Truck Transportation Scheduling for a New Transport Mode of Battery-Swapping Trucks in Open-Pit Mines by Yufeng Xiao, Wei Zhou, Boyu Luan, Keyi Yang, Yuqing Yang

“…The primary objective is to minimize the total haulage cost and total waiting time. Both a genetic algorithm and an adaptive genetic algorithm are applied to solve the proposed multi-objective scheduling optimization model. …”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…This study presents a novel hybrid modeling framework that combines Response Surface Methodology (RSM) with machine learning (ML) algorithms– Support Vector Regression (SVR) and Gradient Boosting Regression (GBR)– to contribute to the predictive modeling and optimization of thermally-activated ZnFe-LDH based Fenton catalysis. …”
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Steganographic model to conceal the secret data in audio files utilizing a fourfold paradigm: Interpolation, multi-layering, optimized sample space, and smoothing by Daffa Tristan Firdaus, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Didacienne Mukanyiligira, Louis Sibomana

“…The proposed method seeks to improve stego audio quality by implementing a smoothing-based technique and optimizing the sample space through linear interpolation, followed by a multi-layering process. …”
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Embedding Moving Baseline RTK for High-Precision Spatiotemporal Synchronization in Virtual Coupling Applications by Susu Huang, Baigen Cai, Debiao Lu, Yang Zhao, Miao Zhang, Linyu Shang

“…To further enhance synchronization performance, a decentralized distributed synchronization algorithm was introduced, reducing communication overhead and improving real-time responsiveness. …”
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Real-Time Parameter Control for Trajectory Generation Using Reinforcement Learning With Zero-Shot Sim-to-Real Transfer by Chang-Hun Ji, Gyeonghun Lim, Youn-Hee Han, Sungtae Moon

“…In this paper, we propose a novel algorithm that utilizes reinforcement learning to determine the optimal maximum velocity and acceleration in real-time within dynamic environments. …”
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Blockchain-Based UAV-Assisted Mobile Edge Computing for Dual Game Resource Allocation by Shanchen Pang, Yu Tang, Xue Zhai, Siyuan Tong, Zhenghao Wan

“…The experimental results show that compared with the traditional single-stage optimization algorithm (SSO), the equal allocation algorithm (EAA) and the dynamic resource pricing algorithm (DRP), the DSO algorithm proposed in this paper has significant advantages by improving resource utilization by 7–10%, reducing task latency by 3–5%, and lowering energy consumption by 4–8%, making it highly effective for dynamic UAV environments.…”
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Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

“…GA handles feature selection, while PSO optimizes MLP hyperparameters (e.g., learning rate, neurons, activation functions). …”
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Sustainable Parking Space Management Using Machine Learning and Swarm Theory—The SPARK System by Artur Janowski, Mustafa Hüsrevoğlu, Malgorzata Renigier-Bilozor

“…It enables rapid and precise detection of available parking spaces while ensuring robustness and continuous improvement. …”
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Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

“…[Results] The study introduced four key innovations to the original Mantis Search Algorithm (MSA): (1) combining Logistic-Tent chaotic mapping for population initialization, ensuring uniform and random distribution of initial solutions to enhance global search capability and convergence speed; (2) nonlinear acceleration factor, refining MSA’s core update formula to transition from global exploration to local exploitation, mitigating local optima entrapment; (3) elite-guided adaptive update strategy, addressing the excessive randomness in the position update strategy when Mantis attacks fail, improving late-stage search efficiency while preserving some randomness; (4) opposition-based learning, generating individuals opposite to the current individual to enhance global optimization. …”
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AI-Assisted Design of Drain-Extended FinFET With Stepped Field Plate for Multi-Purpose Applications by Xiaoyun Huang, Hongyu Tang, Chenggang Xu, Yuxuan Zhu, Yan Pan, Dawei Gao, Yitao Ma, Kai Xu

“…This study introduces a novel DE-FinFET featuring a stepped field plate to improve overall performance of device. Moreover, within an AI-assisted design framework, predictive modeling and multi-objective optimization of the device are accomplished using Kolmogorov–Arnold Networks (KAN) and the Nondominated Sorting Genetic Algorithm (NSGA-III). …”
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Spectrum Efficient Mode Selection and Resource Allocation Optimization for D2D Communication in HetNet: A Multi-Agent Q-Learning Approach by Ali Majid Hasan Alibraheemi, Mhd Nour Hindia, Tengku Faiz Tengku Mohmed Noor Izam, Kaharudin Dimyati

