EV charging stations for sustainable urban transport electrification in the Arabian Peninsula: Performance assessment, social-economic aspects, opportunities, implementation challe... by Jamiu O. Oladigbolu, Asad Mujeeb, Mohd Bilal, Yusuf A. Al-Turki, Saleh S. Alharbi, Salah S. Alharbi

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Model for selective vehicle problem considering mixed fleet with capacitated electric vehicles by Jiacheng Li, Masato Noto, Yang Zhang, Jia Guo

“…The performance and computational efficiency of this algorithm are validated through comparative analysis with other classic optimization algorithms on test instances. …”
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Addressing the Return Visit Challenge in Autonomous Flying Ad Hoc Networks Linked to a Central Station by Ercan Erkalkan, Vedat Topuz, Ali Buldu

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Classification of Fritillaria thunbergii appearance quality based on machine vision and machine learning technology by DONG Chengye, LI Dongfang, FENG Huaiqu, LONG Sifang, XI Te, ZHOU Qin’an, WANG Jun

“…Several statistical learning and object detection algorithms were selected to train and test the F. thunbergii dataset. …”
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Adaptive Hybrid PSO-Embedded GA for neuroevolutionary training of multilayer perceptron controllers in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

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Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

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From Misinformation to Insight: Machine Learning Strategies for Fake News Detection by Despoina Mouratidis, Andreas Kanavos, Katia Kermanidis

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Deep Learning Methods and UAV Technologies for Crop Disease Detection by S. G. Mudarisov, I. R. Miftakhov

“…The paper proposes solutions to these issues, including algorithm optimization and improved data preprocessing techniques. …”
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Height Measurement Method for Meter-Wave Multiple Input Multiple Output Radar Based on Transmitted Signals and Receive Filter Design by Cong Qin, Qin Zhang, Guimei Zheng, Xiaolong Fu, He Zheng

“…We transformed it into two sub-optimization problems and approximated the optimal solution through an alternating iteration algorithm. …”
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Transforming traffic accident investigations: a virtual-real-fusion framework for intelligent 3D traffic accident reconstruction by Yanzhan Chen, Qian Zhang, Fan Yu

“…While visual rendering by 3D-GS struggles under adverse conditions like nighttime or rain, a clustering parameter stochastic optimization model and mixed-integer programming Bayesian optimization (MIPBO) algorithm are proposed to enhance the segmentation of large-scale 3D point clouds. …”
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Evaluating the strength properties of high-performance concrete in the form of ensemble and hybrid models using deep learning techniques by Zhe Wang, Tao Sun, Yan Sun, Na Liu

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Residential Energy Management Method Based on the Proposed A3C-FER by Jinjiang Zhang, Qiang Lin, Lu Wang, Orefo Victor Arinze, Zihan Hu, Yantai Huang

“…In comparison with the Proximal Policy Optimization (PPO) and Deep Q-Network (DQN) algorithms, the novel approach not only improves the average reward value post-convergence by 38.48% and 47.17%, respectively, but also significantly reduces the training duration by 81.19% within a multi-threaded computational environment.…”
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Enhanced water saturation estimation in hydrocarbon reservoirs using machine learning by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Dmitriy A. Martyushev

“…Nine well log parameters—Depth (DEPT), High-Temperature Neutron Porosity, True Resistivity, Computed Gamma Ray, Spectral Gamma Ray, Hole Caliper, Compressional Sonic Travel Time, Bulk Density, and Temperature—were used as input features to train and test five ML algorithms: Linear Regression, Support Vector Machine (SVM), Random Forest, Least Squares Boosting, and Bayesian methods. …”
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Applying Decision Transformers to Enhance Neural Local Search on the Job Shop Scheduling Problem by Constantin Waubert de Puiseau, Fabian Wolz, Merlin Montag, Jannik Peters, Hasan Tercan, Tobias Meisen

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A Hybrid Approach of DenseNet121 with Attention and Bi-LSTM for Yoga Pose Estimation by Aarthy K., Alice Nithya

“…This model enhances accuracy by incorporating self-attention mechanisms, allowing the system to focus on significant features within the data. Performance optimization is achieved through the Enhanced Chicken Swarm Optimization (ECSO) method, which fine-tunes the parameters of the system to ensure optimal results. …”
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AI-driven innovation in antibody-drug conjugate design by Heather A. Noriega, Xiang Simon Wang

“…This review is organized into six sections: (1) the progression from traditional modeling approaches to AI-driven design of individual ADC components; (2) the application of deep learning (DL) to antibody structure prediction and identification of optimal conjugation sites; (3) the use of AI/ML models for forecasting pharmacokinetic properties and toxicity profiles; (4) emerging generative algorithms for antibody sequence diversification and affinity optimization; (5) case studies demonstrating the integration of computational tools with experimental pipelines, including systems that link in silico predictions to high-throughput validation; and (6) persistent challenges, including data sparsity, model interpretability, validation complexity, and regulatory considerations. …”
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Toward Adaptive and Immune-Inspired Viable Supply Chains: A PRISMA Systematic Review of Mathematical Modeling Trends by Andrés Polo, Daniel Morillo-Torres, John Willmer Escobar

“…At the methodological level, a high degree of diversity in modeling techniques was observed, with an emphasis on mixed-integer linear programming (MILP), robust optimization, multi-objective modeling, and the increasing use of bio-inspired algorithms, artificial intelligence, and simulation frameworks. …”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

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Prediction of true critical temperature and pressure of binary hydrocarbon mixtures: A Comparison between the artificial neural networks and the support vector machine by M. Etebarian, k. movagharnejad

“…Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing methods. …”
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Illumination-adaptative granularity progressive multimodal image fusion method by Chuanyun WANG, Dongdong SUN, Mingqi ZHOU, Tian WANG, Qian GAO, Zhaokui LI

“…This module enables global feature perception with linear computational complexity, minimizing the loss of critical information during transmission. …”
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