Low-Power Portable System for Power Grid Foreign Object Detection Based on the Lightweight Model of Improved YOLOv7 by Yonghuan He, Rong Wu, Chao Dang

“…Foreign objects caught and entangled on power grid transmission lines, power towers and other equipment can pose potential threats to the power system. The detection algorithm for foreign objects in the power grid cannot achieve the optimal balance in terms of accuracy and efficiency. …”
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Design and optimization of an open personalized human-computer interaction system for New Year Painting based on the learner's model by Zaozao Guo, Muhamad Firdaus Ramli, Wenpeng Zhang

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Hybrid Feature Selection and Classifying Stages through Electrocardiogram (ECG) Signal for Heart Disease Prediction by Babu Kumar, Radhakrishnan Soundararajan, Kanimozhi Natesan, Roobini Maridhas Santhi

“…In order to choose the best features, a modified chicken swarm optimization algorithm (MCSO) was proposed. Aberrant waves caused by cardiac ailments impacted the dataset patients, according to the suggested research’s unique machine learning methods of multi-module neural network system (MMNNS). …”
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Improving Event Data in Football Matches: A Case Study Model for Synchronizing Passing Events with Positional Data by Alberto Cortez, Bruno Gonçalves, João Brito, Hugo Folgado

“…Three datasets were used to perform this study: a dataset created by applying a custom algorithm that synchronizes positional and event data, referred to as the optimized synchronization dataset (OSD); a simple temporal alignment between positional and event data, referred to as the raw synchronization dataset (RSD); and a manual notational data (MND) from the match video footage, considered the ground truth observations. …”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

“…To address this issue, this paper proposes an optimized YOLOv8n algorithm, incorporating a C2f-DynamicConv optimization module. …”
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Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data by Zaharaddeen Karami Lawal, Ali Aldrees, Hayati Yassin, Salisu Dan'azumi, Sujay Raghavendra Naganna, Sani I. Abba, Saad Sh. Sammen

“…The study had limitations, such as the absence of advanced optimization or dimensionality reduction. In conclusion, it demonstrated that an ensemble model with optimized hyperparameters could classify river water quality more effectively than individual models, contributing to the advancement of sustainable development goals (SGD) related to water access.…”
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Bio inspired multi agent system for distributed power and interference management in MIMO OFDM networks by R. Kanmani, S. Mary Praveena

“…To address these limitations, this work proposes a novel bio-inspired Termite Colony Optimization-based Multi-Agent System (TCO-MAS) integrated with an LSTM model for predictive adaptability. …”
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Multiscale Feature Modeling and Interpretability Analysis of the SHAP Method for Predicting the Lifespan of Landslide Dams by Zhengze Huang, Yuqi Bai, Hengyu Liu, Yun Lin

“…This study proposes a hybrid CNN–Transformer model optimized using the Improved Black-Winged Kite Algorithm (IBKA) aimed at improving the accuracy of landslide dam lifespan prediction by combining local feature extraction with global dependency modeling. …”
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Design and prototyping of a magnetically and hydrodynamically suspended blood pump via multiobjective optimization by Reza Sahebi-Kuzeh Kanan, Hanieh Niroomand-Oscuii, Habib Badri Ghavifekr, Farzan Ghalichi

“…A set of 290 simulations was performed using a Design of Experiments approach, leading to the development of advanced Response Surface Models via Kriging and Genetic Aggregation. Subsequently, a Multi-Objective Genetic Algorithm was employed to maximize outlet pressure and minimize shear stress simultaneously. …”
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Application of artificial intelligence and red-tailed hawk optimization for boosting biohydrogen production from microalgae by Hegazy Rezk, Ali Alahmer, Abdul Ghani Olabi, Enas Taha Sayed

“…Subsequently, the red-tailed hawk algorithm (RTH) is used to determine the optimal values for the process parameters, corresponding to maximum hydrogen yield. …”
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Fire spread simulations using Cell2Fire on synthetic and real landscapes by Minho Kim, Cristobal Pais, Marta C. Gonzalez

