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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SSM-Net: Enhancing Compressed Sensing Image Reconstruction with Mamba Architecture and Fast Iterative Shrinking Threshold Algorithm Optimization by Xianwei Gao, Bi Chen, Xiang Yao, Ye Yuan

“…To address these challenges, this paper proposes SSM-Net, a novel framework that combines the state-space modeling (SSM) of the Mamba architecture with the fast iterative shrinking threshold algorithm (FISTA). …”
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Autonomous Robotic Path Planning Based on the Gaussian Mixture Model in Complex Manufacturing Environment by Rui Sun, Yuanmin Wang, Wenzheng Zhao, Yinhua Liu

“…To solve this problem, this paper proposes a path segment directed evolution algorithm (PSDEA) based on the Gaussian mixture model and a heuristic optimization algorithm. …”
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Enhanced Fall Detection and Prediction Using Heterogeneous Hidden Markov Models in Indoor Environment by Oumaima Guendoul, Hamd Ait Abdelali, Youness Tabii, Rachid Oulad Haj Thami, Omar Bourja

“…The model achieved a 61% prediction rate with an accuracy of 81.51%. …”
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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

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Machine learning-based construction of Immunogenic cell death-related score for improving prognosis and personalized treatment in glioma by Guoyin Li, Yukui Zhao, Yubo He, Zhaoqiang Qian, Yiwen Liu, Xiaoyan Li, Lili Li, Zhiqiang Liu

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Computational intelligence analysis on drug solubility using thermodynamics and interaction mechanism via models comparison and validation by Ahmad J. Obaidullah, Wael A. Mahdi

“…In addition, the Fireworks Algorithm (FWA) is presented as an optimization method, demonstrating its potential in improving the model’s predictive abilities by effectively exploring and exploiting the search space. …”
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A novel method for distracted driving behaviors recognition with hybrid CNN-BiLSTM-AM model by Dengfeng Zhao, Haojie Li, Zhijun Fu, Bao Ma, Fang Zhou, Chaohui Liu, Wenbin He

“…Bayesian optimization algorithm is adopted to automatically optimize hyperparameters of the network so as to improve training efficiency and performance of the proposed model. …”
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Adaptive Matching of High-Frequency Infrared Sea Surface Images Using a Phase-Consistency Model by Xiangyu Li, Jie Chen, Jianwei Li, Zhentao Yu, Yaxun Zhang

“…This paper introduces an algorithm based on the phase-consistency model. We utilize image data collected from a specific maritime area with a high-frame-rate surface array infrared camera. …”
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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

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Authenticity Detection of Egg White Powder Using Near-Infrared Spectroscopy Based on Improved One-Dimensional Convolutional Neural Network Model by ZHU Zhihui, LI Wolin, HAN Yutong, JIN Yongtao, YE Wenjie, WANG Qiaohua, MA Meihu

“…Compared with traditional 1D-CNN network structure and other improved algorithms, the EG-1D-CNN model exhibited higher accuracy, faster detection speed, and smaller model footprint, thus making it more suitable for deployment on embedded devices. …”
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Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field by YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun

“…The simulation results show that the neural network model can be applied to the prediction of stratospheric wind field and the BP neural networks optimized by genetic algorithm and particle swarm optimization can greatly improve the prediction accuracy of BP neural network, and the forecast wind speed is following the true value in a certain period of time. …”
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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

“…This study proposes a novel approach to predict HEC (GJ/t) by utilizing actual production data from SRRF. A genetic algorithm (GA) optimized back-propagation neural network (BPNN) is developed and its performance is compared to that of a standard BP model. …”
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Integrating Explainable Artificial Intelligence With Advanced Deep Learning Model for Crowd Density Estimation in Real-World Surveillance Systems by Sultan Refa Alotaibi, Hanan Abdullah Mengash, Mohammed Maray, Faiz Abdullah Alotaibi, Abdulwhab Alkharashi, Ahmad A. Alzahrani, Moneerah Alotaibi, Mrim M. Alnfiai

“…The system assists in detecting and analyzing crowd density in real-time by utilizing artificial intelligence and machine learning (ML) models on surveillance videos. It detects crowded areas, manages crowd flow, and combines automated analysis with human oversight for improved public safety and early intervention. …”
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Effectiveness of Explainable Artificial Intelligence (XAI) Techniques for Improving Human Trust in Machine Learning Models: A Systematic Literature Review by In-On Wiratsin, Chaiyong Ragkhitwetsagul

“…This paper conducts a systematic literature review (SLR) to evaluate the effectiveness of various XAI techniques in improving human trust in ML models. Our methodology involves a comprehensive search and analysis of relevant literature from 2015 to 2024, using well-known databases and adhering to PRISMA guidelines. …”
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Habitat suitability modeling to improve conservation strategy of two highly-grazed endemic plant species in saint Catherine Protectorate, Egypt by Mohamed M. El-Khalafy, Eman T. El-Kenany, Alshymaa Z. Al-Mokadem, Salma K. Shaltout, Ahmed R. Mahmoud

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Challenges in Unifying Physically Based and Machine Learning Simulations Through Differentiable Modeling: A Land Surface Case Study by Shahryar K. Ahmad, Sujay V. Kumar, Clara Draper, Rolf H. Reichle

“…Scaling and bias correction factors, often used in ML approaches for enhancing generalizability, were found to limit the transferability of the optimized physical parameters to the land model. The global objective function further compromises the algorithm's ability to simultaneously capture contrasting moisture regimes. …”
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Engineered feature embeddings meet deep learning: A novel strategy to improve bone marrow cell classification and model transparency by Jonathan Tarquino, Jhonathan Rodríguez, David Becerra, Lucia Roa-Peña, Eduardo Romero

“…These artificial intelligence models have focused on limited cell subtypes, mainly associated to a particular disease, and are frequently presented as black boxes. …”
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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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Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model by Muhammad Kashif Saeed, Alanoud Al Mazroa, Bandar M. Alghamdi, Fouad Shoie Alallah, Abdulrhman Alshareef, Ahmed Mahmud

“…To optimize the hyperparameter values of the CNN-LSTM approach, the Chaotic Tunicate Swarm Algorithm (CTSA) approach was implemented to improve the accuracy of classifier results. …”
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