Hybrid strategy enhanced crayfish optimization algorithm for breast cancer prediction by Yu-Jiong Li

“…When combined with Extreme Learning Machine (ELM) and applied to the Wisconsin breast cancer dataset, the MSCOA-ELM model achieved 100% accuracy and F1 score, a 28.9% improvement over the baseline ELM, demonstrating the algorithm’s efficiency and generalization ability in solving practical optimization problems.…”
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Length Optimization of MEP Pipeline Integrated Modular Based on Genetic Algorithm by Xuefeng Zhao, Qiantai Yang, Gangwen Yan, Xiongtao Fan, Yinghui Yang, Huizhong Zhang, Song Chen

“…This paper discusses the advantages and limitations of the proposed method and suggests future directions for further optimizing the algorithm and improving module partitioning. …”
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Optimization of the Offshore Wind Turbines Layout Using Cuckoo Search Algorithm by Ibrahim Abdulwahab, Solomon Andrew Onazi, Gideon Rimamfate, Akande Abdulwasiu, Abubakar Umar, N.A Iliyasu

“…After-which a cuckoo search algorithm technique is employed in the wind farm model to optimize the optimization problem (minimizing the wake effect while improving power output and cost). …”
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Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…This methodology is compared against the hurricane optimization algorithm, the sine cosine algorithm, and the salp swarm optimization algorithm. …”
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Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks by S. Yazhinian, S. Famila, P. Jose, Mahendar A, Sofia R

“…It is seen that the proposed RadB_SOA achieves 12.4 % of transmission error, 14.6 % of ranging error, 96.3 % of localization coverage, 98.65 % of PDR, and 21.56 % of energy consumption. • The Radial Bias-Seeker Optimization Algorithm (RadB_SOA) suggested enhances the precision in target localization and optimizes energy usage in wireless sensor networks. • Simulation outcomes reveal improved tracking accuracy, minimized transmission and ranging errors, as well as increased localization coverage over current techniques. • The research presents an extensive evaluation of particle count fluctuations in RBSO, demonstrating enhanced positioning speed and precision with network efficiency.…”
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Research on Two-Stage Energy Storage Optimization Configurations of Rural Distributed Photovoltaic Clusters Considering the Local Consumption of New Energy by Yang Liu, Dawei Liu, Keyi Kang, Guanqing Wang, Yanzhao Rong, Weijun Wang, Siyu Liu

“…Taking a Chinese village as an example, the proposed model is optimized with an improved particle swarm optimization algorithm. …”
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The Significant Effects of Threshold Selection for Advancing Nitrogen Use Efficiency in Whole Genome of Bread Wheat by Mohammad Bahman Sadeqi, Agim Ballvora, Said Dadshani, Md. Nurealam Siddiqui, Mohammad Kamruzzaman, Ahossi Patrice Koua, Jens Léon

“…By incorporating the neural network algorithm, it is possible to improve the reliability of FDR threshold and increase the probability of identifying true genetic associations while minimizing the risk of false positives in GWAS results.…”
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MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design by Anoop Raghuvanshi, Abhinav Sharma, Abhishek Kumar Awasthi, Abhishek Sharma, Rahul Singhal, Kim Soon Chong, Sew Sun Tiang, Wei Hong Lim

“…This paper presents the modified arithmetic optimization algorithm (MAOA), a swift and effective optimization algorithm specifically designed for electromagnetic applications. …”
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Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment by Xun Lu, Junlei Liu, Xinmiao Liu, Jun Liu, Lingxue Lin

“…The methodology integrates an adaptive step size algorithm within a dynamic projected primal–dual distributed optimization framework, eliminating manual parameter tuning requirements while ensuring theoretical convergence guarantees through Lyapunov stability analysis. …”
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A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing by Yacine Bourek, El Mouatez Billah Messini, Chouaib Ammari, Mohamed Guenoune, Boulerbah Chabira, Bipul Krishna Saha

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Improving Forest Above-Ground Biomass Estimation Accuracy Using Multi-Source Remote Sensing and Optimized Least Absolute Shrinkage and Selection Operator Variable Selection Method by Er Wang, Tianbao Huang, Zhi Liu, Lei Bao, Binbing Guo, Zhibo Yu, Zihang Feng, Hongbin Luo, Guanglong Ou

