相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。
Article
Engineering, Multidisciplinary
Jie Xing et al.
Summary: In this work, an improved Whale Optimization Algorithm (QGBWOA) is proposed to address the problems of falling into local optimum and slow convergence. Quasi-opposition-based learning and Gaussian barebone mechanism are introduced to enhance the searching ability and diversity of WOA. Experimental results on benchmark datasets demonstrate the significantly improved convergence accuracy and speed of QGBWOA. Furthermore, applications in feature selection and multi-threshold image segmentation validate its capability in solving complex real-world problems.
JOURNAL OF BIONIC ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Shihong Yin et al.
Summary: This study proposes an improved multi-objective slime mould algorithm (IBMSMA) for solving the multi-objective truss optimization problem. IBMSMA utilizes chaotic grouping mechanism, dynamic regrouping strategy, shift density estimation, and Pareto external archive to improve diversity, select superior search agents, and maintain convergence and distribution of non-dominated solutions. The performance of IBMSMA is evaluated by applying it to eight multi-objective truss optimization problems and comparing the results with 14 other optimization algorithms using hypervolume, inverted generational distance, and spacing-to-extent indicators. The results show that IBMSMA outperforms state-of-the-art algorithms in terms of convergence, diversity, and efficiency for large-scale engineering design problems.
JOURNAL OF BIONIC ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Hang Su et al.
Summary: This paper proposes an efficient optimization algorithm called RIME, which is based on the physical phenomenon of rime-ice. The algorithm simulates the growth process of soft-rime and hard-rime of rime-ice and constructs a corresponding search strategy and puncture mechanism. It improves the greedy selection mechanism and enhances the exploitation capability of the algorithm. The experimental results demonstrate the performance advantage of RIME compared to other well-established and improved algorithms, and the algorithm shows effectiveness and competitiveness in real-world problems.
Article
Computer Science, Interdisciplinary Applications
Qifang Luo et al.
Summary: This paper introduces a multi-objective equilibrium optimizer slime mould algorithm (MOEOSMA) for solving real-world constraint engineering problems. The proposed algorithm outperforms existing multi-objective slime mould algorithms in terms of optimization performance. MOEOSMA incorporates dynamic coefficients for adjusting exploration and exploitation trends, an elite archiving mechanism for promoting convergence, a crowding distance method for maintaining Pareto front distribution, and an equilibrium pool strategy for enhancing exploration ability. Experimental results demonstrate that MOEOSMA not only finds more Pareto optimal solutions, but also maintains a good distribution in decision and objective spaces. Statistical analysis shows that MOEOSMA has a strong competitive advantage in terms of convergence, diversity, uniformity, and extensiveness, and its overall performance is significantly better than other comparable algorithms.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Automation & Control Systems
Shuhui Wang et al.
Summary: Accurate identification of unknown parameters in fractional chaotic systems is crucial for precise control. This paper proposes an algorithm, called ISAWOA, which combines a surrogate-assisted model and improvements to the Whale Optimization Algorithm. The simulation results show that ISAWOA outperforms other algorithms in terms of accuracy and computational speed on benchmark functions and fractional chaotic systems.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Iman Ahmadianfar et al.
Summary: This study presents the analysis and principle of an innovative optimizer called INFO, which utilizes the weighted mean method to optimize different problems. The results show that INFO outperforms other methods in terms of exploration and exploitation, and is capable of converging to satisfactory solutions in engineering problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Multidisciplinary
Davut Izci et al.
Summary: This paper presents a novel hybrid metaheuristic optimization algorithm (AEONM) for designing an optimal PID controller for DC-DC buck converter's output voltage regulation. The algorithm combines artificial ecosystem-based optimization (AEO) algorithm with Nelder-Mead simplex method, and comparative performance analysis demonstrates its superiority in enhancing the buck converter's transient and frequency responses.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Nitish Chopra et al.
Summary: The Golden Jackal Optimization (GJO) algorithm, inspired by the hunting behavior of golden jackals, utilizes prey searching, enclosing, and pouncing steps mathematically to solve challenging engineering problems with unidentified search spaces.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
S. A. Angayarkanni et al.
Summary: In the digital era, Intelligent Transportation Systems play a crucial role in bridging communication and transportation engineering to provide traffic forecasting, incident broadcasting, and entertainment data. Improving the accuracy of machine learning algorithms in parameter selection is essential for accurate traffic flow prediction.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Zhong-kai Feng et al.
Summary: The CSA method, inspired by team cooperation behaviors, uses team communication, reflective learning, and internal competition operators to solve global optimization problems, demonstrating fast convergence and high search accuracy. It performs well in mathematical and engineering optimization problems, providing an effective tool for solving complex global optimization problems.
APPLIED SOFT COMPUTING
(2021)
Article
Biology
Sanjoy Chakraborty et al.
Summary: The COVID-19 pandemic has had a significant impact on various aspects of human life, highlighting the importance of rapid diagnosis and treatment. This research focuses on developing a computational tool to improve diagnostic accuracy by enhancing the whale optimization method and evaluating its efficiency through population reduction.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Biology
Shankar Thawkar et al.
