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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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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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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Multi-objective optimization of hybrid microgrid for energy trilemma goals using slime mould algorithm by Alok Kumar Shrivastav, Soham Dutta

“…Compared to conventional metaheuristic such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), the SMA achieves a power loss reduction of 12.3% and a levelized cost of energy (LCOE) improvement of 9.8%. …”
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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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Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network by Nandita Goyal, Munesh Chandra Trivedi

“…A comparison of different metaheuristics algorithms- Particle Swarm Optimization, Shuffled Frog Leap Optimization and Fire fly algorithm for feature optimization is done based on convergence rate and efficiency.…”
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An intelligent attention based deep convoluted learning (IADCL) model for smart healthcare security by J. Maruthupandi, S. Sivakumar, B. Lakshmi Dhevi, S. Prasanna, R. Karpaga Priya, Shitharth Selvarajan

“…Afterwards, optimization in the classification process is done by the SA-HHO algorithm, which provides the optimal weight values. …”
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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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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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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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Robust multi-objective optimization for water flooding under geological uncertainty by Abobakr Sori, Mohammad Sharifi, Nooshin Jabari

“…By employing a multi-objective optimization (MOO) algorithm, we aim to minimize the sensitivity of objective functions to geological variability. …”
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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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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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A Novel Optimization Approach for Educational Class Scheduling with considering the Students and Teachers’ Preferences by Yu Chen, Mahmonir Bayanati, Maryam Ebrahimi, Sadaf Khalijian

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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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