Article
Thermodynamics
Hao-ran Wang, Tian-tian Feng, Wei Xiong
Summary: This paper proposes a multi-agent transaction model of distributed energy based on blockchain. By analyzing the transaction mode and process, a multi-agent dynamic Stackelberg game is launched to solve the time of use tariff bidding strategy problem. The obtained results reveal the crucial role of distributed energy in carbon neutral energy supply.
Article
Energy & Fuels
Bo Li, Xu Li, Qingyu Su
Summary: This paper introduces the P2G technology to construct a multi-energy complementary integrated energy system and proposes four potential game planning models using game theory and particle swarm optimization analysis. It is found that the synergistic response of hydrogen and methane in the alliance cooperative game mode has significant advantages.
Review
Automation & Control Systems
Jun Tang, Gang Liu, Qingtao Pan
Summary: Swarm intelligence algorithms are a subset of artificial intelligence that has gained popularity for solving optimization problems and has been widely utilized in various applications. This review summarizes the most representative swarm intelligence algorithms and their successful applications in engineering fields, providing insights into future trends and prospects for development.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Computer Science, Information Systems
Mingxiang Guan, Zhou Wu, WeiGuo Yang, Bin Guo, Xuemei Cao, Hanying Chen
Summary: The future communication network will consist of various networks, enabling a distributed air, space, and sea integrated global intelligent network. This system combines the advantages of high altitude platform stations (HAPS) communication system with satellite and land communication systems, while avoiding their disadvantages. Artificial intelligence technology is used to establish a mathematical model of the wireless communication network, train and continuously optimize the model, and adjust the model parameters according to the network changes. The anti-interference algorithm based on particle swarm optimization is introduced in this paper to address the interference issues in high altitude platform stations.
Article
Computer Science, Artificial Intelligence
Vikram Garg, Anupam Shukla, Ritu Tiwari
Summary: This paper proposes an adaptive exploration robotic PSO (AERPSO) algorithm to solve multi-target search problems. By using evolutionary speed and aggregation degree, the proposed method increases the chances of exploring unexplored regions and addresses obstacle avoidance. The algorithm performs exceptionally well in multi-target searching, improving search time and detection rate.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Eslam Al Maghayreh, Habib Dhahiri, Fahad Albogamy, Mohamad Mahmoud Al Rahhal, Awais Mahmood, Esam Othman, Wail S. Elkilani
Summary: This paper investigates a distributed predicates detection algorithm based on the particle swarm optimization algorithm, showing good performance in experiments.
Article
Biochemistry & Molecular Biology
Ross G. Murphy, Alan Gilmore, Seedevi Senevirathne, Paul G. O'Reilly, Melissa LaBonte Wilson, Suneil Jain, Darragh G. McArt
Summary: This study validates unique candidate gene signatures for different underlying biology using Enhanced Binary Particle Swarm Optimization (EBPSO) on transcriptomics cohorts. EBPSO consistently demonstrates accuracy similar to BPSO but with smaller feature signatures and faster runtimes. EBPSO has the ability to identify accurate, succinct, and prognostic signatures that are distinct from traditional single gene signatures.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Physics, Multidisciplinary
Bozena Borowska
Summary: This study proposes a learning competitive swarm optimization algorithm (LCSO) based on particle swarm optimization method and competition mechanism, which improves the search process and achieves higher efficiency compared to other tested methods.
Article
Green & Sustainable Science & Technology
Isaac Oyeyemi Olayode, Lagouge Kwanda Tartibu, Modestus O. Okwu, Alessandro Severino
Summary: This study compares the efficacy of ANN-PSO and ANN models in predicting traffic flow volume in the South African transportation system, with results indicating that the ANN-PSO model is more efficient and effective in forecasting vehicle traffic flow at four-way signalized road intersections.
Article
Multidisciplinary Sciences
Vikram Garg, Ritu Tiwari, Anupam Shukla, Joydip Dhar
Summary: This paper discusses a distributed cooperation-based strategy that uses swarm intelligence based on a robotic particle swarm optimization (RPSO) algorithm to search dynamic targets, and overcomes the limitations of centralized cooperation strategies.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Mathematics, Applied
Shaojie Lv, Feifei Song
Summary: This study uses particle swarm optimization (PSO) to investigate the role of cooperation and punishment in public goods game, finding that intermediate values of the weighting coefficient omega increase the input of punishment, leading to a decrease in cooperation. For low or high values of omega, only cooperators on the edge of clusters tend to punish defectors, thereby increasing the cooperation level of the population.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Construction & Building Technology
K. C. Chan, Victor T. T. Wong, Anthony K. F. Yow, P. L. Yuen, Christopher Y. H. Chao
Summary: Traditionally, chiller plants are controlled by predetermined strategies, but this study proposes a hybrid predictive operational control strategy using artificial intelligence and particle swarm optimization algorithms to optimize the performance of the chiller plant. The strategy has been shown to improve the system coefficient of performance (COP) and reduce overall energy consumption in a real-world application.
