Article
Automation & Control Systems
Victor Semedo de M. Siqueira, Marco Antonio S. L. Cuadros, Celso Jose Munaro, Gustavo M. de Almeida
Summary: This paper presents a fuzzy logic-based system for preventing stuck pipe, which can identify early signs of stuck pipe and avoid its occurrence. By analyzing special features and applying machine learning techniques, the system shows high effectiveness in predicting stuck pipe and can avoid more than 92% of stuck cases.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Review
Energy & Fuels
Kunal Sandip Garud, Simon Jayaraj, Moo-Yeon Lee
Summary: This article reviews the application of artificial intelligence techniques in solar photovoltaic systems, focusing on design, modeling, fault detection, and output prediction. A total of 122 articles from 2009 to 2019 are analyzed, showing the suitability and reliability of ANN, FL, GA, and hybrid models for accurate prediction of solar radiation and system performance characteristics.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Environmental Sciences
Shahryar Sarabi, Qi Han, Bauke de Vries, A. Georges L. Romme, Dora Almassy
Summary: Deriving knowledge from past experiences is crucial for the successful adoption of NBS. However, extracting knowledge from the vast amount of information provided by repositories is challenging. This paper introduces an expert system called NBS-CBS, which combines a black-box artificial neural networks model with a white-box case-based reasoning model to provide intelligent, adaptive, and explainable recommendations and information for NBS planning and design.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Yu-Cheng Wang, Toly Chen
Summary: This study reviews existing XAI techniques for explaining GA applications in job scheduling and proposes several novel XAI techniques to address existing problems. The proposed methodology is able to handle high-dimensional data and visualize the contribution of feasible solutions, satisfying the requirements for an effective XAI technique in explaining GA applications in job scheduling. Additionally, the methodology can be extended to explain other evolutionary AI applications in job scheduling.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Thermodynamics
Mahyuddin K. M. Nasution, Marischa Elveny, Rahmad Syah, Iman Behroyan, Meisam Babanezhad
Summary: This study investigates the efficiency of using AI algorithms, specifically the genetic algorithm-based fuzzy inference system (GAFIS), for reducing computational time in CFD modeling. The results show that GAFIS performs well in predicting pressure, although it has longer prediction times compared to other methods.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Energy & Fuels
Na Xiao, Bai Peng, Xin Li, Jia Wu, Jing Lou, Yu Si
Summary: Power grid fault disposal is of great significance in guiding the efficient and orderly emergency work of power grid accidents. The use of knowledge graph technology can extract, express, and manage fault disposal information, as well as assist dispatchers in fault handling, improving the power grid's emergency handling capacity and dispatching intelligence level.
Article
Chemistry, Medicinal
Juraj Mavracic, Callum J. Court, Taketomo Isazawa, Stephen R. Elliott, Jacqueline M. Cole
Summary: The article introduces a framework for automated populating ontologies, enabling direct extraction of a larger group of properties linked by a semantic network. Exploiting data-rich sources, a new model concept is presented for data extraction of chemical and physical properties. With automatically generated parsers for data extraction and forward-looking interdependency resolution, the power of the approach is illustrated through automatic extraction of a crystallographic hierarchy.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Chemistry, Analytical
Hugo Torres-Salinas, Juvenal Rodriguez-Resendiz, Edson E. Cruz-Miguel, L. A. Angeles-Hurtado
Summary: This study implements a position controller based on fuzzy logic on a real platform, using genetic algorithms to optimize the fuzzification of input variables. Experimental results show that the proposed controller performs better than similar techniques in various scenarios.
Review
Computer Science, Interdisciplinary Applications
Ashutosh Sharma, Alexey Tselykh, Elizaveta Podoplelova, Alexander Tselykh
Summary: This article provides an adaptive review and analysis of different knowledge-oriented methods for establishing Fuzzy Cognitive Maps (FCM) based Causal Inference Relations in various domains. It introduces the progress of artificial intelligence-based methodologies in the field and presents a new ensembled-FCM approach with performance evaluation. The article also categorizes existing techniques and outlines potential research directions in the domain.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Review
Computer Science, Interdisciplinary Applications
Ashutosh Sharma, Alexey Tselykh, Elizaveta Podoplelova, Alexander Tselykh
Summary: This article contributes to the field of casual relations by providing an adaptive review of different knowledge-oriented methods for the establishment of Fuzzy Cognitive Maps based Causal Inference Relations. It introduces artificial intelligence-based methodologies and compares their performance. The article also presents an ensembled-FCM based approach and evaluates its performance parameters.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Alessandro Boaro, Jakub R. Kaczmarzyk, Vasileios K. Kavouridis, Maya Harary, Marco Mammi, Hassan Dawood, Alice Shea, Elise Y. Cho, Parikshit Juvekar, Thomas Noh, Aakanksha Rana, Satrajit Ghosh, Omar Arnaout
Summary: Accurate segmentation and volumetric assessment of brain meningiomas are crucial for clinical practice. Fully-automated algorithms can improve accuracy, efficiency, and reduce inter-user variability. Previous research mainly focused on segmentation tasks and lacked evaluation of deep learning solutions in clinical practice.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Artificial Intelligence
You Cao, Zhijie Zhou, Changhua Hu, Wei He, Shuaiwen Tang
Summary: This article systematically summarizes the interpretability characteristics of the belief rule base (BRB) expert system and proposes four interpretability criteria to ensure its interpretability in optimization. An improved optimization algorithm with interpretability constraints derived from the criteria is developed to establish an interpretable BRB. A case study on the health state evaluation of aerospace relay demonstrates the effectiveness of the proposed method.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Business
