for banks using an integrated approach, and found that the blockchain-based Fintech strategy is ideal for a bank in Taiwan. The findings unveiled the complicated relationships among evaluation factors, shedding light on banks' innovation in financial services and benefiting supply chain participants in securing efficient loans.
Article
Computer Science, Interdisciplinary Applications
Lu Wang, Xiaobo Zhang, Guijie Li, Zhenzhou Lu
Summary: Global sensitivity analysis and regional sensitivity analysis are valuable tools for identifying important inputs and simplifying models, but there is limited research on them in the presence of fuzzy uncertainty. A new Global Sensitivity Index (GSI) and Contribution to this CrDF based index (CCI) plot have been proposed to quantify the impact of important inputs on the output under fuzzy uncertainty.
ENGINEERING WITH COMPUTERS
(2022)
Article
Multidisciplinary Sciences
Shahzaib Ashraf, Muhammad Sohail, Razia Choudhary, Muhammad Naeem, Gilbert Chambashi, Mohamed R. Ali
Summary: Due to frequent emergency events causing significant damage to society and the economy, the importance of emergency decision-making has become evident. In such situations, aggregation methods are crucial, especially when dealing with multiple competing criteria. This study introduces new aggregation operators and thoroughly covers their characteristics in the context of spherical hesitant fuzzy soft systems (SHFSS). An algorithm is developed to handle emergency decision-making within the SHFSS framework. The study also extends to evaluation using the Distance from Average Solution method and provides a numerical illustration to validate the proposed work.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Interdisciplinary Applications
Amit Karamchandani, Samir K. Srivastava, Abha, Akhil Srivastava
Summary: This paper proposes a decision-making framework based on blockchain and artificial intelligence for organizations and their supply chains to analyze and validate big data. It has unique features and advantages in application.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Mathematics
Fernando Chacon-Gomez, M. Eugenia Cornejo, Jesus Medina
Summary: This paper investigates different methods for classifying new objects using decision rules in decision-making processes. These methods determine the best possible decision based on various indicators associated with the decision rules.
Article
Medicine, General & Internal
Atiqe Ur Rahman, Muhammad Saeed, Mazin Abed Mohammed, Mustafa Musa Jaber, Begonya Garcia-Zapirain
Summary: The study proposes a novel medical diagnostic decision-making approach by integrating the concepts of fuzzy parameterized fuzzy hypersoft set (Delta-set) and Riesz Summability. The algorithms are validated using real attributes and subattributes of the Cleveland dataset, demonstrating better flexibility and reliability in diagnosing heart-related ailments compared to existing methods.
Article
Management
Ming-Lang Tseng, Thi Phuong Thuy Tran, Kuo-Jui Wu, Raymond R. Tan, Tat Dat Bui
Summary: This study aims to establish a framework to understand the seafood industry in Vietnam and enhance its performance. The research findings highlight the importance of collaboration in the supply chain and lean management in driving economic benefits.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2022)
Article
Environmental Sciences
Shaher H. Zyoud, Daniela Fuchs-Hanusch
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2020)
Article
Environmental Sciences
Georg Arbesser-Rastburg, Daniela Fuchs-Hanusch
Article
Computer Science, Artificial Intelligence
Shaher H. Zyoud, Daniela Fuchs-Hanusch
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2020)
Article
Environmental Sciences
Ariel Gorenstein, Meir Kalech, Daniela Fuchs Hanusch, Sharon Hassid
Article
Green & Sustainable Science & Technology
Shaher H. Zyoud, Ahed H. Zyoud
Summary: Following the outbreak of COVID-19, research in the environmental field has focused on the impacts of the pandemic on air quality, mental health, and economic aspects. Methodologies include cross-sectional studies, evidence-based tools, remote sensing, satellite mapping, geographic information systems, market analysis, and sampling.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2021)
Article
Chemistry, Analytical
Michael Pointl, Daniela Fuchs-Hanusch
Summary: LPWAN technologies offer new possibilities for real-time leak detection in water distribution systems by combining long-distance wireless communication with low power consumption. When compared to GPRS, LPWAN standards like Narrowband IoT, LoRaWAN, and Sigfox provide viable alternatives for leak detection in WDS.