Summary: The article introduces a hybrid feature selection method based on the Butterfly optimization algorithm and the Ant Lion optimizer for the design and development of a computer-based system for breast cancer detection. The method outperforms original algorithms in terms of accuracy, sensitivity, specificity, and error rates, demonstrating high performance and robustness in breast cancer diagnosis.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Kashif Hussain et al.
Summary: Feature selection is crucial in data mining, and the SCHHO hybrid optimization method proposed in this paper shows promising results in terms of efficient search and improved accuracy. The method integrates different search strategies to tackle the optimization problem in numerical optimization and feature selection. The experimental and statistical analyses demonstrate the effectiveness of SCHHO in reducing feature-size and achieving high accuracy without additional computational cost. Potential future directions for research are highlighted based on the findings of this study.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Mathematical & Computational Biology
Hadi Bayzidi et al.
Summary: The paper introduces a new metaheuristic optimization algorithm called social network search (SNS), which mimics the decision moods of social network users in expressing opinions. The algorithm shows effectiveness in solving engineering optimization problems by modeling real-world user behaviors in social networks.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2021)
Review
Automation & Control Systems
Mehrdad Rostami et al.
Summary: Research has shown that feature selection methods can improve the accuracy of data mining tasks and reduce computational complexity by reducing irrelevant, redundant, or noisy data to lower data dimensionality. The aim of feature selection is to select a subset of features with the lowest inner similarity and highest relevancy to the target class.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Iman Ahmadianfar et al.
Summary: The optimization field is plagued by metaphor-based pseudo-novel or fancy optimizers, with limited contributions to the optimization process. This study introduces a novel metaphor-free population-based optimization method called RUNge Kutta optimizer (RUN) based on mathematical foundations, showing promising results in mathematical tests and engineering problems. The RUN algorithm utilizes slope variations computed by the RK method for global optimization, demonstrating superior exploration and exploitation tendencies, fast convergence rate, and local optima avoidance.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Yun Liu et al.
Summary: The newly proposed MCSSA algorithm, based on the original SSA algorithm, uses chaotic exploitative trends and a multi-population structure to improve its performance. This new strategy significantly enhances the speed of convergence and search ability, resulting in better solutions compared to the basic SSA.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Biology
Jayashree Piri et al.
Summary: A new MOQBHHO technique is proposed, utilizing KNN method to extract optimal feature subsets, with crowding distance used as a third criterion. Experimental findings show that this method outperforms other existing multi-objective techniques, effectively finding non-dominated feature subsets.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Biology
Gehad Ismail Sayed et al.
Summary: A new melanoma skin cancer prediction model is proposed in this paper, which overcomes class imbalance by using random over-sampling and data augmentation techniques, achieving an accuracy of 98.37% and sensitivity of 100%, demonstrating high competitiveness.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Engineering, Chemical
Abdelhady Ramadan et al.
Summary: Clean energy resources, especially photovoltaic energy, are a global concern. The study proposes an improved bald eagle search algorithm for estimating PV model parameters. Results show that the modified models are more accurate than conventional models, and IBES outperforms original BES and other algorithms.
Article
Engineering, Multidisciplinary
Jiaze Tu et al.
Summary: This paper introduces a new stochastic optimizer called the Colony Predation Algorithm (CPA) based on the predation behavior of animals in nature, utilizing mathematical mapping to improve algorithm performance by simulating strategies used by animal hunting groups. The proposed CPA demonstrates competitive performance in optimizing engineering problems and will provide publicly available source code after publication.
JOURNAL OF BIONIC ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
H. A. Alsattar et al.
ARTIFICIAL INTELLIGENCE REVIEW
(2020)
Article
Computer Science, Artificial Intelligence
Qian Fan et al.
Article
Computer Science, Artificial Intelligence
Afshin Faramarzi et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Abhishek Kumar et al.
SWARM AND EVOLUTIONARY COMPUTATION
(2020)
Article
Automation & Control Systems
Essam H. Houssein et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2020)
Article
Computer Science, Theory & Methods
Shimin Li et al.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2020)
Article
Computer Science, Artificial Intelligence
Akash Saxena et al.
APPLIED SOFT COMPUTING
(2019)
Article
Computer Science, Artificial Intelligence
Youwei Wang et al.
APPLIED INTELLIGENCE
(2019)
Article
Engineering, Multidisciplinary
Huiling Chen et al.
APPLIED MATHEMATICAL MODELLING
(2019)
Review
Biology
Beatriz Remeseiro et al.
COMPUTERS IN BIOLOGY AND MEDICINE
(2019)
Article
Computer Science, Theory & Methods
Ali Asghar Heidari et al.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2019)
Article
Computer Science, Artificial Intelligence
Ali W. Mohamed et al.
SWARM AND EVOLUTIONARY COMPUTATION
(2019)
Article
Computer Science, Interdisciplinary Applications
Mehak Kohli et al.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2018)
Article
Automation & Control Systems
Yongquan Zhou et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2017)
Article
Computer Science, Information Systems
Ying Ling et al.