ENERGY AND BUILDINGS
(2022)
Review
Chemistry, Multidisciplinary
Zool Hilmi Ismail, Mohd Ghazali Mohd Hamami
Summary: This study provides a systematic literature review of swarm robotics (SR) strategies for target search problems with environmental constraints, exploring different approaches for handling various levels of environment complexity and summarizing suitable strategies for real-world applications.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Rashid A. Saeed, Mohamed Omri, S. Abdel-Khalek, Elmustafa Sayed Ali, Maged Faihan Alotaibi
Summary: This article discusses the challenges and issues in drone path planning and introduces the application of swarm optimization algorithms in solving path planning problems. The article summarizes different swarm optimization algorithms and focuses on the analysis of the performance of the ant colony optimization algorithm in drone path planning.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Cybernetics
Rafael Guerra De Pontes, Herman Martins Gomes, Igor Santa Ritta Seabra
Summary: Given the increasing competition in the digital gaming industry, the production of creative and appealing games has become more complex. This paper proposes a novel approach to procedural content generation (PCG) using Particle Swarm Optimization (PSO). The experiments show that PSO outperforms Genetic Algorithms (GA) in terms of convergence time and fitness function values for PCG tasks.
ENTERTAINMENT COMPUTING
(2022)
Article
Chemistry, Multidisciplinary
Hossein R. Najafabadi, Tiago G. Goto, Mizael S. Falheiro, Thiago C. Martins, Ahmad Barari, Marcos S. G. Tsuzuki
Summary: Topology optimization of engineering products is crucial for maximizing performance and efficiency, with gradient-based and non-gradient-based methods being the two main categories. Non-gradient-based methods are gaining attention due to their independence from derivatives of objective functions and compatibility with the knowledge structure in digital design and simulation domains.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Interdisciplinary Applications
Andre Kubagawa Sato, Thiago Castro Martins, Marcos Sales Guerra Tsuzuki
Summary: Irregular packing problems are an important subject in the study of C&P problems, with efficient solutions having significant economic and environmental impacts. The main objective is to achieve a feasible layout without overlap. The best packing algorithms utilize overlap minimization approach for high density solutions.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2022)
Article
Chemistry, Multidisciplinary
Ahmad Barari, Marcos Sales Guerra Tsuzuki
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Civil
Tiago G. Goto, Hossein R. Najafabadi, Mizael F. Falheiro, Rafael T. Moura, Larissa Driemeier, Ahmad Barari, Marcos S. G. Tsuzuki, Thiago C. Martins
Summary: Non-gradient-based topology optimization (NGTO) is a promising method that can avoid local minima and deal better with manufacturability constraints. In this study, a new NGTO algorithm using the simulated annealing algorithm and connectivity criteria was proposed. The algorithm penalizes checkerboard solutions and converges to optimized structures with comparable or enhanced compliance values. The proposed algorithm, being non-gradient-based and easy to apply, presents itself as a promising approach in the field of topology optimization research. The main contribution of the proposed method is the binary non-gradient topology optimization with checkerboard-free structure.
Article
Computer Science, Artificial Intelligence
Andre Kubagawa Sato, Leandro Resende Mundim, Thiago Castro Martins, Marcos Sales Guerra Tsuzuki
Summary: This paper proposes new separation and compaction algorithms for the two-open dimension nesting problem. The algorithms achieve optimal solutions within a short runtime and are competitive with other literature algorithms. The new algorithm performs better than other approaches on benchmark instances with two open dimensions.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Andre Kubagawa Sato, Thiago Castro Martins, Marcos Sales Guerra Tsuzuki
Summary: The finite element method (FEM) is commonly used for describing physical phenomena through solving partial differential equations. This study proposes a parallel incomplete Cholesky conjugate gradient (ICCG) algorithm for graphics processing units (GPUs), which is suitable for Monte Carlo-based solutions to inverse problems. The algorithm uses the cpJDS sparse matrix format and a coloring scheme to overcome difficulties in parallelizing the triangular solver. Tests on various sparse matrices showed that the proposed solution outperforms the CPU implementation, achieving speed-ups of up to 60x for medium-to-large matrices.