Article
Environmental Sciences
Shaher H. Zyoud, Ahed H. Zyoud
Summary: In recent years, research on Environmental Impact Assessment (EIA) in the Arab world has rapidly developed, with a focus on countries like Egypt, Saudi Arabia, and Tunisia. The utilization of remote sensing, GIS, and other technologies in assessing environmental impacts will be key themes for future research, while strengthening regional experience, increasing funding, and improving capabilities are necessary to further promote EIA research activities.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Environmental Sciences
Anika Stelzl, Michael Pointl, Daniela Fuchs-Hanusch
Summary: This study examined the impacts of climate change on water supply in Austria and proposed a general multiple linear regression model, which performed similarly to other modeling approaches. Using this model to predict future water demand, it was found that peak water demand is expected to increase by 3.5% compared to the reference period.
Article
Engineering, Civil
Sanghoon Jun, Georg Arbesser-Rastburg, Daniela Fuchs-Hanusch, Kevin Lansey
Summary: This paper examines the impact of uncertainties on the calibration of water distribution system (WDS) models. The results show that even with uncertainties, the response surfaces remain smooth and convex, but there are deviations between the best parameter solutions and the true solutions.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
(2022)
Article
Environmental Sciences
Shaher Zyoud
Summary: This study tracked and analyzed research works on intermittent water supply systems (IWSSs) using bibliometric techniques and visual mapping tools. The findings showed certain expectations in terms of productivity, with the United States being the most productive country and Water Switzerland journal being the most productive journal. The study also highlighted concerns related to transitioning to continuous supply, equity, and mitigating health risks associated with IWSSs. The use of artificial intelligence techniques and expert systems was identified as key for future research activities in this field.
Article
Green & Sustainable Science & Technology
Shaher H. Zyoud
Summary: This study provides a comprehensive overview of the implications of COVID-19 on achieving the sustainable development goals (SDGs) outlined in the United Nations' 2030 Agenda, as well as the state of research activities related to COVID-19 and the SDGs. The research found that there is still limited research on the impacts of COVID-19 on SDGs, with only a small percentage of global research productivity dedicated to this topic. The study highlights the significant attention given to the impact of COVID-19 on SDG-3 (good health and well-being) and SDG-13 (climate action), and raises concerns about achieving the SDGs by 2030 in the post-COVID-19 scenarios.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Environmental Sciences
Verena Germann, Florian Borgwardt, Jorg Fischer, Daniela Fuchs-Hanusch, Martin Regelsberger, Gerhard Schubert, Annett Uhmann, Gunter Langergraber
Summary: The Agenda 2030 of the United Nations sets out 17 ambitious Sustainable Development Goals (SDGs), which must be implemented at the national level in a coherent and context-specific manner. The interaction between the SDGs and corresponding measures poses a complex challenge for decision-makers, and research on these interactions can help identify policy options with the greatest impact. This study develops eleven options and 85 measures to advance SDG 6 Targets in Austria and evaluates their effects on a 7-point scale.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Social Sciences, Interdisciplinary
Shaher H. Zyoud, Ahed H. Zyoud
Summary: This paper provides a comprehensive overview of research activities in ESWA since 1990, utilizing bibliometric techniques to characterize research patterns in the journal. Taiwan emerged as the most productive country, with National Cheng Kung University being the most productive institution. Active research topics in ESWA include genetic algorithms, data mining, and neural networks.
Proceedings Paper
Engineering, Civil
Jakim P. Lippacher, David B. Steffelbauer, Georg Arbesser-Rastburg, Daniela Fuchs-Hanusch
WORLD ENVIRONMENTAL AND WATER RESOURCES CONGRESS 2019: HYDRAULICS, WATERWAYS, AND WATER DISTRIBUTION SYSTEMS ANALYSIS
(2019)
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)