Article
Computer Science, Artificial Intelligence
Peng Gui, Fazhi He, Bingo Wing-Kuen Ling, Dengyi Zhang
Summary: This study introduces an optimization algorithm, the united equilibrium optimizer (UEO), which improves both exploration and exploitation capabilities by modifying the search structure of the equilibrium optimizer (EO) and adjusting it with dynamic parameters. The UEO outperforms other algorithms in most cases, as demonstrated through benchmark tests and practical problems.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
Binwen Zhu, Qifang Luo, Yongquan Zhou
Summary: With the rapid development of communication technology, the reduction of side lobe level (SLL) in line antenna arrays (LAA) remains a challenging problem. This study proposes a quantum equilibrium optimizer (QEO) algorithm for LAA optimization, which combines quantum coding and quantum rotation gate strategy. The proposed algorithm is proven to be advantageous in terms of maximum SLL reduction, convergence speed, and accuracy compared to other metaheuristic optimization algorithms.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Biotechnology & Applied Microbiology
Zongshan Wang, Hongwei Ding, Jingjing Yang, Peng Hou, Gaurav Dhiman, Jie Wang, Zhijun Yang, Aishan Li
Summary: This paper introduces a bio-inspired algorithm called Salp swarm algorithm (SSA) and proposes an improved strategy combining pinhole-imaging-based learning (PIBL) and orthogonal experimental design (OED). It also designs an effective adaptive conversion parameter method to enhance the algorithm's performance. Comparative experiments show that the algorithm performs well in most benchmark problems.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Engineering, Multidisciplinary
Weng-Hooi Tan, Junita Mohamad-Saleh
Summary: This research paper proposes a hybrid Whale Optimization Algorithm (WOA) variant based on Equilibrium Optimizer (EO), named Equilibrium Whale Optimization Algorithm (EWOA). The proposed algorithm combines WOA's encircling and net-bubble attacking mechanisms via EO's weight balance strategy, leading to better optimization efficiency than the original and other state-of-the-art algorithms. The experimental results demonstrate that EWOA outperforms other algorithms in terms of statistical mean performance, clustering data, convergence rate, and robustness.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Benyamin Abdollahzadeh, Farhad Soleimanian Gharehchopogh, Seyedali Mirjalili
Summary: Metaheuristics play a crucial role in solving optimization problems, often inspired by the collective intelligence of natural organisms. This paper introduces a new metaheuristic algorithm, GTO, inspired by gorilla troops' social intelligence in nature. Results show that the GTO outperforms existing metaheuristics on most benchmark functions and engineering problems, especially in high-dimensional scenarios.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Ali Kaveh, Siamak Talatahari, Nima Khodadadi
Summary: This paper presents an art-inspired optimization algorithm called Stochastic Paint Optimizer (SPO), which simulates the search space as a painting canvas and utilizes different color combinations to find the best solution. The performance of SPO is evaluated using benchmark functions and compared with other algorithms, demonstrating its competitive results. Additionally, the practicality of SPO is confirmed through its application to challenging structural design problems.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Information Systems
Yuxian Duan, Changyun Liu, Song Li, Xiangke Guo, Chunlin Yang
Summary: This article introduces an improved affinity propagation algorithm based on optimization of preference (APBOP) for automatic clustering on high-dimensional data. APBOP aims to address the challenges of feature extraction from high-dimensional data and the sensitivity of the clustering performance to preference. The proposed method utilizes dimensionality reduction and preference optimization techniques to improve the effectiveness of affinity propagation.
INFORMATION SCIENCES
(2023)
Article
Engineering, Multidisciplinary
Muqthiar Ali Shaik, Padma Lalitha Mareddy, N. Visali
Summary: This paper discusses the method of improving system efficiency by reconfiguring the distribution network and installing distributed generation units. An equilibrium optimizer is used to determine the optimal location for DG and perform reliability analysis. The implemented method results in substantial improvement in voltage profile, reduction in power loss, and enhancement of system reliability indexes.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Qingsong Fan, Haisong Huang, Kai Yang, Songsong Zhang, Liguo Yao, Qiaoqiao Xiong
Summary: The Equilibrium Optimizer (EO) is a physics-based metaheuristic algorithm that has competitive performance but with certain drawbacks. To address these issues, a modified version (m-EO) utilizing opposition-based learning and novel update rules is proposed, which significantly improves optimization precision and convergence speed. Experimental results demonstrate that the m-EO outperforms not only the original EO but also other state-of-the-art algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Mathematics
Mohamed Abdel-Basset, Reda Mohamed, Karam M. Sallam, Ripon K. Chakrabortty
Summary: This paper introduces a novel physical-inspired metaheuristic algorithm called Light Spectrum Optimizer (LSO) for continuous optimization problems. The experimental results demonstrate the merits and highly superior performance of the proposed LSO algorithm.
