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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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

“…The simulation results demonstrate that the proposed optimization planning method effectively improves the voltage distribution and net load level of the IES distribution network, while the complementary characteristics of the electric–hydrogen hybrid energy storage system enhance the operational flexibility of the IES.…”
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Hierarchical Disturbance Propagation Mechanism and Improved Contract Net Protocol for Satellite TT&C Resource Dynamic Scheduling by Zhiqing Xiang, Yi Gu, Xinwei Wang, Guohua Wu

“…Dynamic disturbances are propagated layer by layer from the task layer to the central external collaboration layer in a bottom-up manner, using efficient heuristic strategies in the task layer and the resource layer, respectively. We use improved contract network algorithms in the center internal collaboration layer and the center external collaboration layer, the original scheduling plan is quickly adjusted to minimize the impact of disturbances while effectively completing dynamic task requirements. …”
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Real-Time Estimation Method of P-Wave Slowness Based on Kalman Filtering and STC by SUN Hao, CHEN Wenhui, SUN Xuekai, YU Weidong, LI Siyi, ZHAO Peng

“…Utilizing the Kalman filter to update the system's optimal state in real-time effectively improves the accuracy and stability of automated picking in low signal-to-noise ratio regions and slow formations. …”
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A Comprehensive Review of Sizing and Energy Management Strategies for Optimal Planning of Microgrids with PV and Other Renewable Integration by Fadi Agha Kassab, Rusber Rodriguez, Berk Celik, Fabrice Locment, Manuela Sechilariu

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Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

“…To solve this, we propose an Adaptive Firefly-Based Bi-Objective Optimization (AFBO) algorithm that introduces multiple adaptive mechanisms to improve convergence and diversity. …”
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Optimization of Reverse Logistics Networks for Hazardous Waste Incorporating Health, Safety, and Environmental Management: Insights from Large Cruise Ship Construction by Huilin Li, Jiaqi Yang, Wei Zhang

“…The comparative analysis shows that DCSA performs as well as NSGA-II, while outperforming DGWO, demonstrating both stability and efficiency. …”
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Multi-objective optimization of wavy microchannel heat sinks with symmetric configurations generated by interpolation curves by Zhen Li, Haitao Han, Xunqing Huang, Jiarun Lou, Qiancan He, Haoran Zheng, Xiangyao Xue, Shuai Shao

“…Microchannel heat sinks (MCHS) with symmetric configurations enhance fluid flow disturbances through expansion-contraction sections, improving heat transfer performance. This paper presents an optimal design for symmetrically curved MCHS generated by using interpolation curves. …”
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Integrating Explainable Artificial Intelligence With Advanced Deep Learning Model for Crowd Density Estimation in Real-World Surveillance Systems by Sultan Refa Alotaibi, Hanan Abdullah Mengash, Mohammed Maray, Faiz Abdullah Alotaibi, Abdulwhab Alkharashi, Ahmad A. Alzahrani, Moneerah Alotaibi, Mrim M. Alnfiai

“…This study proposes an Osprey Optimization Algorithm with Deep Learning Assisted Crowd Density Detection and Classification (OOADL-CDDC) technique for smart video surveillance systems. …”
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Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

“…The methodology involves a formation-specific modelling approach, where separate ELM models are trained for each formation using surface drilling parameters such as weight on bit (WOB), rotary speed (RPM), and flow rate. Metaheuristic algorithms optimize the ELM’s weights and biases to improve predictive performance. …”
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A Comprehensive Analysis of the Triple-Hybrid Metamodel of MLP-PSO-ARIMA for Forecasting the FDSD Index: A Case Study of Khuzestan Province by Mohammad Ansari Ghojghar

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Recurrent Neural Network Optimized by Grasshopper for Accurate Audio Data-Based Diagnosis of Parkinson's Disease by Saif Wali Ali Alsudani, Ghassan Khudair Saud

“… Proposed here is a speech-based diagnostic framework for detecting Parkinson's disease that utilizes a Long Short-Term Memory neural network and the Grasshopper Optimization Algorithm. The framework aims to improve the detection of PD while ensuring accurate and efficient classification of speech-based signals. …”
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Surfactants Adsorption onto Algerian Rock Reservoir for Enhanced Oil Recovery Applications: Prediction and Optimization Using Design of Experiments, Artificial Neural Networks, and... by Kahina Imene Benramdane, Mohamed El Moundhir Hadji, Mohamed Khodja, Nadjib Drouiche, Bruno Grassl, Seif El Islam Lebouachera

“…Unlike traditional data acquisition methods, this approach enables a methodical and structured exploration of adsorption behavior while reducing the number of required experiments, leading to improved prediction accuracy, optimization, and cost-effectiveness. …”
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Disturbance Observer-Based Bio-Inspired LQR Optimization for DC Motor Speed Control by Mubarak Badamasi Aremu, Mohammed Abdel-Nasser, Nezar M. Alyazidi, and Sami El-Ferik

“…Numerous simulations demonstrate the enhanced performance of the developed technique in achieving optimal speed control while maintaining high robustness.…”
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Sample-Adjusted Threshold Calculation (SATC) for Optimizing Flood Mapping From a Trustworthy and Explainable Perspective by Zhijun Jiao, Biyan Chen, Zhimei Zhang, Lixin Wu

“…The experimental results of applying SATC to various scenarios indicate that these SATC-optimized algorithms achieve a notable 10–30% improvement in accuracy while concurrently reducing false and omission rates to <20% . …”
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Multi-clause deduction algorithm based on dynamic combination optimization of strategies and its application(策略动态组合优化多元演绎算法及应用) by 郭海林(GUO Hailin), 曹锋(CAO Feng), 易见兵(YI Jianbing), 李俊(LI Jun), 吴贯锋(WU Guanfeng)

“…In order to better guide the clause selection in multi-clause deduction, multi-clause deduction method based on dynamic combination optimization of strategies is proposed. This method dynamically combines and iteratively optimizes the number of words and function term depth of clause, fully exploring the existing multi-clause deduction heuristic strategies while improving the adaptability of different problems to strategies, achieving efficient clause selection of multi-clause deduction. …”
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Modeling and Performance Evaluation of Hybrid Classical–Quantum Serverless Computing Platforms by Claudio Cicconetti

“…While quantum computing technologies are evolving toward achieving full maturity, hybrid algorithms, such as variational quantum computing, are already emerging as valid candidates to solve practical problems in fields, such as chemistry and operations research. …”
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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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Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…To enhance model performance, the slime mould algorithm is employed for parameter optimization. Experimental results demonstrated that the hybrid model achieves excellent predictive accuracy, with crop yield prediction exceeding 99%. …”
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Optimization of thermal conductivity in coir fibre-reinforced PVC composites using advanced computational techniques by Saksham Anand, Venkatachalam Gopalan, Shenbaga Velu Pitchumani

“…To address these challenges, the study uses Response Surface Methodology (RSM) and three nature-inspired optimization methods viz. Particle Swarm Optimization (PSO), Dragonfly Optimization (DFO) and Cuckoo Search Algorithm (CSA) to improve factors like fibre content, particle size and chemical treatment. …”
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