“…The Lasso-GA method results in an ETR model with an R² of 0.73 and an RMSE of 16.70 Mg/ha. Compared to the optimal SGBoost model with the Lasso variable selection method (R² of 0.69, RMSE of 18.63 Mg/ha), the VIF-Lasso method improves R² by 0.06 and reduces RMSE by 2.15 Mg/ha, while the Lasso-GA method improves R² by 0.04 and reduces RMSE by 1.93 Mg/ha. …”
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Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis? by Mohamed Hassan, Aleksandar Vakanski, Boyu Zhang, Min Xian

“…These sharpness-based optimizers have shown improvements in model generalization compared to conventional stochastic gradient descent optimizers and their variants on general domain image datasets, but they have not been thoroughly evaluated on medical images. …”
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Improving detection of Parkinson’s disease with acoustic feature optimization using particle swarm optimization and machine learning by Elmoundher Hadjaidji, Mohamed Cherif Amara Korba, Khaled Khelil

“…This study aims to refine PD detection systems by introducing customized weighting to acoustic features, adjusting their significance based on their correlation with the disease and the classification algorithm utilized. The particle swarm optimization algorithm is employed for this purpose, with the Oxford PD dataset serving as the source data for training and validation. …”
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Research on Multi-Target Point Path Planning Based on APF and Improved Bidirectional RRT* Fusion Algorithm by Zijian Bian, Gang Li, Xizheng Wang

“…This study also aims to improve the RRT* algorithm by using optimization strategies such as bidirectional sampling and adding an adaptive target bias strategy to improve its efficiency in obtaining global paths. …”
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Multi-AGV multitask collaborative scheduling based on an improved ant colony algorithm by Yazhen Zhu, Qing Song, Meng Li

“…This paper establishes a mathematical model with the optimization objective of minimizing the overall running time of material distribution tasks and proposes an improved ant colony algorithm to optimize the model. …”
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Research on Collaborative Optimization Strategy of Railway Signal Nonlinear Control System Based on BBO Algorithm and Multi-objective Optimization by Xue Li, Yixuan Yang, Zheng Li, Hui He

“…Specifically, it sets a population size of 50, a maximum number of iterations of 200, a migration rate dynamically adjusted between 0.6-0.9, and an adaptive mutation rate of 0.01-0.05, using root mean square error and response time as performance evaluation metrics for parameter optimization. Experimental data show that compared to traditional methods, this strategy can increase the average operating speed of trains by 15%, reduce signal delays by 20%, and improve system robustness indicators by 18.5%, achieving a collaborative enhancement of efficiency and safety while ensuring stable operation, thus providing an engineering-valued solution for the intelligent upgrade of railway transport.…”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…In addition, it examines 2,000 random surface soil samples, ranging from 0 to 20 cm, that were optimized using genetic algorithms (GA), particle swarm optimization (PSO), and Optuna. …”
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Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

“…The focus is on maximizing the monitored area while minimizing energy usage. A Scalable coverage-based particle swarm optimization (SCPSO) algorithm integrates a probabilistic coverage model based on Euclidean distance to detect coverage gaps and guide the optimal positioning of nodes, ensuring that each target within the region of interest is covered by at least one sensor. …”
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An innovative coverage optimization method for smart information monitoring in agricultural IoT using the multi-strategy Pelican optimization algorithm by Wei Chen, Qike Cao, Bingyu Cao, Bo Jin

“…Comparative experiments with Improved Artificial Bee Colony Algorithm (IABC), Chaotic Adaptive Firefly Optimization Algorithm (CAFA), Adaptive Particle Swarm Optimization (APSO), and Lévy Flight Strategy Chaotic Snake Optimization Algorithm (LCSO) demonstrate that MSPOA improves network coverage by 5.85%, 11.33%, 21.05%, and 20.66%, respectively. …”
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Lightweight Apple Leaf Disease Detection Algorithm Based on Improved YOLOv8 by LUO Youlu, PAN Yonghao, XIA Shunxing, TAO Youzhi

“…To reduce the incidence of apple diseases and increase fruit yield, developing efficient and fast apple leaf disease detection technology is of great significance. An improved YOLOv8 algorithm was proposed to identify the leaf diseases that occurred during the growth of apples.…”
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