Sydney Chinchanachokchai, Pipat Thontirawong, Punjaporn Chinchanachokchai
Summary: This research investigates the impact of consumer knowledge on the performance and evaluation of user-based collaborative filtering and content-based recommendation systems. Results indicate that expert consumers prefer user-based collaborative filtering systems, while there is no significant preference difference between the two systems among novice consumers.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2021)
Article
Engineering, Industrial
Yong Jin Suh, Jin Young Choi
Summary: The research focuses on analyzing and dispersing congested material flows in the spine-structure Fab of S Electronics in Korea caused by AMHS. It suggests an efficient Fab facility layout determination method using genetic algorithm, showing superiority in reducing overall distance of congested material handling and alleviating traffic congestions. This method is expected to be helpful in solving Fab process layout problems in the actual industrial field.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Zhaoyu He, Weimin Guo, Peng Zhang
Summary: Capable of storing and redistributing energy, thermal energy storage (TES) shows promising applicability in energy systems. Artificial intelligence (AI) techniques are gradually playing an important role in the intelligent design, optimization, and control of TES systems. This review summarizes that AI-based prediction and optimization models can accurately estimate and optimize the performance of TES systems. However, limitations of AI techniques include the inability to unveil unknown physical mechanisms and the lack of comprehensive performance databases.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Automation & Control Systems
George Charalambous, Sarah R. Fletcher, Philip Webb
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2017)
Editorial Material
Engineering, Manufacturing
Ashutosh Tiwari, Phil Webb, Vinayak Prabhu
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2018)
Article
Computer Science, Interdisciplinary Applications
Gilbert Tang, Phil Webb, John Thrower
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2019)
Article
Engineering, Aerospace
Pablo Coladas Mato, Philip Webb, Yigeng Xu, Daniel Graham, Andrew Portsmore, Edward Preston
AEROSPACE SCIENCE AND TECHNOLOGY
(2019)
Article
Materials Science, Composites
Amit Ramji, Yigeng Xu, Mehdi Yasaee, Marzio Grasso, Philip Webb
COMPOSITES SCIENCE AND TECHNOLOGY
(2020)
Article
Engineering, Multidisciplinary
Seemal Asif, Philip Webb
Summary: This paper aims to study the kinematics of a manipulator using the Comau NM45 Manipulator with a spherical wrist. Pieper's approach is employed to analyze the inverse kinematics of the robot, reducing the complexity of the problem. Mathematical solutions based on D-H parameters are provided, showing that the model accurately follows the motion trajectory of the manipulator.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Materials Science, Composites
Amit Ramji, Yigeng Xu, Marzio Grasso, Mehdi Yasaee, Philip Webb
Summary: The experimental study found that the delamination resistance of 5-harness satin woven laminates is influenced by both interfacial fiber orientation and veil density, with the 90/45 fiber orientation bias exhibiting the greatest resistance, while increasing veil density has limited additional benefits on resistance enhancement.
COMPOSITES SCIENCE AND TECHNOLOGY
(2021)
Article
Engineering, Aerospace
Chao You, Mehdi Yasaee, Shun He, Daqing Yang, Yigeng Xu, Iman Dayyani, Hessam Ghasemnejad, Shijun Guo, Phil Webb, James Jennings, Giovanni Federico
Summary: This study presents a FEM-based preliminary structural sizing method for a single-aisle wing box structure. Various load cases representing typical aircraft manoeuvres, engine loads, landing and ground handling conditions are considered. The sensitivity analysis shows the importance of considering buckling and fatigue constraints, aircraft rolling loads, engine loads, and landing loads in sizing.
AEROSPACE SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Mechanical
Amit Ramji, Yigeng Xu, Mehdi Yasaee, Marzio Grasso, Philip Webb
Summary: Experimental results show that using veil interleaving in CFRP laminates can reduce and shift damage location, impacting stiffness, with differences observed after the Delamination Threshold Load (DTL). This method also achieves a smoothing effect in impact force history and provides important insights into damage characteristics.
INTERNATIONAL JOURNAL OF IMPACT ENGINEERING
(2021)
Article
Robotics
Matthew Story, Phil Webb, Sarah R. Fletcher, Gilbert Tang, Cyril Jaksic, Jon Carberry
Summary: The study finds that the speed and proximity setting of an industrial robot arm can impact a person's workload, but their effect on trust is not significant. It highlights the importance of considering these factors in the development and design of collaborative work cells.
INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS
(2022)
Article
Mechanics
Qing Qin, Iman Dayyani, Phil Webb
Summary: This paper introduces a novel cylindrical metamaterial with zero Poisson's ratio in two different directions. The authors present detailed CAD modelling of curved Fish-Cells for numerical and experimental analysis. High-fidelity finite element models are developed to investigate the mechanical behavior of the cylindrical Fish-Cells metamaterial. Experimental analysis is performed to validate the numerical simulations. Furthermore, the buckling and modal behaviors of the cylindrical Fish-Cells metamaterial are studied and compared with equivalent shell models.
COMPOSITE STRUCTURES
(2022)
Article
Computer Science, Information Systems
Seemal Asif, Philip Webb
Summary: In the aerospace industry, where high variety and low volume manufacturing are common, the use of robots for automation is crucial. This study identifies the challenges of robot errors and proposes solutions for dynamic, real-time error correction and compensation.
APPLIED SYSTEM INNOVATION
(2022)
Article
Robotics
Gilbert Tang, Phil Webb
JOURNAL OF ROBOTICS
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
S. R. Fletcher, P. Webb
Article
Engineering, Aerospace
David Judt, Kevin Forster, Helen Lockett, Craig Lawson, Philip Webb
SAE INTERNATIONAL JOURNAL OF AEROSPACE
(2016)
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)
