Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations by Marzieh Faridi Masouleh, Ali Harounabadi, Asal Sayyad

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Enhancing the decision optimization of interaction design in sustainable healthcare with improved artificial bee colony algorithm and generative artificial intelligence. by Shuhui Yu, Xin Guan, Xiaoyan Peng, Yanzhao Zeng, Zeyu Wang, Xinyi Liang, Tianqiao Qin, Xiang Zhou

“…This study proposes an improved Artificial Bee Colony (ABC) algorithm aimed at optimizing decision-making models in the field of digital health. …”
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Intelligent irrigation strategy model for farmland using dung beetle optimization-random forest algorithms by Wenwen Hu, Yong Liu, Jun An, Shipu Xu, Zhiwen Zhou, Mingming An, Xiaokun Guo, Xiang Ma, Wenfei Jiang, Yunsheng Wang

“…This study proposes an optimized machine learning prediction model using the Dung Beetle Optimization-Random Forest (DBO-RF) algorithm, thus improving irrigation predictability. …”
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Models and Algorithms of Conflict Detection and Scheduling Optimization for High-Speed Train Operations Based on MPC by Zhihui Wang, Yonghua Zhou, Deng Liu

“…Compared with the general-speed railway transportation, the high-speed railway transportation requires a timely and automatic adjustment capability in the centralized traffic control (CTC) system. In order to improve the capability, this paper mainly explores the models and algorithms of conflict detection and scheduling optimization of high-speed train operations. …”
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Optimization Management of Storage Location in Stereoscopic Warehouse by Integrating Genetic Algorithm and Particle Swarm Optimization Algorithm by Shuhong Zhang, Xianghui Zheng, Fan Xu, Suzhen Wang, Qixia Zhang, Yuan Cao

“…At the same time, the study introduced the GA-PSO algorithm to solve the mathematical model and optimize the goods location planning. …”
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Application model of “Internet+Marketing service” virtual robot under dung beetle optimizer algorithm by HE Wei, ZHOU Yutian, YU Yang, KANG Yumeng, ZHU Meng, QIAN Xusheng

“…In order to deal with the situation of power marketing service under the new situation and improve the service of power grid in the internet era, a virtual robot model of "Internet+Marketing service" was designed by the dung beetle optimizer (DBO) algorithm. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“…This study investigates the impact of multiple optimization algorithms within transfer learning, employing EfficientNet models for the classification of agricultural insects. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“…This study investigates the impact of multiple optimization algorithms within transfer learning, employing EfficientNet models for the classification of agricultural insects. …”
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State-of-the-Art Review: Models and Algorithms for Optimal Power System Design, Stabilization, and Reliability Enhancement by Senele Njabulo Zwane, Bongumsa Mendu, Bessie Baakanyang Monchusi

“…In this study, a state-of-the-art review of models and algorithms for optimal power system design, stabilization, and reliability enhancement is conducted. …”
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A multi-objective optimization-based ensemble neural network wind speed prediction model by Haoyuan Ma, Chang Liu, Ziyuan Qiao, Yuan Liang, Hongqing Wang

“…To optimize the hyperparameters of XGBoost, we introduce a novel algorithm named NS-ADPOA, which adopts a bi-objective optimization strategy targeting both Mean Squared Error and model complexity. …”
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Hybrid RSA-ROA Scheduling Algorithm for Minimization of Power Loss and Improving the Renewable with Sustainable Energy Harvesting in Power System by Cuddapah Anitha, Virendra Swaroop Sangtani, Ajay Kumar Bansal, Mahaveerakannan R., R. Rajesh Sharma, Saravanan M. S.

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Modelling and optimization of well hole cleaning using artificial intelligence techniques by Nageswara Rao Lakkimsetty, Hassan Rashid Ali Al Araimi, G. Kavitha

“…This study aims to improve the accuracy and practicality of hole cleaning assessment by applying Artificial Intelligence (AI) techniques, specifically Artificial Neural Networks (ANN) and Genetic Algorithms (GA), to predict downhole parameters and optimize drilling processes. …”
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Competitive Elimination Improved Differential Evolution for Wind Farm Layout Optimization Problems by Sichen Tao, Yifei Yang, Ruihan Zhao, Hiroyoshi Todo, Zheng Tang

“…Therefore, metaheuristic algorithms with inherent discrete characteristics like genetic algorithms (GAs) and particle swarm optimization (PSO) have been extensively developed into current state-of-the-art WFLOP optimizers. …”
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Optimization Strategy of Microgrid Hierarchical Scheduling Considering Electric Vehicles User Satisfaction Degree by Huiqun YU, Shen YIN, Hao ZHANG, Shanshan SHI, Daogang PENG, Guoshun CAI

“…Renewable energy is used to support the load of the microgrid in the source storage layer, and the excess part is absorbed by the dispatchable electric vehicle, which makes the comprehensive cost of the microgrid minimized. The improved ant lion algorithm is used to solve the model of the source storage layer. …”
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An improved multiclass classification of acute lymphocytic leukemia using enhanced glowworm swarm optimization by Saranya N, Kalamani M

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An Improved NSGA-III Algorithm for Scheduling Ships Arrival and Departure the Main Channel of Tianjin Port by Luzhen Ren, Yuzheng Li, Shibo Zhou

“…The improved NSGA-III algorithm employs the Metropolis criterion in the simulated annealing algorithm in conjunction with the small habitat technique to optimize the initial population of NSGA-III. …”
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Optimization method improvement for nonlinear constrained single objective system without mathematical models by HOU Gong-yu, XU Zhe-dong, LIU Xin, NIU Xiao-tong, WANG Qing-le

“…In addition, samples are needed to solve such system optimization problems. Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. …”
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Optimization of a photovoltaic/wind/battery energy-based microgrid in distribution network using machine learning and fuzzy multi-objective improved Kepler optimizer algorithms by Fude Duan, Mahdiyeh Eslami, Mohammad Khajehzadeh, Ali Basem, Dheyaa J. Jasim, Sivaprakasam Palani

“…The variables are microgrid optimal location and capacity of the HMG components in the network which are determined through a multi-objective improved Kepler optimization algorithm (MOIKOA) modeled by Kepler’s laws of planetary motion, piecewise linear chaotic map and using the FDMT. …”
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Soft actor-critic algorithm and improved GNN model in secure access control of disaggregated optical networks by Zhenqian Zhao, Yuhe Wang

“…Key findings include: (1) Threat Detection: GESAC achieves an F1-score of 0.915–0.931 in identifying physical-layer attacks such as wavelength eavesdropping and cross-domain privilege escalation, with a false positive rate as low as 0.7%. (2) Resource Optimization: Compared to greedy strategies, GESAC improves wavelength utilization variance by up to 58.9% and reduces end-to-end latency standard deviation by up to 57.7% under high-load conditions. (3) Policy Robustness: In scenarios involving topological mutations, the model increases Pareto frontier coverage by over 100% and reduces policy entropy decay rate by more than 65%, indicating strong robustness. (4) Scalability: At a scale of 100,000 network nodes, GESAC achieves a single-step decision latency of just 25.6µs and significantly reduces communication overhead, demonstrating excellent scalability. …”
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Research on Reactive Power Optimization Strategy under the Intelligent Improvement Model of the Distribution Network by Menglin Yu

“…In order to improve the reactive power optimization effect of the distribution network, this paper combines the multiagent deep reinforcement learning algorithm to analyze the reactive power optimization strategy of the distribution network and constructs an intelligent optimization model. …”
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