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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Non-Destructive Identification of Virgin Cashmere and Chemically Modified Wool Fibers Based on Fractional Order Derivative and Improved Wavelength Extraction Algorithm Using NIR Sp... by Yaolin Zhu, Yong Zhang, Xin Chen, Jinni Chen, Hongsong Zhang

“…Meanwhile, common wavelength extraction algorithms few consider inherent relationship between spectral features and chemical properties, so an improved wavelength extraction algorithm using Shuffled Frog Leaping Algorithm (SFLA) and Beluga Whale Optimization (BWO) is employed to explore the connection of the two. …”
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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

“…The multi-objective genetic algorithm based on decomposition (MOEA/D) is used to achieve the optimization of three design variables, and pumping power and thermal resistance are considered as the objective functions. …”
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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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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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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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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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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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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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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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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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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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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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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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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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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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A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework by Mengji Yang, Haiqing Zhang, Xi Yu, Aicha Sekhari Seklouli, Abdelaziz Bouras, Yacine Ouzrout

“…Firstly, to reduce the redundancy of the input for the prediction model and the computational time complexity, while enhancing the robustness and stability of the prediction model, nonlinear correlation search algorithm based on time window extending and time window shrinking strategies have been proposed. …”
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Machine-learning based optimizing the neutronic and thermal-hydraulic performance in a VVER-1000 mixed-core as well as fuel burnup assessment by A. Koraniany, G.R. Ansarifar

“…By integrating this neural network with a genetic algorithm, optimization was carried out to identify the optimal fuel placement and enrichment for loading the UTVS fuel assembly into the targeted reactor core. …”
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The Mode of Constructing Safe Trajectories of Motion of the Unmanned Aerial Vehicle while Monitoring Power Lines Considering the Influence of their Electromagnetic Fields by Shabanova A.R., Tolstoy I.M., Lebedev I.V.

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A constructal theory framework for optimizing HRSG design: Enhancing thermal performance and cost-effectiveness by Morteza Mehrgoo, Majid Amidpour

“…Thermal efficiency improvements facilitate a 7.3-9.8% increase in steam production while maintaining optimal pinch point temperature differences of 10-12°C. …”
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