“…Then, based on the allocated optimal channel, a modified MAQL algorithm is introduced to allocate the optimal power for each D2D transmitter. …”
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Robust InceptionV3 with Novel EYENET Weights for Di-EYENET Ocular Surface Imaging Dataset: Integrating Chain Foraging and Cyclone Aging Techniques by Muhammad Ahmad Khan, Saif Ur Rehman Khan, Hafeez Ur Rehman, Suliman Aladhadh, Ding Lin

“…Our results demonstrate that the InceptionV3 model, fine-tuned with the newly developed EYENET weights, outperforms both traditional ImageNet weights and other pretrained models, showing a 2% accuracy improvement. This research highlights the potential of nature-inspired optimization algorithms and tailored datasets to enhance AI model robustness and adaptability in the context of medical disease diagnosis, particularly in the field of diabetic eye disease.…”
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Multi-objective optimization of custom implant abutment design for enhanced bone remodeling in single-crown implants using 3D finite element analysis by Pongsakorn Poovarodom, Chaiy Rungsiyakull, Jarupol Suriyawanakul, Qing Li, Keiichi Sasaki, Nobuhiro Yoda, Pimduen Rungsiyakull

“…A 12-month bone remodeling algorithm subroutine in finite element analysis to optimize three parameters: implant placement depth, abutment taper degree, and gingival height of the titanium base abutment. …”
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Bio-Inspired Traffic Pattern Generation for Multi-AMR Systems by Rok Vrabič, Andreja Malus, Jure Dvoršak, Gregor Klančar, Tena Žužek

“…Validated through physics-based simulations in Gazebo across three scenarios, a standard MAPF benchmark, and two industrial environments, the movement constraints generated using the proposed method improved the system throughput by up to 10% compared to unconstrained navigation and up to 4% compared to expert-designed solutions while reducing the need for conflict-resolution interventions.…”
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Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

“…In modern wind turbine design, two significant challenges arise: achieving optimal aerodynamic performance while minimizing acoustic noise emissions. …”
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NoiseAugmentNet-HHO: Enhancing Histopathological Image Classification Through Noise Augmentation by Prem Purusottam Jena, Debahuti Mishra, Kaberi Das, Sashikala Mishra

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Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia by Munkhsuren Badrakh, Narantsetseg Tserendash, Erdenejargal Choindonjamts, Gáspár Albert

“…Geological mapping in remote and geologically complex regions can be substantially improved by integrating remote sensing data with machine learning algorithms. …”
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Frequency regulation of PV-reheat thermal power system via a novel hybrid educational competition optimizer with pattern search and cascaded PDN-PI controller by Serdar Ekinci, Davut Izci, Ozay Can, Mohit Bajaj, Vojtech Blazek

“…The controller's performance was evaluated under various scenarios, including a 10 % step load change and solar radiation variations, demonstrating significant improvements in frequency regulation. The hECO-PS tuned PDN-PI controller achieved a minimum integral of time-weighted absolute error (ITAE) value of 0.4464, outperforming conventional methods like the modified whale optimization algorithm and sea horse algorithm, which yielded ITAE values of 2.6198 and 0.8598, respectively. …”
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Dynamic Inversion Method for Concrete Gravity Dam on Soft Rock Foundation by Guanglin Yin, Chaoning Lin, Taozhen Sheng, Wenbo Xue, Tongchun Li, Siyu Chen

“…To address this limitation, an improved particle swarm optimization (PSO) algorithm is developed for dynamic parameter inversion, combining real-time monitoring data with finite element modeling to evaluate the time-varying elastic modulus of the foundation. …”
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Design of an intelligent optimization system for high-altitude photovoltaic power plant output power prediction and enhancement using GVSAO-CNN-BiGRU-Attention by Shuai Yuan, Hui Zhou, Kai Zhao

“…The system integrates convolutional neural networks (CNN), bi-directional gated recurrent units (BiGRU), attention mechanisms, and genetic algorithm optimization (GVSAO). The CNN extracts spatial features, while the BiGRU enhances temporal dependency modeling, effectively capturing short- and long-term patterns. …”
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