Article
Computer Science, Artificial Intelligence
Essam H. Houssein, Emre Celik, Mohamed A. Mahdy, Rania M. Ghoniem
Summary: This paper proposes a self-adaptive Equilibrium Optimizer (self-EO) to address global, combinatorial, engineering, and multi-objective optimization problems. By integrating four effective exploring phases, the new self-EO algorithm overcomes the potential shortcomings of the original EO and achieves better results compared to other nine metaheuristic algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Biology
Changting Zhong, Gang Li, Zeng Meng, Haijiang Li, Wanxin He
Summary: Feature selection is a popular technique in machine learning to improve classification accuracy by extracting optimal features. This study proposes a self-adaptive quantum equilibrium optimizer with artificial bee colony (SQEOABC) for feature selection. Experimental results on benchmark datasets and a real-world COVID-19 problem demonstrate the effectiveness and superiority of the SQEOABC algorithm compared to other metaheuristic algorithms and variants of equilibrium optimizer.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Changting Zhong, Gang Li, Zeng Meng, Wanxin He
Summary: In this work, the EOOBLE algorithm is proposed to solve high-dimensional global optimization problems. It combines the opposition-based learning strategy, the Levy flight strategy, and the evolutionary population dynamics strategy to improve the convergence capacity and performance. Experimental results show that the EOOBLE algorithm outperforms other state-of-the-art metaheuristic algorithms and variants of EO.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Shijie Zhao, Tianran Zhang, Shilin Ma, Mengchen Wang
Summary: This paper proposes a novel swarm intelligence-based metaheuristic called sea-horse optimizer (SHO) which mimics the movement, predation, and breeding behaviors of sea horses in nature. The algorithm is designed to balance local exploitation and global exploration, and has been shown to be a high-performance optimizer with positive adaptability to deal with constraint problems.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Zeng Meng, Ali Riza Yildiz, Seyedali Mirjalili
Summary: This paper proposes a unified framework to improve the performance of existing RBDO algorithms for complex problems. The framework is based on three new strategies: generalized decoupling evolutionary and metaheuristic RBDO framework, particle's memory saving strategy, and adaptive fractional-order equilibrium optimizer algorithm. Experimental results demonstrate that the proposed algorithm outperforms other algorithms in terms of performance.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Navid Kardani, Abidhan Bardhan, Bishwajit Roy, Pijush Samui, Majidreza Nazem, Danial Jahed Armaghani, Annan Zhou
Summary: A novel hybrid model combining IHHO and ELM was proposed to predict the permeability of tight carbonates, achieving highly accurate predictions in the testing phase. The results of the proposed ELM-IHHO model outperformed other benchmark models in predicting the permeability of tight carbonates.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Geological
Xi Sun, Jie Li, Donald Cameron, Annan Zhou
Summary: This study conducted field monitoring in a suburb of Melbourne to investigate the impact of trees on expansive soils and the physical processes involved. Through laboratory tests and field investigations, the study evaluated soil properties and tree-root interaction with the soil, providing valuable insights for improving current footing design guidelines in geotechnical engineering practices.
Article
Engineering, Geological
Song-Shun Lin, Shui-Long Shen, Ning Zhang, Annan Zhou
Summary: This paper introduces a risk evaluation model of excavation system based on the extended TODIM method. The model consists of three phases for risk assessment and has been applied in an excavation construction project in Tianjin. Results show that high-risk sub-systems can be identified, consistent with engineering practices, and sensitivity analysis has been conducted to increase the model's robustness.
Article
Astronomy & Astrophysics
An-Nan Zhou, Lin Cai, Chun-Yu Xiao, Ding-Yin Tan, Hong-Yin Li, Yan-Zheng Bai, Ze-Bing Zhou, Jun Luo
Summary: Non-gravitational force models play a critical role in satellite orbit determination and prediction, as well as in gravitational reference sensors and accelerometers in space missions. In this study, a correction was made in the non-gravitational force models based on data from the TQ-1 mission, resulting in a significant improvement in the calibration of inertial sensor data. The peak-to-peak value of the non-gravitational acceleration correction terms and the root mean square of calibration residual errors were both reduced, while the bias and scale factor of the inertial sensor were obtained through least-squares fit calibration. Additionally, the validation and analysis of signal compositions of the inertial sensor measurements were conducted.
CLASSICAL AND QUANTUM GRAVITY
(2022)
Article
Computer Science, Interdisciplinary Applications
Xin Liu, Annan Zhou, Jie Li, Arul Arulrajah
Summary: This study presents a micromechanical investigation on the characteristics of shear-induced anisotropy in granular media under different saturation states. The effects of suctions on anisotropy are explored, and it is found that mechanical anisotropy plays a dominant role in providing shear resistance.
