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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Multi-Scenario Stochastic Optimal Scheduling for Power Systems With Source-Load Matching Based on Pseudo-Inverse Laguerre Polynomials by Jiahao Ye, Lirong Xie, Lan Ma, Yifan Bian, Chuanshi Cui

“…Firstly, to improve the accuracy and stability of wind-photovoltaic power forecasting, a novel multi-objective wind-photovoltaic forecasting model is proposed based on the Laguerre polynomial, pseudo-inverse learning, and hybrid multi-objective Runge-Kutta algorithm (HMORUN). …”
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Research on the Location-Routing Optimization of International Freight Trains Considering the Implementation of Blockchain by Zhichao Hong, Hao Shen, Wenjie Sun, Jin Zhang, Hongbin Liang, Gang Zhao

“…In this case, 43 stations in the Indo-China Peninsula are selected as origin stations, and two Chinese stations are designated terminal stations. An improved NSGA-II algorithm (ANSGAII-OD) is proposed to resolve the location-routing optimization model. …”
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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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Strength prediction and optimization for microwave sintering of large-dimension lithium hydride ceramics: GA-BP-ANN modeling by Hongzhou Yan, Huayan Chen, Wenyan Zhang, Maobing Shuai, Bin Huang

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Rejection-Free Monte Carlo Simulation of QUBO and Lechner–Hauke–Zoller Optimization Problems by Yoshihiro Nambu

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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 Configuration of Electric–Hydrogen Hybrid Energy Storage System Considering Power Grid Voltage Stability by Yunfei Xu, Yiqiong He, Hongyang Liu, Heran Kang, Jie Chen, Wei Yue, Wencong Xiao, Zhenning Pan

“…This model, applied to the IEEE-33 standard test system, utilizes the Multi-Objective Artificial Hummingbird Algorithm (MOAHA) to optimize the capacity and location of the electric–hydrogen hybrid energy storage system. …”
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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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An effectiveness of deep learning with fox optimizer-based feature selection model for securing cyberattack detection in IoT environments by Mimouna Abdullah Alkhonaini

“…Furthermore, the FOFSDL-SCD model utilizes the Fox optimizer algorithm (FOA) method for the feature selection process to select the most significant features from the dataset. …”
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Simplified Model Predictive for Controlling Circulating and Output Currents of a Modular Multilevel Converter by Abolfazl Sheybanifar, Seyed Masoud Barakati

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Harmonized Integration of GWO and J-SLnO for Optimized Asset Management and Predictive Maintenance in Industry 4.0 by A. N. Arularasan, P. Ganeshkumar, Mohammad Alkhatib, Tahani Albalawi

“…The study encompasses the application of two different advanced optimization algorithms on asset management and predictive maintenance in Industry 4.0—Grey Wolf Optimization and Jaya-based Sea Lion Optimization (J-SLnO). …”
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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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