Article
Chemistry, Multidisciplinary
Naser Tanabi, Agesinaldo Matos Silva, Marcosiris Amorim Oliveira Pessoa, Marcos Sales Guerra Tsuzuki
Summary: This study proposes an algorithm to optimize the shape of an airfoil based on variable parameters and flight conditions. The algorithm uses NACA-4 digit airfoils as input and employs a bounds definition to ensure the result is within the capabilities of the morphing wing. The proposed algorithm is compared with a previous flow solver for validation.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Eduardo Umaras, Ahmad Barari, Oswaldo Horikawa, Marcos Sales Guerra Tsuzuki
Summary: There is a trade-off between quality and affordability in component manufacturing, as higher precision often leads to higher costs. This study introduces a novel approach that optimizes dimensional tolerances of mechanical assembly components, considering manufacturing requirements and costs of non-quality. The proposed method also takes into account the functional constraints imposed by interrelated tolerance chains within the product.
APPLIED SCIENCES-BASEL
(2023)
Article
Acoustics
Nicolas Perez, Marcelo Y. Matuda, Flavio Buiochi, Julio C. Adamowski, Marcos Sales Guerra Tsuzuki
Summary: This paper presents a temperature compensation methodology for measuring the thickness of metallic structures using ultrasound. The methodology can be applied to evaluate corrosion over long time periods.
Article
Engineering, Electrical & Electronic
Cody Berry, Marcos S. G. Tsuzuki, Ahmad Barari
Summary: This paper discusses a method for online data collection from manufactured parts in Industry 4.0 to monitor production health, and the method for noise reduction and removal in optical sensor-based inspection of highly reflective parts.
Article
Engineering, Electrical & Electronic
Andre C. M. Cavalheiro, Diolino J. Santos Filho, Jonatas C. Dias, Aron J. P. Andrade, Jose R. Cardoso, Marcos S. G. Tsuzuki
Summary: This study proposes a hierarchical supervisory control system based on a mechatronic approach for dynamically, automatically, and safely controlling an implantable centrifugal blood pump. By using Bayesian networks to diagnose the patient's cardiovascular condition, Petri nets to generate the control algorithm, and safety instrumented systems to ensure the safety of the VAD system, the effectiveness and performance of the VAD can be improved.
Proceedings Paper
Engineering, Industrial
Felipe B. C. L. Lima, Fernando F. Doria, Lucas Real, Vinicius R. G. Oliveira, Rogerio Y. Takimoto, Andre K. Sato, Hossein R. Najafabadi, Fabio S. G. Tsuzuki, Marcos S. G. Tsuzuki
Summary: The paper proposes using different CNNs to classify soccer field views, aiding in creating correspondences of relevant points automatically, which is the most difficult part of automation. A method for creating synthetic soccer field views is suggested, and all three CNNs achieved good results and high accuracy.
2021 14TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRY APPLICATIONS (INDUSCON)
(2021)
Proceedings Paper
Engineering, Industrial
Andre Cesar Martins Cavalheiro, Marcos de Sales Guerra Tsuzuki, Jose Roberto Cardoso, Diolino Jose dos Santos Filho, Aron Jose Pazin de Andrade
Summary: The text discusses the necessity of implanting Ventricular Assist Devices (VAD) in patients with severe heart diseases, especially those with indication for heart transplantation. It also highlights the potential failures even in reliable devices, and proposes a mechatronic approach for dynamically, automatically, and safely controlling VAD.
2021 14TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRY APPLICATIONS (INDUSCON)
(2021)
Proceedings Paper
Engineering, Industrial
Hossein R. Najafabadi, Bruno M. Verona, Tiago G. Goto, Thiago C. Martins, Ahmad Barari, Marcos S. G. Tsuzuki
Summary: This paper introduces a non-gradient topology optimization method developed with simulated annealing combined with density filter and morphology operators to address manufacturing limitations in the microfabrication process. The results of topology optimization on a cantilever beam show minimal changes in system performance when applying microfabrication constraints through morphology operators and density filters.
2021 14TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRY APPLICATIONS (INDUSCON)
(2021)
Article
Computer Science, Artificial Intelligence
Eduardo Umaras, Ahmad Barari, Marcos Sales Guerra Tsuzuki
Summary: Successful products offer high quality at a fair cost, with functional reliability being a major requirement. Intelligent designs and robust designs can achieve fair costs, being insensitive to sources of variation during product life.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
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)