COMPUTERS AND GEOTECHNICS
(2022)
Article
Construction & Building Technology
Fengming Xu, Xiaoshan Lin, Annan Zhou, Qing-feng Liu
Summary: This study investigates the effect of three different waste ceramic aggregates as internal curing materials for high performance concrete (HPC). The experimental results show that using aggregates with larger porosity achieves better shrinkage control, while lower replacement ratios result in higher strength. All three recycled ceramic aggregates are highly efficient in reducing autogenous shrinkage of HPC while maintaining satisfactory mechanical properties.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Engineering, Geological
Tao Yan, Shui-Long Shen, Annan Zhou
Summary: This paper proposes a framework to identify geological characteristics using a fuzzy C-means algorithm based on borehole data and operational data. The identified factors are significantly reduced by principal component analysis, and the types of geological characteristics are determined using the fuzzy C-means model.
Article
Multidisciplinary Sciences
Zhonggao Chen, Jiapei Du, Annan Zhou, Chunyu Wang, Yuhuan Bu, Huajie Liu
Summary: This study investigates the relationship between the microstructure complexity of silica-enhanced cement and its compressive strength, using scanning electron microscope and image processing methods. The results show that curing time and temperature directly and indirectly affect the complexity of cement microstructure and compressive strength, respectively. Moreover, pore size distribution is found to be the most important factor influencing the complexity of cement matrix and compressive strength of silica-enhanced cement.
ROYAL SOCIETY OPEN SCIENCE
(2022)
Article
Engineering, Geological
Song-Shun Lin, Shui-Long Shen, Annan Zhou
Summary: This study develops a hybrid model based on PSO and GRU neural network to predict the performance of shield tunneling. The model establishment includes steps such as data processing, model evaluation, and correlation analysis. Experimental results indicate the significance of geological and construction variables on the model performance, providing a new approach to tackle time-series data in tunnel projects.
JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING
(2022)
Article
Engineering, Geological
Pierre Guy Atangana Njock, Ning Zhang, Annan Zhou, Shui-Long Shen
Summary: This study proposes an improved random forest (IRF) model to evaluate ground displacement caused by jet grouting. By integrating a hybrid particle swarm optimization-simulated annealing algorithm (PSO-SA) into random forest, the IRF model shows better searching and convergence abilities compared to its counterparts. The results demonstrate that the IRF model outperforms benchmark models in predicting ground displacement. Additionally, the analysis of variable importance shows that ground lateral displacement can be controlled through two operating parameters.
GEOTECHNICAL AND GEOLOGICAL ENGINEERING
(2023)
Article
Mechanics
X. W. Yuan, W. G. Li, Z. M. Xiao, Y. M. Zhang
Summary: A temperature-dependent micromechanical model was proposed to estimate the transverse mechanical properties of carbon fiber reinforced polymer composites. The model considered the random distribution of fibers, the temperature-dependent Young's modulus of the polymer, and the plasticity model of the polymer. A modified cohesive zone model with temperature-dependent parameters was presented for simulating the fiber/polymer interface. The model was validated by experimental results and found to be reliable and accurate.
COMPOSITE STRUCTURES
(2023)
Article
Automation & Control Systems
Choon Wee Joel Lim, Yanmei Zhang, Sheng Huang, Wai Lee Chan
Summary: The study focuses on understanding the properties of clad formation in the directed energy deposition process for fabricating and repairing thin wall structures using stainless steel 316L powder. The parameters of laser power, laser traverse speed, and powder mass flow rate were investigated, and the clads obtained showed an average hardness close to SS316L materials. It was found that laser power is the most significant factor for clad depth, while laser traverse speed is dominant for clad height. The study also introduced a dimensionless analysis that can facilitate parameter selection for desired clad dimensions, potentially improving manufacturing turnaround time.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Shubham Gupta, Rong Su
Summary: In this study, an extended version of the differential evolution (DE) algorithm named multiple individual guided differential evolution (MGDE) is proposed. The MGDE algorithm introduces a novel mutation strategy based on multiple guiding individuals to manage diversity and convergence. Experimental results show that the MGDE algorithm performs well and is highly competitive with other metaheuristic algorithms.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Chemical
Xin Liu, Annan Zhou, Kai Sun, Shui-Long Shen
Summary: In this study, the influence of suction on the macro/micro-mechanical behaviour of unsaturated soil was investigated through a series of three-dimensional simulations using the discrete element method. The results were compared with laboratory test results to understand the relationship between macroscopic behavior and micro-mechanical variables.
Article
Materials Science, Composites
Jingjing Liu, Liqing Wang, Yuqing He, Yanmei Zhang, Xiaowei Yuan, WeiGuo Li
Summary: This study investigates the tensile behaviors of carbon fiber reinforced polymer laminates under low temperature and large open-hole conditions. The results show that large open-hole significantly decreases the strength of laminates, while low temperature enhances the strength of laminates with small open holes.
COMPOSITES COMMUNICATIONS
(2023)