Predicting Earthquake Casualties and Emergency Supplies Needs Based on PCA-BO-SVM by Fuyu Wang, Huiying Xu, Huifen Ye, Yan Li, Yibo Wang

“…Subsequently, the optimal hyperparameters for the SVM model are obtained using the Bayesian Optimization algorithm. …”
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Route Generation and Built Environment Behavioral Mechanisms of Generation Z Tourists: A Case Study of Macau by Ying Zhao, Pohsun Wang, Yafeng Lai

“…However, limited research has integrated behavioral drivers with algorithmic travel route optimization, particularly in the context of Generation Z tourists. …”
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Carbon emission prediction method for expressway construction period based on PSO-BP neural network by Quansheng ZHAO, Fei LI, Feng′ai GUO, Jianyou YU, Shizhao XU, Yunpeng HU, Xiaomeng CHU

“…To solve the problem of inaccurate carbon emissions prediction during the highway construction period, a method of optimizing the back propagation(BP) neural network by particle swarm optimization (PSO) algorithm was proposed to predict carbon emissions. …”
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A convolutional neural network driven suspension control strategy to enhance sustainability of high-speed trains by Duo Zhang, Hong-Wei Li, Fang-Ru Zhou, Yin-Ying Tang, Qi-Yuan Peng

“…In conjunction with the neural network algorithm, a bi-objective optimization model is further developed and solved to adjust scale factor of the Skyhook controller according to different running conditions. …”
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Modeling 5G-NR User Blocking Probability in Conditional Handover-Enabled Heterogeneous Networks by Amiraslan Haghrah, Javad Musevi Niya, Jafar Pourrostam

“…To demonstrate the practical applicability of the proposed model, we present a case study involving a multi-objective optimization problem solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). …”
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AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management by Luis Rojas, Álvaro Peña, José Garcia

“…The findings highlight the increasing adoption of deep learning, reinforcement learning, and digital twins for anomaly detection and process optimization. Additionally, AI-driven methods are improving sensor-based data acquisition and asset management, extending equipment lifecycles while reducing failures. …”
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Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry by Chaowei Dong, Jianfei Xu, Nan Zhou, Jixiong Zhang, Hao Yan, Zejun Li, Yuzhe Zhang

“…Analysis demonstrates that the particle swarm optimal (PSO) algorithm based on adaptive adjustment strategy can effectively optimize the hyperparameters of support vector regression (SVR), and the MC-PSO-SVR model exhibits better predictive capability (R2> 0.88) and lower error coefficients (MAE, RSE, and RMSE values approaching 0) and narrower widths of 95 % confidence intervals for yield stress, plastic viscosity, fluidity, and UCS. …”
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Rotation reshapes sustainable potato production in dryland by reducing environmental footprints synergistically enhancing soil health by Hanyou Xie, Weiyan Wang, Ping He, Wencheng Ding, Xinpeng Xu, Xuelian Tan, Xiaowei Liu

“…Furthermore, the non-dominated sorting genetic algorithm II (NSGA-II) was used to optimize regional cropping structure. …”
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Deep Reinforcement Learning-Based Dynamic Scheduling for Real-Time Applications in LTE and RAN Slicing for eMBB in 5G by Houssem Eddine Benmadani, Mohamed Azni, Turki Essa Alharbi, Mohammed S. Alzaidi, Mohamed Tounsi

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Reconceptualizing Gatekeeping in the Age of Artificial Intelligence: A Theoretical Exploration of Artificial Intelligence-Driven News Curation and Automated Journalism by Dan Valeriu Voinea

“…Moreover, adaptive algorithms learn from user behavior, creating feedback loops that dynamically shape news diversity and bias over time. …”
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A Review of Systematic Methodologies for Shipyard Facility Layout Design by Ghulam Tulus Pambudi, Gunawan Gunawan, Dimas Angga Fakhri Muzhoffar, Wanda Rulita Sari

“…Heuristic algorithms, including genetic algorithms and simulated annealing, offer flexible and rapid solutions but may not always achieve global optimization. …”
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A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture by Bing Shi, Zelin Gao, Tianheng Pu, Jianming Jiang, Yueping Sun

“…The inertia weight $$\omega$$ and learning factor c were optimized to enhance the optimization ability of the particle swarm. …”
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Crash severity prediction using a virtual geometry-group-based deep learning approach with images-based feature representation by Nanon Sonnatthanon, Kasem Choocharukul

“…To address class imbalance, a combination of the Synthetic Minority over Sampling technique, Edited Nearest Neighbor, and Tomek Link algorithms are applied. A Virtual Geometry Group deep learning model, optimized using Bayesian optimization, is trained to maximize the F1-score and Area Under the Curve, ensuring high prediction performance. …”
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AYOLO: Development of a Real-Time Object Detection Model for the Detection of Secretly Cultivated Plants by Ali Yılmaz, Yüksel Yurtay, Nilüfer Yurtay

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

“…This algorithm is subsequently deployed to optimize hyperparameters within the redesigned predictive architecture. …”
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Pricing principles in the field of ready–made meal delivery: analysis of influence factors by K. V. Martynov

“…The study describes the most popular pricing principles: cost–based, competitor–oriented, as well as dynamic algorithms taking into account seasonal demand. The results reflecting the willingness of customers to pay extra while observing short delivery times and maintaining product quality are studied. …”
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Training multi-layer binary neural networks with random local binary error signals by Luca Colombo, Fabrizio Pittorino, Manuel Roveri

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Minimizing Delay in UAV-Aided Federated Learning for IoT Applications With Straggling Devices by Mudassar Liaq, Waleed Ejaz

“…We then use the concurrent deterministic simplex with root relaxation algorithm. We also propose a deep reinforcement learning (DRL)-based solution to improve runtime complexity. …”
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Sum Rate Maximization of Active RIS-Assisted FD-NOMA Systems by Yi Peng, Yang Xiao, Qingqing Yang

“…Additionally, the optimal transmit powers for all uplink users are obtained through an iterative algorithm. …”
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Adaptive Quantum-Inspired Evolution for Denoising PCG Signals in Unseen Noise Conditions by Lubna Siddiqui, Ashish Mani, Jaspal Singh

“…The filter coefficients were optimised using the proposed QiEA with Adaptive Rotation Gate Operator (ARGO). The proposed algorithm accelerates convergence towards optimal solutions based on fitness feedback, improving filter optimisation while clamping rotation angles to maintain algorithm stability. …”
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