Article
Environmental Sciences
Hassan Tavakol-Davani, Michael Violante, Saeed Manshadi
Summary: This multidisciplinary research aims to assess and reduce the probability of utility pole failure caused by flooding through an optimization framework. By utilizing conventional hydrological, hydrostatic, and geotechnical calculations, the flow rates that lead to utility pole overturn can be determined, and the most cost-efficient subterranean pipe network configuration can be created to redirect flood waters. The implementation of this optimization model in different watersheds demonstrated its effectiveness in preventing utility pole failure.
Article
Environmental Sciences
C. Dionisio Perez-Blanco, Laura Gil-Garcia, Pablo Saiz-Santiago
Summary: This paper presents a hierarchical framework that connects hydrologic and economic modules to assess the economic repercussions of strengthening irrigation quotas to achieve minimum environmental flows. Results show that reductions in agricultural water allocations lead to incremental profit and employment losses in irrigated agriculture, particularly during extreme droughts.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Computer Science, Artificial Intelligence
Mehmet Guray Guler, Ebru Gecici, Tugce Koroglu, Emre Becit
Summary: Studied the exam timetabling and supervisor assignment problems in a vocational school, proposed solutions embedded into a decision support system to generate a complete timetable quickly.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Review
Business
Pouya Mohseni, Hedieh Sajedi, Khalid Hussain
Summary: This paper reviews the fields related to gift exchange and gift recommendation systems, proposing a framework based on introduced metrics. It further assesses existing literature on gift recommendation systems and evaluates their adherence to the proposed framework. The contributions of this paper lie in providing a clear understanding of gift exchange practices and presenting a framework for gift recommendation systems.
ELECTRONIC COMMERCE RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Behrouz Alizadeh Mousavi, Cathal Heavey, Chirine Millauer, Zhikang Tian, Hans Ehm
Summary: This article focuses on designing, developing, and testing a prototype Decision Support System (DSS) based on a mathematical model to assist human planners and improve demand fulfillment systems in tight supply situations, specifically in the semiconductor industry. By incorporating digitalization and supporting human intervention, our approach enhances the complex hierarchical supply chain planning systems. The developed mathematical model, applied as a web application decision support tool called the Regional Customer Allocation Support Tool (ReCAST), is shown to effectively support decision-making processes in a real-world context, as demonstrated through a semiconductor case study.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2023)
Article
Environmental Sciences
Vanessa Assumma, Marta Bottero, Elena De Angelis, Julia M. Lourenco, Roberto Monaco, Ana Jacinta Soares
Summary: This paper introduces an integrated evaluation framework to assess the territorial resilience of a socio-ecological system, combining resilience indicators and a mathematical model. The framework is applied to the Douro Valley wine region in Portugal, demonstrating its suitability for landscape and urban planning.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Computer Science, Artificial Intelligence
Pawel Sitek, Jaroslaw Wikarek, Grzegorz Bocewicz, Izabela Nielsen
Summary: One of the key elements in the modern trade and services market is the use of business chain solutions, such as restaurant chains. The development of IT technology and availability of the Internet and mobile technologies have modernized these solutions. Remote ordering and delivery options have become increasingly popular, especially during the pandemic. The development of decision support models and the integration of different approaches have helped optimize customer order processing and delivery.
Review
Computer Science, Interdisciplinary Applications
Fumiya Okubo, Tetsuya Shiino, Tsubasa Minematsu, Yuta Taniguchi, Atsushi Shimada
Summary: In this study, an integrated system is proposed to support learners' reviews. The system uses a review dashboard to recommend adaptive review contents based on individual learners' level of understanding and provide other useful information. Pages of digital learning materials estimated to be insufficiently understood and related webpages are recommended. The experiment showed that the review dashboard was found useful by at least half of the participants for various types of feedback, and it significantly improved learning as indicated by the higher rate of change in quiz scores.
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES
(2023)
Article
Agronomy
Carlos F. Brunner-Parra, Luis A. Croquevielle-Rendic, Carlos A. Monardes-Concha, Bryan A. Urra-Calfunir, Elbio L. Avanzini, Tomas Correa-Vial
Summary: Chile is one of the largest walnut producers and exporters globally, but there is a lack of scientific advice regarding decision support systems in the walnut sector. This study introduces a DSS for walnut processing decisions, aiming to maximize the benefits by considering the quality of raw materials. The implemented DSS in a Chilean walnut exporter resulted in a significant profit increase.
Article
Energy & Fuels
Mingxun Zhu
Summary: This paper analyzes the e-commerce energy regulatory system model based on data mining, discussing the current models of energy regulatory systems at home and abroad. The implementation of the support-vector machine (SVM) algorithm in the model results in satisfactory performance, achieving more than 97% which outperforms most of the latest approaches.
Article
Computer Science, Artificial Intelligence
Qichen Deng, Bruno F. Santos, Wim J. C. Verhagen
Summary: Modern aircraft maintenance involves thousands of components that need regular inspection or replacement. Maintenance planners schedule maintenance checks for each aircraft and associated tasks. This paper introduces a decision support system (DSS) for optimizing maintenance check schedules and task allocation, showing substantial improvements in key performance indicators compared to traditional planning methods.
DECISION SUPPORT SYSTEMS
(2021)
Article
Computer Science, Information Systems
Omer Dogan, Hacer Karacan
Summary: Reviews and reputation scores are crucial for buyers in an e-commerce system, and a privacy-preserving decentralized reputation system using permissioned blockchains is proposed in this work. The use of verifiable credentials ensures authenticity of digital identities and feedback, while smart contracts provide a secure and transparent mechanism for processing feedback and applying business rules. The proposed approach helps reduce identity-related attacks and unfair feedbacks.
Article
Engineering, Electrical & Electronic
Nikolay Yu Ruban, Aleksey A. Suvorov, Mikhail Andreev, Ruslan A. Ufa, Alisher B. Askarov, Alexandr S. Gusev, Bhavesh R. Bhalja
Summary: The transient and unpredictable nature of processes in electric power systems poses challenges for control, especially with the integration of renewable energy sources and flexible AC transmission technology. While automatic control systems simplify solutions, operators still play a crucial role in resolving issues related to system state control. Decision support systems are used to enhance operator efficiency, but existing algorithms may be inoperable in certain cases.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Filipe Dwan Pereira, Luiz Rodrigues, Marcelo Henrique Oliveira Henklain, Hermino Freitas, David Fernandes Oliveira, Alexandra I. Cristea, Leandro Carvalho, Seiji Isotani, Aileen Benedict, Mohsen Dorodchi, Elaine Harada Teixeira de Oliveira
Summary: Programming online judges (POJs) are increasingly used in CS1 classes to provide students with practice and quick feedback. However, selecting problems in POJs can be time-consuming and subjective. This research proposes an intelligent recommender system based on data-driven analysis and automatic topic detection to support CS1 instructors in problem selection.
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES
(2023)
Article
Computer Science, Artificial Intelligence
Yao-Huei Huang, Cheng-Hung Hsieh
Summary: This study proposes an intelligent decision support system to guide the use of parking slots on roadsides in urban areas. The system aims to help drivers find suitable parking slots more efficiently, while also addressing issues such as traffic congestion, vehicle emissions, and illegal parking. The proposed system's architecture reduces installation and maintenance costs and serves as an important foundation for smart cities.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
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)