GPTOR: Gridded GA and PSO-based task offloading and ordering in IoT-edge-cloud computing by Arezou Mahmoudi, Leili Farzinvash, Javid Taheri

“…In this study, we propose an improved genetic algorithm for joint task offloading and ordering to distribute tasks across the IoT, edge, and cloud layers. …”
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Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models by Mohammad Bazrafshan, Kourosh Sayehmiri

“…A combination of statistical models for feature selection and machine learning algorithms for prediction was used, with Random Forest showing the best performance. …”
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A Novel Seal Packaging Structure Applied in Sub Miniature Push-On Connector Based on Ni47Ti44Nb9 Shape Memory Alloy Seal Ring by Yang Hai, Cong Lu

“…Finally, to reduce the seal packaging leakage rate, the structural parameters of the seal ring are further optimized with an improved Adaptive Genetic Algorithm (IAGA), and the efficiency of the IAGA is verified through comparison with the conventional Adaptive Genetic Algorithm (AGA).…”
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An Enhanced Measurement of Epicardial Fat Segmentation and Severity Classification using Modified U-Net and FOA-guided XGBoost by Rajalakshmi K, Palanivel Rajan S

“…The proposed method integrates a modified squeeze-and-excitation (MSE) block and a multi-scale dense (MS-D) convolutional neural network (CNN) to improve feature extraction. In addition, a metaheuristic optimization algorithm from falcon optimization algorithm (FOA) is used for efficient feature selection. …”
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Optimal Coverage Path Planning for Unmanned Surface Vehicles Using Flexible Formation Tracking Control by Minsung Park, Bo Woo Nam

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Coupling Artificial Intelligence with Proper Mathematical Algorithms to Gain Deeper Insights into the Biology of Birds’ Eggs by Valeriy G. Narushin, Natalia A. Volkova, Alan Yu. Dzhagaev, Darren K. Griffin, Michael N. Romanov, Natalia A. Zinovieva

“…Considering the geometry of egg profiles, we revisit the Preston–Biggins egg model, the Hügelschäffer’s model, universal egg models, principles of egg universalism and “The Main Axiom”, proposing a series of postulates to evaluate the legitimacy and practical application of various mathematical models. …”
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Optimizing electric vehicle energy consumption prediction through machine learning and ensemble approaches by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adeeb Noor, Sufyan Ali Memon

“…The K-Nearest Neighbors (KNN) algorithm is employed as the base model, with hyperparameter optimization performed using GridSearchCV, RandomizedSearchCV, Optuna, and Particle Swarm Optimization (PSO). …”
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Smart home power management algorithm using real-time model predictive control for a stand-alone PV system with battery energy storage by Aziz Watil

“…The overall battery efficiency reached 96.45%, demonstrating the algorithm’s ability to optimize power flow, ensure a reliable energy supply, and maintain battery safety under varying weather conditions.…”
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Comprehensive Fault Location on Transmission Lines Considering Variation in Line Parameters and Saturation in Current Transformers by Duy C. Huynh, Loc D. Ho

“…Precise and rapid fault location on transmission lines is a cornerstone for enhancing the reliability and cost-efficiency of power systems. This paper proposes an innovative approach to a fault location by solving an optimization problem. …”
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Facility location problem for senior centers in an upcoming super-aging society by Eun Hak Lee, Jonghwa Jeong

“…This study aims to address the facility location problem for senior centers in upcoming super-aging societies. An optimization model is developed using a genetic algorithm to determine the optimal locations of senior centers. …”
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Research on Offshore Vessel Trajectory Prediction Based on PSO-CNN-RGRU-Attention by Wei Liu, Yu Cao

“…This study utilizes real Automatic Identification System (AIS) data and applies the PSO algorithm to optimize the model and determine the optimal parameters, using a sliding window method for input and output prediction. …”
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Energy optimization through morphing blade design under structural constraints: a case study on the NREL 1.5 MW wind turbine by Najafian Arezoo, Jahangirian Alireza

“…The morphing process is modeled using an m-degree shape function and optimized through a Genetic Algorithm (GA) to maximize power generation while minimizing structural displacement and thrust forces. …”
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Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction by Ruijie Zhu, Fengtian Yang, Xiaocheng Zhou, Jiao Tian, Yongxian Zhang, Miao He, Jingchao Li, Jinyuan Dong, Ying Li

“…Additionally, including sampling time in the data sets significantly improves the model's predictive performance. However, it is important to note that the model's predictive performance varies across different hot spring and indicators type, highlighting the importance of identifying optimal indicators for specific scenarios. …”
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Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…Finally, the CADHDD-SFLNHM model implements the pelican optimization algorithm (POA) method to fine-tune the hyperparameters involved in the CNN-BiGRU-A method. …”
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Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction by Liana Toderean, Mihai Daian, Tudor Cioara, Ionut Anghel, Vasilis Michalakopoulos, Efstathios Sarantinopoulos, Elissaios Sarmas

“…However, the prediction accuracy of federated learning models tends to diminish when dealing with non-IID data highlighting the need for adaptive hyperparameter optimization strategies to improve performance. …”
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A Novel SOH Estimation Method for Lithium-Ion Batteries Based on the PSO–GWO–LSSVM Prediction Model with Multi-Dimensional Health Features Extraction by Xu He, Zhengpu Wu, Jinghan Bai, Junchao Zhu, Lu Lv, Lujun Wang

“…With strong generalization and robustness, least squares support vector machine (LSSVM) is widely applied to nonlinear computations and function approximation. To improve LSSVM model accuracy and efficiency, this paper develops a novel prediction model that uses particle swarm optimization (PSO) combined with grey wolf optimization (GWO) algorithms to optimize the LSSVM model. …”
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Renewable Energy Consumption Strategies for Electric Vehicle Aggregators Based on a Two-Layer Game by Xiu Ji, Mingge Li, Zheyu Yue, Haifeng Zhang, Yizhu Wang

“…For the complexity of large-scale scheduling, this paper introduces the A2C (Advantage Actor-Critic) reinforcement learning algorithm, which combines the value network and the strategy network synergistically to optimize the real-time scheduling process. …”
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Mixed Time/Event-Triggered Model Predictive Tracking Control for Networked Mobile Robots by Huixin Liu, Yonghua Lai, Hongsong Lian, Guobin Wang, Dongsheng Zheng

“…The MPC algorithm is developed based on the auxiliary optimization problem (OP), which is constrained by linear matrix inequalities. …”
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Optimization Study of Multidimensional Computational Model for Distribution Network Cable Fault Location and Hidden Danger Warning System in Smart Grid Environment by Xin Li, Jiyou Wang, Minghui Liu

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Balanced operation strategies of district heating systems based on dynamic hydraulic-thermal modeling by Xiaojie Lin, Ning Zhang, Zheng Luo, Encheng Feng, Wei Zhong

“…For the primary side network in the various operation conditions, the dynamic hydraulic-thermal model is established. The heating supply imbalance of the primary side return temperatures among different heating substations is defined and optimized based on the dynamic hydraulic-thermal model and the particle swarm optimization algorithm. …”
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