Sinkhole attack detection based on fusion of ACO and P2P trust model in WSN by Wumaier HENIGULI

“…For the Sinkhole attack problem of wireless sensor network（WSN），a detection algorithm based on fusion of ant colony optimization（ACO）and P2P trust model was proposed.Firstly，ant colony optimization algorithm was used to detect the existence of a Sinkhole attack in route and generate the alarm information of sensor nodes. …”
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Optimization Design of Diaphragm Profile based on Kriging Model by Geng Hu, Zhigang Chen, Ding Zhang

“…Finally，the initial Kriging model is updated with MP （minimizing the predicted objective function） infill-sampling criterion and genetic algorithm，and the optimal design is obtained via the final Kriging model. …”
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Optimizing Feature Selection and Machine Learning Algorithms for Early Detection of Prediabetes Risk: Comparative Study by Mahmoud B Almadhoun, MA Burhanuddin

“…ConclusionsIt is demonstrated in this research that optimized ML models, especially random forest and XGBoost, are effective tools for assessing early prediabetes risk. …”
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A Comprehensive Review of AI Algorithms for Performance Prediction, Optimization, and Process Control in Desalination Systems by Mahmoud Ibnouf, Hadi Jaber, Hadil Abukhalifeh, Mohammed Ghazal, Mohamad Ramadan, Mohammad Alkhedher

“…In order to improve efficiency, AI algorithms are also used in desalination modelling to optimize system parameters and aid in process control. …”
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OPTIMIZED CLUSTER-BASED COMMUNICATION IN MWSN USING FUZZY NEURAL NETWORKS AND CROW SEARCH ALGORITHM by S Archana, V Jayapradha

“…The CSA algorithm is used to guide cluster formation and CH selection by modeling the intelligent behavior of crows, resulting in energy-efficient partitioning of the network. …”
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VERIFICATION OF THE PARSEC METHOD AND OPTIMIZATION OF NACA-4412, SG-6043 USING GENETIC ALGORITHM IN MATLAB by Raheem Alhamdawee, M. Manzoor Hussain

“…The study also includes the improvement of the aerodynamic design of both airfoils through the use of a genetic algorithm which is coded and run in MATLAB, with the PARSEC parameters used as the base for optimization. …”
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Self-optimization of Wind Turbine Variable-pitch Control Parameters Based on Adaptive Genetic Algorithm by CHANG Sheng, WAN Yubin, JIANG Tao

“…The author first described the basic principle of variable-pitch control system; then based on the genetic algorithm, planned and designed constraint conditions for different wind turbine models, covering initial population selection, self-optimization algorithm constraints and adaptability function design; and finally compared and analyzed the response curve, simulation and field operation results of the traditional parameter tuning method and self-optimization parameter tuning method. …”
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Enhancing 5G Vehicular Edge Computing Efficiency with the Hungarian Algorithm for Optimal Task Offloading by Mohamed Kamel Benbraika, Okba Kraa, Yassine Himeur, Khaled Telli, Shadi Atalla, Wathiq Mansoor

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Multi-Energy Optimal Dispatching of Port Microgrids Taking into Account the Uncertainty of Photovoltaic Power by Xiaoyong Wang, Xing Wei, Hanqing Zhang, Bailiang Liu, Yanmin Wang

“…Then, a planning model centered on economy is established. Through multi-energy coordinated optimization, supply–demand balance and cost control are achieved. …”
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A Study on Container Storage Optimization in Yards Based on a Hyper-Heuristic Algorithm with a Q-Learning Mechanism by Lifen Chen, Jiajun Lin, Shihao Xu

“…The objective is to minimize the carbon emissions and the number of container rehandling operations in ports, for which a mixed-integer linear programming model is built. Both heuristic algorithms and hyper-heuristic algorithms are employed to optimize the container storage plan, and their applicability in storage optimization is compared. …”
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Prediction Method of Lithology Log Based on XGBoost Algorithm by CHU Qingjun, GE Yunlong, TONG Maosong, WANG Yan, AN Lyuxing, YU Chuanwu, JIA Xin

“…Noise is added to the samples to improve the robustness of the model. The 8 hyperparameters of the XGBoost algorithm are optimized using grid search. …”
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RE-YOLO: An apple picking detection algorithm fusing receptive-field attention convolution and efficient multi-scale attention. by Jinxue Sui, Li Liu, Zuoxun Wang, Li Yang

“…Finally, the loss function of YOLOv8 is improved using the Wise Intersection over Union (WIOU) function, which not only simplifies the gradient gain assignment mechanism and improves the ability to detect targets of different sizes, but also accelerates the model optimization. …”
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Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration by Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang

“…This algorithm adeptly balances resource expenditures with model quality, employing Lyapunov-driven optimization theory to convert long-term stochastic challenges into short-term deterministic resolutions. …”
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GENETIC ALGORITHM-PID CONTROLLER FOR MODEL ORDER REDUCTION PANTOGRAPHCATENARY SYSTEM by Nasir A. Al-Awad, Izz K. Abboud, Muaayed F. Al-Rawi

“…Then, in this paper, we current an active manipulate of the minimize order model of pantograph-catenary system .The proposed manipulate approach implements an optimization technique, like particle swarm (PSO), the usage of a frequent approximation of the catenary equal stiffness. …”
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Reverse Logistics Network Optimization for Retired BIPV Panels in Smart City Energy Systems by Cimeng Zhou, Shilong Li

“…Meanwhile, the multi-level recycling network which covers “building points-regional transfer stations-specialized distribution centers” is designed in the research, the Pareto solution set is solved by the improved NSGA-II algorithm, a “1 + 1” du-al-core construction model of distribution center and transfer station is developed, so as to minimize the total cost and life cycle carbon footprint of the logistics network. …”
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Engineering project management technology based on visual simulation module and particle swarm optimization by Hua Tian

“…The particle swarm multi-objective optimization algorithm performed well in reducing project cost prediction errors. …”
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Reinforcing long lead time drought forecasting with a novel hybrid deep learning model: a case study in Iran by Mahnoosh Moghaddasi, Mansour Moradi, Mahdi Mohammadi Ghaleni, Zaher Mundher Yaseen

“…Key parameters of the DFFNN, including the number of neurons and layers, learning rate, training function, and weight initialization, were optimized using the WSO algorithm. The model’s performance was validated against two established optimizers: Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems by Yongxin Li, Ali Basem, As'ad Alizadeh, Pradeep Kumar Singh, Saurav Dixit, Hanaa Kadhim Abdulaali, Rifaqat Ali, Pancham Cajla, Husam Rajab, Kaouther Ghachem

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The Elitist Non-Dominated Sorting Crisscross Algorithm (Elitist NSCA): Crisscross-Based Multi-Objective Neural Architecture Search by Zhihui Chen, Ting Lan, Dan He, Zhanchuan Cai

“…This paper proposes a multi-objective evolutionary algorithm called the elitist non-dominated sorting crisscross algorithm (elitist NSCA) and applies it to neural architecture search, which considers two optimization objectives: the accuracy and network parameters. …”
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Time and Covariance Threshold Triggered Optimal Uncooperative Rendezvous Using Angles-Only Navigation by Yue You, Hua Wang, Christophe Paccolat, Volker Gass, Jean-Philippe Thiran, Jiu Ren Li

“…In the context of Yamanaka-Ankersen orbital relative motion equations, the square root unscented Kalman filter (SRUKF) AON algorithm is developed to compute the relative state estimations from a low-volume/mass, power saving, and low-cost optical/infrared camera’s observations. …”
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