Residual Film–Cotton Stubble–Nail Tooth Interaction Study Based on SPH-FEM Coupling in Residual Film Recycling by Xuejun Zhang, Yangyang Shi, Jinshan Yan, Shuo Yang, Zhaoquan Hou, Huazhi Li

“…Through analyses of the pickup device, key parameters were identified, and a model was built by combining the FEM and SPH algorithms to simulate the interaction of nail teeth, residual film, soil and root stubble. …”
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Enhanced prediction of corrosion rates of pipeline steels using simulated annealing-optimized ANFIS models by Ali Hussein Khalaf, Bing Lin, Ahmed N. Abdalla, Zhongzhi Han, Ying Xiao, Junlei Tang

“…These factors influence corrosion rates, represented by a single output neuron. The SA algorithm optimizes the ANFIS model's parameters, enhancing its ability to handle non-linear relationships. …”
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AI-driven generative and reinforcement learning for mechanical optimization of 2D patterned hollow structures by Yicheng Shan, Leitao Cao, Yu Wang, Jing Ren, Chen Huang, Wenli Gao, Shengjie Ling

“…This study demonstrates the efficacy of combining advanced AI techniques for rapid and precise material design optimization, providing a scalable and cost-effective solution for developing superior lightweight materials with tailored mechanical properties for critical engineering applications.…”
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Does mean arterial pressure augmentation improve neurological recovery of blunt spinal cord injuries: an EAST multicenter trial by Jeffry Nahmias, Ryan Peter Dumas, Brian Daley, Dalier R Mederos, Bradley M Dennis, Michael Steven Farrell, Stephanie Scott, Gregory Schaefer, Asanthi Ratnasekera, Alison Smith, Scott Armen, Joshua Hill, Carlos H Palacio, Caitlin Anne Fitzgerald, Stephanie Doris, Claudia Alvarez, John D Berne, Lindsey Perea, Aimee LaRiccia, James Bardes, Bhairav Shah, Tanisha Kashikar, Erik Teicher, Jennifer Huber, Malia Eischen, H Akin Erol, Lauren Colom, Melissa Moncrief, William DeVoe, William Brigode, Melissa Linskey Dougherty, Emily Alberto, Stephen Gadomski, Salina Wydo, Jennifer Schweinsburg, M Chance Spalding

“…Patients were divided into two groups: neurological improvement and no improvement, based on their change in ASIA score from arrival to hospital discharge.Results A total of 19 centers contributed 222 patients of those, 164 had pre-ASIA and post-ASIA scores. …”
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Integration of Regression-Based Guidance Ant for Enhanced Exploration and Convergence in Ant Colony Optimization (ACO) by Desi W. Sari, Suci Dwijayanti, Bhakti Y. Suprapto

“…To address these limitations, this research incorporates a linear regression line as a directional guide for ants, helping them navigate toward the optimal path more efficiently. This paper presents an improved Ant Colony Optimization (I-ACO) algorithm by integrating regression-based guidance to enhance both exploration and convergence. …”
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Collaborative Optimization of Container Liner Slot Allocation and Empty Container Repositioning Within Port Clusters by Wenmin Wang, Cuijie Diao, Wenqing He, Zhihong Jin, Zaili Yang

“…Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. …”
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Optimizing adaptive modulation technique using standard propagation model for enhanced wireless communication channels by Rahim Khan, Zahid Ullah Khan, Sher Taj, Sajid Ullah Khan, Javed Khan, Nazik Alturki, Sultan Alanazi

“…To ensure optimal configuration, an advanced optimization algorithm is employed to dynamically select the most effective SPM parameters, enabling robust performance across varying channel conditions. …”
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DC-WUnet: An Underwater Ranging Signal Enhancement Network Optimized with Depthwise Separable Convolution and Conformer by Xiaosen Liu, Juan Li, Jingyao Zhang, Yajie Bai, Zhaowei Cui

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Energy Distribution Optimization in Heterogeneous Networks with Min–Max and Local Constraints as Support of Ambient Intelligence by Alessandro Aloisio, Domenico D. Bloisi, Marco Romano, Cosimo Vinci

“…Since many devices are battery-powered, choosing the right communication interface is critical for optimizing energy efficiency. Our primary objective is to improve network performance while extending its operational lifespan by identifying an optimal set of interfaces that balance power consumption and efficiency. …”
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Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…The use of CBO ensures efficient convergence with minimal parameter tuning, making the model suitable for large-scale datasets compared to conventional optimizers, including Adam, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
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Machine learning-based prediction of optimal antenatal care utilization among reproductive women in Nigeria by Jamilu Sani, Adeyemi Oluwagbemiga, Mohamed Mustaf Ahmed

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Development of an optimized deep learning model for predicting slope stability in nano silica stabilized soils by Ishwor Thapa, Sufyan Ghani, Prabhu Paramasivam, Mitiku Adare Tufa

“…The results show that RNN-CNN-LSTM, optimized through OPTUNA algorithms, overcomes conventional machine learning models and achieves an accuracy of 99.4% on unseen test data, supported by stable validation trends and robust predictive performance. …”
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A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model by Wan Nie, Bingliang Shen, Desheng Li

“…To address the key challenges of limited practical application, high implementation difficulty, and poor generalization capability in existing theoretical models for data resource pricing, this study employs generative adversarial network (GAN) to augment the dataset and constructs a DRV-LightGBM model based on a Bayesian parameter optimization algorithm that maximizes the coefficient of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) to predict data resource transaction prices and provide post-hoc explanations for the prediction model. …”
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An Intelligent Path Planning System for Urban Airspace Monitoring: From Infrastructure Assessment to Strategic Optimization by Qianyu Liu, Wei Dai, Zichun Yan, Claudio J. Tessone

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Enhanced Underwater Image Restoration and Clarity Optimization Using Advanced Digital Image Processing Techniques by Gopirajan Punniyakotti Varadharajan, Pradeep T., Charan R.

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Model Predictive Control-Based Energy Management System for Cooperative Optimization of Grid-Connected Microgrids by Sungmin Lim, Jaekyu Lee, Sangyub Lee

“…Finally, the cooperative operation of MGs was compared with the independent operation of a single MG to analyze the impact of the cooperative approach on performance improvement. Quantitatively, integrating predictions reduced operating costs by 19.23% compared to the case without predictions, while increasing costs by approximately 3.7% compared to perfect predictions. …”
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. …”
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Prediction method of gas emission in working face based on feature selection and BO-GBDT by MA Wenwei

“…The wrapping method was identified as the most effective feature selection algorithm. Based on field conditions, 8 optimal features were selected for prediction. …”
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Delay margin analysis of FOTID controller for RES based EV system using MMGPE optimization by Adhit Roy, Susanta Dutta, Soumen Biswas, Anagha Bhattacharya, Sajjan Kumar, Soham Dutta, Provas Kumar Roy

“…For a steady, continuous power supply, renewable energy has become one of the most promising substitutes for traditional energy sources in recent decades. …”
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A Dynamic Interval Auto-Scaling Optimization Method Based on Informer Time Series Prediction by Yu Ding, Chenhao Li, Zhengong Cai, Xinghao Wang, Bowei Yang

“…In the experiments conducted on the official World Cup forum load and Alibaba cluster CPU load, the Informer time series prediction algorithm demonstrated better long-sequence time series prediction capabilities compared to algorithms such as LSTM and RNN. …”
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