Article
Automation & Control Systems
Joao Luiz Junho Pereira, Matheus Brendon Francisco, Sebastiao Simoes da Cunha, Guilherme Ferreira Gomes
Summary: Optimization is a crucial tool for achieving optimal results in various engineering problems. The Lichtenberg Optimization Algorithm is a nature-inspired method used for complex inverse damage identification, showcasing strong performance even in noisy response and low damage severity situations.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Joao Luiz Junho Pereira, Guilherme Antonio Oliver, Matheus Brendon Francisco, Sebastiao Simoes Cunha, Guilherme Ferreira Gomes
Summary: The Multi-objective Lichtenberg Algorithm is a hybrid meta-heuristic algorithm capable of dealing with multiple objectives, distributing points for evaluation through Lichtenberg patterns in each iteration. It has shown promising results in terms of convergence and maximum spread, outperforming traditional and recent algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Joao Luiz Junho Pereira, Matheus Chuman, Sebastiao Simoes Cunha Jr, Guilherme Ferreira Gomes
Summary: This study develops a numerical identification and characterization of crack propagation using the Lichtenberg optimization method, achieving good crack identification results in plates-like structures. The Lichtenberg algorithm was applied as the main solver for crack tip modeling.
ENGINEERING COMPUTATIONS
(2021)
Article
Physics, Applied
Zhijie Shi, Chuanyang Li, Zhipeng Lei, Yang Yang, Jinliang He, Jiancheng Song
Summary: Electrostatic discharge (ESD) is a common phenomenon on insulation surfaces of electrical and electronic devices under different environmental conditions. This study shows that the discharge pattern of PMMA is influenced by relative humidity (RH) during ESD, with high RH conditions suppressing the ESD process. The results highlight the significant impact of voltage amplitude, polarity, and electrode shape on the surface discharge process during ESD.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2021)
Article
Mathematics
Broderick Crawford, Ricardo Soto, Jose Lemus-Romani, Marcelo Becerra-Rozas, Jose M. Lanza-Gutierrez, Nuria Caballe, Mauricio Castillo, Diego Tapia, Felipe Cisternas-Caneo, Jose Garcia, Gino Astorga, Carlos Castro, Jose-Miguel Rubio
Summary: The balance between exploration and exploitation is a key issue in metaheuristic optimization, with a Q-learning integration framework being proposed to improve operator selection and showing statistical improvements in the balance and solution quality for multiple recent metaheuristic algorithms tested on the Set Covering Problem.
Article
Computer Science, Artificial Intelligence
Joao Luiz Junho Pereira, Matheus Brendon Francisco, Ronny Francis Ribeiro, Sebastiao Simoes Cunha, Guilherme Ferreira Gomes
Summary: This paper presents a multi-objective optimization method for isogrid tube structures, using the Multi-objective Lichtenberg Algorithm and finite element method. The results show that optimizations via finite element updating associated with meta-heuristics can effectively reduce mass, decrease instability coefficient, improve TW, and increase natural frequency.
Review
Computer Science, Interdisciplinary Applications
Raedal Abu Zitar, Mohammed Azmi Al-Betar, Mohammed A. Awadallah, Iyad Abu Doush, Khaled Assaleh
Summary: This review paper provides an in-depth overview of the JAYA algorithm, analyzing its optimization model, convergence characteristics, and various versions. It also discusses the applications and open sources code of the algorithm, highlighting its advantages and limitations in dealing with optimization problems. Finally, the paper suggests possible future enhancements to improve the performance of the JAYA algorithm.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2022)
Article
Mechanics
Joao Luiz Junho Pereira, Felipe Ciolini Guedes, Matheus Brendon Francisco, Andre Garcia Chiarello, Guilherme Ferreira Gomes
Summary: This study optimizes the disk brake rotor using parametric and topological optimizations, considering mass, temperature variation, and breaking time as conflicting objectives. The MOLA algorithm is employed for parametric optimization and TOPSIS for decision-making. The rotor design is then performed in SolidWorks (R) 3D software and topological optimization is carried out using ANSYS software. The results show significant reduction in mass and the ability to find a reliable and lightweight rotor with low braking time.
MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES
(2023)
Article
Automation & Control Systems
Damodar Panigrahy, Padarbinda Samal
Summary: This manuscript proposes a new metaheuristic optimization algorithm based on nature-inspired algorithms, which solves constraint optimization problems through two stages of calculating and updating fitness values. By comparing and validating with seven other algorithms, the results show that the proposed algorithm has better performance.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Mathematics
Mohammed H. Qais, Hany M. Hasanien, Saad Alghuwainem, Ka Hong Loo
Summary: This paper proposes a new optimization algorithm, called the propagation search algorithm (PSA), which utilizes mathematical models of voltage and current as search agents. The robustness of PSA is verified and it is successfully applied to find the optimum design parameters of engineering design problems.