“…In response, we used two optimization methods to improve the simulation’s accuracy. …”
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Optimization of Fused Deposition Modeling Parameters for Mechanical Properties of Polylactic Acid Parts Based on Kriging and Cuckoo Search by Yuan Yang, Yiyang Wang, Bowen Xue, Changxu Wang, Bo Yang

“…In response to the problems of poor mechanical properties and difficulty in selecting process parameters for fused deposition modeling (FDM), this paper analyzed the principle of FDM and proposed a parameter optimization method based on a Kriging and Cuckoo Search (CS) algorithm aimed at improving the mechanical properties of 3D printed polylactic acid (PLA) parts. …”
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The financial impact of human resources configuration: A quantitative analysis based on modified single candidate optimizer by Zhuozhuo Zhang, Jun Lu, Qi Wang

“…This paper presents an innovative HR optimization framework that uses a modified metaheuristic model, called the Modified Single Candidate Optimizer (MSCO) algorithm to resolve this task. …”
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Cnidaria herd optimized fuzzy C-means clustering enabled deep learning model for lung nodule detection by R. Hari Prasada Rao, Agam Das Goswami

“…Furthermore, statistical and texture descriptors extract the significant features that aid in improving the detection accuracy. In addition, the FC2R segmentation model combines the optimized fuzzy C-means clustering algorithm and the Resnet −101 deep learning approach that effectively improves the performance of the model. …”
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Dynamic Agricultural Pest Classification Using Enhanced SAO-CNN and Swarm Intelligence Optimization for UAVs by Shiwei Chu, Wenxia Bao

“…Key contributions include: (1) A hybrid SAO-CNN architecture that dynamically adjusts convolution kernels and leverages unlabeled data through self-supervised learning, improving adaptability to lighting and background variations. (2) A UAV swarm intelligence framework optimized via bio-inspired algorithms, reducing flight time by 29.2% and energy consumption by 32% compared to non-optimized systems. (3) Superior performance with 91.2% classification accuracy, 0.89 recall, and 32 FPS processing speed, outperforming state-of-the-art models (e.g., YOLO variants, ResNet, and ConvLSTM) in both static and dynamic scenarios. …”
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Multiobjective Optimization of Stress-Release Boot of Solid Rocket Motor under Vertical Storage Based on RBF Model by Qiuwen Miao, Huihui Zhang, Zhibin Shen, Weiyong Zhou

“…To optimize a SRM with star and finocyl grain, the RBF (radial basis functions) model that satisfies the accuracy requirements was established based on parametric modeling technology and the OPLHS (Optimal Latin Hypercube Sampling) method. …”
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Synergistic Framework for Fuel Cell Mass Transport Optimization: Coupling Reduced-Order Models with Machine Learning Surrogates by Shixin Li, Qingshan Liu, Yisong Chen

“…The combination of the one-dimensional model, the surrogate model, and the genetic algorithm can effectively improve the optimization efficiency.…”
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Dynamic Sensor-Based Data Management Optimization Strategy of Edge Artificial Intelligence Model for Intelligent Transportation System by Nu Wen, Ying Zhou, Yang Wang, Ye Zheng, Yong Fan, Yang Liu, Yankun Wang, Minmin Li

“…To address these issues, we propose an automatic sensor-based data loading and unloading optimization strategy for algorithm models. This strategy is designed for artificial intelligence (AI) application systems that leverage edge computing. …”
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Retrieval of Leaf Area Index for Wheat and Oilseed Rape Based on Modified Water Cloud Model and SAR Data by Xiyue Yang, Wangfei Zhang, Armando Marino, Han Zhao, Wei Kang, Zhengyong Xu

“…The proposed MWCM parameters were calibrated using an iterative optimization algorithm named the Levenberg–Marquardt (LM) algorithm. …”
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Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

“…This study examines the application of advanced machine learning techniques, combined with metaheuristic optimization methods, to improve predictive models for intradialytic hypotension (IDH) in hemodialysis patients. …”
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