Optimizing Social Security Contributions for Spanish Self-Employed Workers: Combining Data Preprocessing and Ensemble Models for Accurate Revenue Estimation by Luis Palomero, Vicente García, José Salvador Sánchez

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Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line by Sahatsawat Wainiphithapong, Chana Phutthananon, Sompote Youwai, Pitthaya Jamsawang, Phattarawan Malaisree, Ochok Duangsano, Pornkasem Jongpradist

“…This integrated framework, which combines the non-dominated sorting genetic algorithm (NSGA-II) with LSTM neural networks, is applied to MOO to identify the optimal SOPs, while accounting for their influence on S variation as a time-series over 11 timesteps, as considered in this study. …”
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BERT Mutation: Deep Transformer Model for Masked Uniform Mutation in Genetic Programming by Eliad Shem-Tov, Moshe Sipper, Achiya Elyasaf

“…We introduce BERT mutation, a novel, domain-independent mutation operator for Genetic Programming (GP) that leverages advanced Natural Language Processing (NLP) techniques to improve convergence, particularly using the Masked Language Modeling approach. …”
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Crucial heat damage analysis and optimization of a mid-sized pickup truck based on a deep Gaussian process model by Zebin Zhang, Sisi Liu, Xianzong Meng, Tingting Wang, Shizhao Jing, Chuanrui Wang, Dongchen Qin

“…Based on simulation results, a multi-objective two-layer deep Gaussian process model predicted heat source temperatures. The positions of cooling components were optimized using a genetic algorithm with heat-sensitive locations as the objectives. …”
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Seismic Optimization of Fluid Viscous Dampers in Cable-Stayed Bridges: A Case Study Using Surrogate Models and NSGA-II by Qunfeng Liu, Zhen Liu, Jun Zhao, Yuhang Lei, Shimin Zhu, Xing Wu

“…The second strategy employs a data-driven surrogate model, specifically an Artificial Neural Network (ANN), integrated with the NSGA-II optimization algorithm. …”
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Intelligent rockburst level prediction model based on swarm intelligence optimization and multi-strategy learner soft voting hybrid ensemble by Qinghong Wang, Tianxing Ma, Shengqi Yang, Fei Yan, Jiang Zhao

“…The data preprocessing method proposed in this study, based on an improved version of the Student t-SNE algorithm, effectively reduced the negative impact of data noise on model performance, enhancing the reliability of predictions. …”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…Explainable Artificial Intelligence (xAI) methods were used to enhance model interpretability and trustworthiness, with optimization via the Optuna algorithm. …”
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GPT-NAS: Neural Architecture Search Meets Generative Pre-Trained Transformer Model by Caiyang Yu, Xianggen Liu, Yifan Wang, Yun Liu, Wentao Feng, Xiong Deng, Chenwei Tang, Jiancheng Lv

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Assessment model of ozone pollution based on SHAP-IPSO-CNN and its application by Xiaolei Zhou, Xingyue Wang, Ruifeng Guo

“…To address this problem, a convolutional neural network (CNN) model combining the improved particle swarm optimization (IPSO) algorithm and SHAP analysis, called SHAP-IPSO-CNN, is developed in this study, aiming to reveal the key factors affecting ground-level ozone pollution and their interaction mechanisms. …”
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Optimal control of asynchronous drive of auxiliary machines of electric rolling stock by Yu. M. Kulinich, S. A. Shukharev, V. K. Dukhovnikov, D. A. Starodubtsev

“…The proposed system of optimal control of electric locomotive auxiliary machines is designed to improve the energy efficiency of the drive with a new algorithm for selecting the optimal value of the rotor flux linkage by reducing the current consumed by the drive. …”
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Attention-based hybrid deep learning model with CSFOA optimization and G-TverskyUNet3+ for Arabic sign language recognition by Ahmed A. Mohamed, Abdullah Al-Saleh, Sunil Kumar Sharma, Ghanshyam Tejani

“…In addition, employing a novel metaheuristic algorithm, the Crisscross Seed Forest Optimization Algorithm, which combines the Crisscross Optimization and Forest Optimization algorithms to determine the best features from the extracted texture, color, and deep learning features. …”
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Dynamic optimization of solar DG and shunt capacitor placement to mitigate the impact of EV charging stations on power distribution network by T. Yuvaraj, M. Thirumalai, T.D. Suresh, Sudhakar Babu Thanikanti, Mohammad Khishe

“…Simulation results confirm the superior performance of QRSMA in improving voltage profiles, reducing power losses, and achieving better computational efficiency compared to conventional optimization algorithms. …”
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Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Bader Aldughayfiq, Hisham Allahem, Alshimaa Abdelraof Mahmoud, Wael Said, Hosameldeen Shabana, Mohamed Ezz

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GA BP prediction model for energy consumption of steel rolling reheating furnace by Yi Duan, Guang Chen, Xiangjun Bao, Jing Xu, Lu Zhang, Xiaojing Yang

“…The proposed GA-BP model demonstrates superior predictive capabilities and robustness, offering valuable insights for optimizing process parameters and improving energy efficiency in SRRF operations.…”
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Prediction and Optimization for Multi-Product Marketing Resource Allocation in Cross-Border E-Commerce by Yi Xie, Heng-Qing Ye, Wenbin Zhu

“…We propose a two-stage optimization framework that integrates predictive models with constrained optimization. …”
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SLPDBO-BP: an efficient valuation model for data asset value by Cuiping Zhou, Shaobo Li, Cankun Xie, Panliang Yuan, Zihao Liao

“…Secondly, in an attempt to comprehensively evaluate the optimization performance of SLPDBO, a series of numerical optimization experiments are carried out with 20 test functions and with popular optimization algorithms and dung beetle optimizer (DBO) algorithms with different improvement strategies. …”
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Development of IIOT-Based Pd-Maas Using RNN-LSTM Model with Jelly Fish Optimization in the Indian Ship Building Industry by PNV Srinivasa Rao, PVY Jayasree

“…The validation of the proposed predictive maintenance model optimization with different types of deep learning algorithms shows that our proposed methodology gives an improved accuracy of 98.9336% which is higher than any other models.   …”
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Enhancing the prediction of groundwater quality index in semi-arid regions using a novel ANN-based hybrid arctic puffin-hippopotamus optimization model by Moustafa Gamal Snousy, Hussein M. Elshafie, Ashraf R. Abouelmagd, Najmaldin Ezaldin Hassan, Mahmoud E. Abd-Elmaboud, Ali Akbar Mohammadi, Ashraf M.T. Elewa, E. EL-Sayed, Ahmed M. Saqr

“…Study focus: This study presents a novel hybrid arctic puffin–hippopotamus optimization (HPHO) algorithm combined with an artificial neural network (ANN) to improve irrigation water quality index (IWQI) predictions in semi-arid areas. …”
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Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network by Raheleh Ghadami, Javad Rahebi

“…<b>Method:</b> This proposal methodology involves sourcing Alzheimer’s disease-related MRI images and extracting features using convolutional neural networks (CNNs) and the Gray Level Co-occurrence Matrix (GLCM). The Harris Hawks Optimization (HHO) algorithm is applied to select the most significant features. …”
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Dynamic Classification: Leveraging Self-Supervised Classification to Enhance Prediction Performance by Ziyuan Zhong, Junyang Zhou

“…In addition, the algorithm uses subareas boundary to refine predictions results and filter out substandard results without requiring additional models. …”
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