Article
Computer Science, Artificial Intelligence
Essam H. Houssein, Diego Oliva, Emre Celik, Marwa M. Emam, Rania M. Ghoniem
Summary: Feature selection is an optimization problem that aims to simplify and improve the quality of highly dimensional datasets by selecting prominent features and eliminating redundant and irrelevant data to enhance classification accuracy. The Sooty Tern Optimization Algorithm (STOA) and its improved version mSTOA are used to optimize the feature selection problem. However, mSTOA performs better than STOA in terms of convergence to optimal solutions, as validated through experiments and statistical analyses.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Mathematics
Mohammed H. Qais, Hany M. Hasanien, Rania A. Turky, Saad Alghuwainem, Marcos Tostado-Veliz, Francisco Jurado
Summary: This paper presents a novel metaheuristic optimization algorithm called the circle search algorithm (CSA) that is inspired by the geometrical features of circles. The CSA is evaluated against other algorithms through independent experiments using a variety of functions and engineering problems, and the results show that CSA outperforms other algorithms in terms of convergence speed and robustness to high-dimensional problems. Therefore, CSA is a promising algorithm for solving various optimization problems.
Article
Computer Science, Information Systems
Mohammed Azmi Al-Betar, Iyad Abu Doush, Sharif Naser Makhadmeh, Ghazi Al-Naymat, Osama Ahmad Alomari, Mohammed A. Awadallah
Summary: This survey paper comprehensively analyzes the performance and applications of Equilibrium Optimizer (EO), comparing it with eight other well-established methods. Different versions and applications of EO are discussed, highlighting their pros and cons, and suggesting future research directions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Civil
Matheus Brendon Francisco, Joao Luiz Junho Pereira, Guilherme Augusto Vilas Boas Vasconcelos, Sebastiao Simoes da Cunha, Guilherme Ferreira Gomes
Summary: Through numerical, experimental, and statistical analysis, this paper conducted a multi-objective optimization study on the double arrowhead auxetic model, analyzing its performance in terms of mass, critical buckling load, natural frequency, Poisson's ratio, and maximum load of compression, and improving its performance through optimization analysis.
Article
Materials Science, Multidisciplinary
Matheus Brendon Francisco, Joao Luiz Junho Pereira, Anderson Paulo de Paiva, Elioenai Levi Barbedo, Sebastiao Simoes da Cunha Jr, Guilherme Ferreira Gomes
Summary: The authors optimized an auxetic tube considering various structural responses and used the response surface methodology to generate a metamodel with non-linear equations. Data were generated through numerical modeling after experimental validation. The Lichtenberg Algorithm was employed to find the best configurations. This paper demonstrates unprecedented improvements in the static and modal performance of an auxetic tube, achieving up to 43% enhancement compared to the initial model.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2023)
Article
Computer Science, Artificial Intelligence
Evandro Gabriel Magacho, Ariosto Bretanha Jorge, Guilherme Ferreira Gomes
Summary: Truss-type structures are widely used in engineering, but direct inspection techniques face difficulties in locating and identifying structural damage due to their large-scale nature. Therefore, structural health monitoring techniques based on optimization algorithms offer a promising and non-destructive solution. In this study, an inverse damage identification problem for large-scale lattice-type structures is solved using the SunFlower Optimization algorithm, which considers multiple damage sites and two objective functions. The inclusion of mode shapes in a multi-objective formulation improves the accuracy of damage identification. The multi-objective SFO algorithm outperforms NSGAII.
EVOLUTIONARY INTELLIGENCE
(2023)
Article
Thermodynamics
T. A. Z. de Souza, J. L. J. Pereira, M. B. Francisco, C. A. R. Sotomonte, B. Jun Ma, G. F. Gomes, C. J. R. Coronado
Summary: This study provides a detailed analysis of hydrogen production using Response Surface Methodology and Lichtenberg Algorithm, aiming to quickly optimize steam reforming cycles considering different feedstock compositions and other characteristics. Comparison with other optimization studies demonstrates that this new methodology offers a quick and consistent method for optimizing steam reforming and potentially other thermodynamic cycles.
INTERNATIONAL JOURNAL OF GREEN ENERGY
(2023)
Article
Materials Science, Composites
Daniel Brighenti Bortoluzzi, Camila Aparecida Diniz, Ronny Francis Ribeiro Jr, Matheus Brendon Francisco, Antonio Carlos Ancelotti Jr, Guilherme Ferreira Gomes
Summary: A great deal of research has shown that z-pins can significantly enhance the mechanical properties of carbon fiber composite laminates. This study investigates the modal responses of z-pinned composites using rectangular z-pin sizes and area density insertion design variables. The experimental results indicate an increase in the natural frequency and a reduction in vibration amplitude when compared to unpinned specimens. Furthermore, the study highlights the use of analysis of variance (ANOVA) and artificial neural networks (ANN) for analyzing and predicting the modal responses of z-pinned composites.
