A two stage differential evolution algorithm for parameter estimation of proton exchange membrane fuel cell by Mohammad Aljaidi, Sunilkumar P. Agrawal, Pradeep Jangir, Sundaram B. Pandya, Anil Parmar, Arpita, Ali Fayez Alkoradees, Bhargavi Indrajit Trivedi, Mohammad Khishe

“…Most traditional parameter estimation methodologies depend on optimization algorithms which are limited in their efficiency, convergence speed, and robustness. …”
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Environmental risk assessment based on multiscale spatial recurrent neural network algorithm for IoT agriculture area by M. Sofiya, M. Arulmozhi

“…The Exhaustive Traffic Information Rate (ETIR) method evaluates the marginal rate of each feature, and the AntLion Behavior Optimization (ALBO) algorithm selects the most significant features, reducing dimensionality. …”
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Autonomous UAV Path Optimization Using Genetic and Multiobjective Evolutionary Algorithms for Effective Data Retrieval in Cache-Enabled Mobile Ad-Hoc WSNs by Umair B. Chaudhry, Chris Ian Phillips

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Research on the configuration scheme and system parameter optimization of pumps in the component cooling system and sea water system for HPR1000 by Weiguang Zhao, Pei Yu, Xiaobo Zeng, Guangming Fan, Zhaoming Meng, Changqi Yan

“…Based on a mathematical model for CCS and SWS that can be utilized for optimization calculations, we propose and validate an Improved Non-dominated Sorting Genetic Algorithm II (INSGA-II) with good algorithm performance, optimizing for system design costs and total operational costs as objectives, and provide a sensitivity analysis of relevant variables. …”
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Harnessing feature pruning with optimal deep learning based DDoS cyberattack detection on IoT environment by Eunmok Yang, Sooyong Jeong, Changho Seo

“…Besides, the feature pruning process is performed using an improved pelican optimization algorithm (IPOA), which enables the choice of an optimal subset of features. …”
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Adaptive Top-K Algorithm for Medical Conversational Diagnostic Model by Yiqing Yang, Guoyin Zhang, Yanxia Wu, Zhixiang Zhao, Yan Fu

“…Additionally, the Top-K algorithm optimizes the diagnostic model through a policy network loss function, effectively reducing the number of symptoms and diseases processed and improving the system’s response speed by 1.3–1.9 times compared to the state-of-the-art differential diagnosis systems.…”
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Comprehensive improvement of energy efficiency and indoor environmental quality for university library atrium—A multi-objective fast optimization framework by Shen Xu, Yongzhong Chen, Jianlin Liu, Jian Kang, JinFeng Gao, Yuchen Qin, Wenjun Tan, Gaomei Li

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Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment by Vikas K. Soman, V. Natarajan

“…The CFOPS-BSBEA technique leverages the strengths of both steganography and encryption to provide a secure and effective approach to digital image protection. The Crayfish Optimization algorithm is used to select the most suitable pixels for steganography, ensuring that the secret image is embedded in a way that minimizes detection. …”
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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…<b>Conclusions</b>: This study underscores the potential of ML models as effective tools for assessing SSI risk, warranting further clinical exploration to improve patient outcomes. …”
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An improved Harris hawks optimizer with enhanced logarithmic spiral and dynamic factor and its application for predicting molten iron temperature in the blast furnace by Zhendong Liu, Yiming Fang, Le Liu, Shuidong Ma

“…Subsequently, IHHO‐ELSDF is subjected to a comparative analysis with 17 algorithms on the IEEE CEC2022 benchmark suite. These tests show that IHHO‐ELSDF outperforms most competitors in numerical optimization. …”
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Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

“…The Superimposed Image combined these heatmaps with the original lesion images, making it clear which parts of the lesions influenced the model’s classification. These results underscore the potential of deep learning models, optimized with the memetic algorithm, to significantly improve skin cancer detection. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Key observations include: (1) the CNN-LSTM-BMO model converges 27% faster than traditional optimization methods; (2) SHapley Additive exPlanations (SHAP) analysis reveals that temperature-related features, particularly saturation temperature, are the most influential predictors across all models; and (3) the proposed model maintains prediction accuracy even under varying operational conditions. …”
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Internet of things driven object detection framework for consumer product monitoring using deep transfer learning and hippopotamus optimization by Amnah Alshahrani, Mukhtar Ghaleb, Hany Mahgoub, Achraf Ben Miled, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Hasan Beyari, Sultan Alanazi

“…Moreover, the convolutional autoencoder (CAE) model is implemented for classification. Additionally, the hippopotamus optimization algorithm (HOA)-based hyperparameter selection model is implemented to improve the classification result of the CAE technique. …”
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SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study by Abrar Yaqoob, Navneet Kumar Verma, Mushtaq Ahmad Mir, Ghanshyam G. Tejani, Nashwa Hassan Babiker Eisa, Hind Mamoun Hussien Osman, Mohd Asif Shah

“…Abstract In this study, we propose a novel approach for breast cancer classification that integrates the Seagull Optimization Algorithm (SGA) for feature selection with the Random Forest (RF) classifier for effective data classification. …”
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Multi-Stage and Multi-Objective Optimization of Solar Air-Source Heat Pump Systems for High-Rise Residential Buildings in Hot-Summer and Cold-Winter Regions by Zhen Wang, Jiaxuan Wang, Chenxi Lv

“…When optimizing the renewable energy system configuration of residential buildings for solar-air source heat pump systems, the optimization algorithm and the setting of parameter ranges will have an impact on the optimization results. …”
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Robust Path Tracking Control with Lateral Dynamics Optimization: A Focus on Sideslip Reduction and Yaw Rate Stability Using Linear Quadratic Regulator and Genetic Algorithms by Karrar Y. A. Al-bayati, Ali Mahmood, Róbert Szabolcsi

“…Under external and internal disturbances, such as road conditions, lateral wind, and actuator delay, the model demonstrates improved tracking performance and reduced sideslip angle and lateral acceleration by adjusting the longitudinal vehicle speed. …”
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Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition by Konstantinos Vantas, Vasiliki Mirkopoulou

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Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm by Xiang Wu, Zhen Yang, Dongdong Wu

“…Moreover, adaptive particle swarm optimization (APSO) was used to optimize the penalty factor and kernel parameters of the support vector machine to improve the global search ability and avoid the occurrence of the local optimal solutions. …”
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Optimization Design of Diaphragm Profile based on Kriging Model by Geng Hu, Zhigang Chen, Ding Zhang

“…To improve the fatigue performance of the diaphragm coupling，a optimization design method for the diaphragm profile parameters based on the Kriging model is proposed to maximize the high-cycle fatigue safety factor of the diaphragm design. …”
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Multi-objective optimization of current-assisted splitting spinning of small module tooth-shaped part based on the combination of BP neural network and NSGA-II algorithm by Zhou Haoyang, Xia Qinxiang, Xiao Gangfeng, Chen Can

“…The results show that the material at the tooth tip along the radial direction is in the state of tensile stress along radial and compressive stresses along tangential and axial directions, which promotes the radial flowing of the material and is beneficial the tooth filling of SMTSPs; the tooth saturation increases obviously under pulse current comparing without pulse current; the BPNN combined with the NSGA-II algorithm can reliably optimize the process parameters of the CASS, improving the forming quality of SMTSPs; experiments verified the feasibility of the process and the accuracy of the predictive model based on the optimization results.…”
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