Remaining Useful Life Prediction of Aero-Engine Based on Improved GWO and 1DCNN by Lihua Shen, Yucheng Wang, Baorui Du, Hailong Yang, He Fan

“…To mitigate the local optimum entrapment inherent in deep learning hyperparameter optimization, an improved Gray Wolf Optimizer incorporating dynamic perturbation factors is proposed. …”
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An improved beluga whale optimizer-Derived Adaptive multi-channel DeepLabv3+ for semantic segmentation of aerial images. by Anilkumar P, Venugopal P

“…With the motive of addressing the difficulties in the existing semantic segmentation techniques for aerial images, the adoption of deep learning techniques is utilized. This model has adopted a new Adaptive Multichannel Deeplabv3+ (AMC-Deeplabv3+) with the help of a new meta-heuristic algorithm called Improved Beluga whale optimization (IBWO). …”
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Optimized Ensemble Model to Predict the Compatibility of Automobiles With Hybrid Electric Vehicles by Rohit Bajaj, Deepika Sharma, Ruchika Gupta, Shonak Bansal, Payal Patial, Krishna Prakash

“…Through rigorous testing and refinement, the proposed model exhibits improved accuracy, elevating performance from 81.76% to 86.68%. …”
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Leveraging prior mean models for faster Bayesian optimization of particle accelerators by Tobias Boltz, Jose L. Martinez, Connie Xu, Kathryn R. L. Baker, Zihan Zhu, Jenny Morgan, Ryan Roussel, Daniel Ratner, Brahim Mustapha, Auralee L. Edelen

“…Abstract Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. …”
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Optimizing additive manufacturing workflows using model-based systems engineering by Mohamed Amine Daoud, Khadija Bekkay Haouari, Meriem Hayani Mechkouri, Amine Ennawaoui, Hicham El hadraoui, Ilias Naser, Mustapha Ouardouz, Kamal Reklaoui

“…These models formalize the system architecture, providing a foundation for developing automated design validation, flaw detection, and optimization mechanisms. …”
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Numerical modeling and neural network optimization for advanced solar panel efficiency by Udit Mamodiya, Indra Kishor, Mohammed Amin Almaiah, Monia Hamdi, Rami Shehab, Tayseer Alkhdour

“…Conventionally, such optimization techniques—MPPT (Maximum Power Point Tracking) along with heuristic algorithms—suffer significantly from slow adaptability and track sub optimality under dynamic environments. …”
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Optimal machine learning algorithms and UAV multispectral imagery for crop phenotypic trait estimation: a comprehensive review and meta-analysis by Adama Ndour, Gerald Blasch, João Valente, Bisrat Haile Gebrekidan, Tesfaye Shiferaw Sida

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Research on the Photovoltaic MPPT Method Based on Improved BP-SVM-ELM Combination Prediction by DAI Bowang, ZHAO Xianggui, ZHU Qiliang

“…Through experimental simulation analysis, the combined forecasting method can use the advantages of each algorithm, effectively avoiding their deficiencies, and fundamentally improve the performance of the predictive model. …”
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Optimization method of task uninstallation in mobile edge computing environment combining improved deep Q-learning and transmission learning by Lihong Zhao, Shuqin Wang, Xiaomei Ding

“…Meanwhile, by introducing TL, the model can quickly transfer knowledge and achieve adaptive optimization of tasks in new environments, thereby improving the generalization ability and efficiency of the decision-making process. …”
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Research on manufacturing quality improvement based on product gene evaluation method and a meta-heuristic algorithm with hybrid encoding scheme by Wenxiang Xu, Chao Wang, Shimin Xu, Junyong Liang, Dezheng Liu, Baigang Du

“…To address the model, an improved genetic algorithm (GA) and artificial bee colony algorithm (ABC) with hybrid encoding scheme (H-IGA-IABC) is designed by considering the different types of gene elements. …”
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A new CNN deep learning model for computer-intelligent color matching by He Zhibin, Tan Yanmei, Li Sa

“…Besides, based on the optimized algorithm, an intelligent color-matching model was constructed. …”
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A study on the prediction of mountain slope displacement using a hybrid deep learning model by Yuyang Ma, Xiangxiang Hu, Yuhang Liu, Yaya Shi, Zhiyuan Yu, Xinmin Wang, Liangbai Hu, Shuailing Liu, Dongdong Pang

“…The method employs an Improved Whale Optimization Algorithm (IWOA) to fine-tune parameters for GNSS data fitting, ensuring accurate signal feature extraction. …”
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Prediction of Thyroid Classes Using Feature Selection of AEHOA Based CNN Model for Healthy Lifestyle by Rachappa Jopate, Piyush Kumar Pareek, DivyaJyothi M. G, Ariam Saleh Zuwayid Juma Al Hasani

“…This research presents the Adaptive Elephant Herd Optimisation Algorithm (AEHOA) model for selecting optimal attributes in order to circumvent these limitations. …”
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Using artificial intelligence methods for the optimal synthesis of reversible networks by Taras Kyryliuk, Mykhailo Palahuta, Vitaly Deibuk

“…The ant colony optimization algorithms were improved, including several changes to the proposed data representation model, structure, and operational principles of the synthesis algorithm, enabling effective synthesis of devices on the NCT basis along with Fredkin gates. …”
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Modeling, optimization, and thermal management strategies of hydrogen fuel cell systems by Abubakar Unguwanrimi Yakubu, Liu Qingsheng, Meng Kai, Chen Jinwei, Omer Abbaker Ahmed Mohammed, Jiahao Zhao, Qi Jiang, Xuanhong Ye, Junyi Liu, Qinglong Yu, Muhammad Aurangzeb, Shusheng Xiong

“…Optimization algorithms such as PSO, WOA, MIGA, and NSGA-II have shown promising results, including up to 15 % reduction in hydrogen consumption and 20 to 30 % improvement in thermal uniformity. …”
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Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…A convolutional neural network (CNN) based on the VGG16 architecture is utilized for spatial feature extraction, followed by a bidirectional long short-term memory (BiLSTM) network to capture the temporal dependencies of the scalograms. The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
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Virtual Cluster Partitioning Method of Active Distribution Networks Using Quantum Particle Swarm Optimization and Sector Search by Wei Liu, Yifan Tong, Xinran Xing, Xi Chen, Bo Hu, Qian Sun, Yufei Wang, Huaxin Li, Huidong Guo

“…This model simplifies the search for node locations and improves the algorithm's convergence speed. …”
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An improved MP-NMO correction method based on multiparameter fitting and its application by Xiaohui YANG, Pengfei YU, Jiawei ZHANG

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Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

“…Methods We developed a novel hybrid model integrating convolutional neural network (CNN), Transformer, and Whale Optimization Algorithm (WOA) for arrhythmia prediction in AMI patients. …”
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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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