APPLIED COMPOSITE MATERIALS
(2023)
Article
Engineering, Civil
Matheus Brendon Francisco, Joao Luiz Junho Pereira, Sebastiao Simoes da Cunha, Guilherme Ferreira Gomes
Summary: This paper focuses on the multi-objective optimization of a tubular sandwich structure with an auxetic reentrant core. The Response Surface Methodology and the Multi-objective Lichtenberg Algorithm were used to find the optimized configuration of the structure. A parametric analysis was also conducted to study the influence of design factors on different responses. The results demonstrated the significant effect of unit cell height on failure load, natural frequency, and mass, while revealing the lack of correlation between unit cell height and Poisson's ratio.
ENGINEERING STRUCTURES
(2023)
Article
Computer Science, Artificial Intelligence
Joao Luiz Junho Pereira, Benedict Jun Ma, Matheus Brendon Francisco, Ronny Francis Ribeiro Jr, Guilherme Ferreira Gomes
Summary: Feature selection is a valuable tool in understanding problems in data mining, improving patterns and reducing computational costs. This study introduces a new metaheuristic called binary sunflower optimization (BSFO), which shows promising results in terms of fitness value and computational costs. The improved version, IBSFO, is compared with eight other metaheuristics and performs better in terms of fitness value and execution time.
Article
Computer Science, Artificial Intelligence
Joao Luiz Junho Pereira, Guilherme Ferreira Gomes
Summary: In order to tackle challenging engineering problems, the state-of-the-art in multi-objective optimization is shifting towards using meta-heuristics and a posteriori decision-making methods. The Multi-objective Sunflower Optimization (MOSFO) algorithm, inspired by the phototropic life cycle of sunflowers, was created and validated in this work. MOSFO demonstrated significant convergence and coverage capabilities and outperformed other popular and recent algorithms in most of the test functions, making it a promising method for problems with multiple objectives.
Article
Materials Science, Characterization & Testing
Lucas Antonio de Oliveira, Guilherme Ferreira Gomes, Joao Luiz Junho Pereira, Matheus Brendon Francisco, Anthonin Demarbaix, Sebastiao Simoes Cunha Jr
Summary: Infrared thermography technique is used to detect damage in metallic and non-metallic materials, and it helps in determining the safety of mechanical structures. Vibrothermography combines vibration and infrared thermography to identify internal damages through temperature mapping. The current study focuses on identifying different research approaches for damage identification and characterization, evaluating heat generation mechanisms in damaged regions, and utilizing mathematical methods to enhance the efficiency of damage detection and characterization.
JOURNAL OF NONDESTRUCTIVE EVALUATION
(2023)
Article
Engineering, Mechanical
Ronny Francis Ribeiro Junior, Fabricio Alves de Almeida, Ariosto Bretanha Jorge, Joao Luiz Junho Pereira, Matheus Brendon Francisco, Guilherme Ferreira Gomes
Summary: Fault diagnosis is crucial for maintenance industries to prevent catastrophic failures and save time and money. This paper proposes a model using uniaxial acceleration signals to cluster, identify, and diagnose six different failures in electric motors. Experiment results demonstrate the efficiency of the proposed method, with an average accuracy of 97.9%, especially in identifying bearing, unbalanced, and mechanical loss failures. The method can be used for early detection of fault conditions based on real electric motor experiments.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2023)
Article
Mechanics
Joao Luiz Junho Pereira, Felipe Ciolini Guedes, Matheus Brendon Francisco, Andre Garcia Chiarello, Guilherme Ferreira Gomes
Summary: This study optimizes the disk brake rotor using parametric and topological optimizations, considering mass, temperature variation, and breaking time as conflicting objectives. The MOLA algorithm is employed for parametric optimization and TOPSIS for decision-making. The rotor design is then performed in SolidWorks (R) 3D software and topological optimization is carried out using ANSYS software. The results show significant reduction in mass and the ability to find a reliable and lightweight rotor with low braking time.
MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES
(2023)
Article
Materials Science, Multidisciplinary
Guilherme Antonio Oliver, Joao Luiz Junho Pereira, Matheus Brendon Francisco, Guilherme Ferreira Gomes
Summary: This study proposes a damage index for identifying delaminations in laminated composite structures using a discrete wavelet transform. The index achieved high-quality results in identifying damage in both numerical cases and real carbon fiber-reinforced polymer beams. The method proved effective at locating damage in almost all positions along the beam, with some issues at the free end due to signal discontinuity.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2023)
Article
Engineering, Civil
Camila Aparecida Diniz, Joao Luiz Junho Pereira, Daniel Brighenti Bortoluzzi, Sebastia Simoes Cunha Jr, Guilherme Ferreira Gomes
Summary: A comparative study was conducted on the static and dynamic behavior of a new type of tubular structure with drop-offs used in lower limb prostheses. Numerical and experimental methods were used to obtain results on natural frequencies, damping loss factors, and maximum compression load. The hybrid structure with drop-offs was found to be the best cost-effective option for pylon tubes.
ENGINEERING STRUCTURES
(2023)
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)