Development of a Self-Updating System for the Prediction of Steel Mechanical Properties in a Steel Company by Machine Learning Procedures by Valerio Zippo, Elisa Robotti, Daniele Maestri, Pietro Fossati, David Valenza, Stefano Maggi, Gennaro Papallo, Masho Hilawie Belay, Simone Cerruti, Giorgio Porcu, Emilio Marengo

“…The integration of this model into the production process allows a large-scale steel industry to predict steel properties with heightened accuracy, optimizing the manufacturing process for minimal waste and improved consistency. …”
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YOLO-SMUG: An Efficient and Lightweight Infrared Object Detection Model for Unmanned Aerial Vehicles by Xinzhe Luo, Xiaogang Zhu

“…To tackle the high computational demands and accuracy limitations in UAV-based infrared object detection, this study proposes YOLO-SMUG, a lightweight detection algorithm optimized for small object identification. …”
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A Systematic Integration of Artificial Intelligence Models in Appendicitis Management: A Comprehensive Review by Ivan Maleš, Marko Kumrić, Andrea Huić Maleš, Ivan Cvitković, Roko Šantić, Zenon Pogorelić, Joško Božić

“…Artificial intelligence (AI) and machine learning (ML) are transforming the management of acute appendicitis by enhancing diagnostic accuracy, optimizing treatment strategies, and improving patient outcomes. …”
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Evaluation Method for Remaining Life of XLPE Insulated Power Cable by MA Hanchao, GAO Baoqi, LI Xiangyang, WU Suzhou, ZHANG Xiaojun

“…The results show that this method can obtain the optimal solution fitness value quickly, improve the efficiency of the surplus life evaluation of the analysis object, determine the weight value of the assessment factor under the measurement of the iterative period, and improve the residual life of the cable. …”
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The Development of a Lightweight DE-YOLO Model for Detecting Impurities and Broken Rice Grains by Zhenwei Liang, Xingyue Xu, Deyong Yang, Yanbin Liu

“…A rice impurity detection algorithm model, DE-YOLO, based on YOLOX-s improvement is proposed to address the issues of small crop target recognition and the similarity of impurities in rice impurity detection. …”
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Transport Capacity Maximization in Rail Mass Transit Stations Under Uncertainty by Adrian Fernandez-Rodriguez, Maria Dominguez, Asuncion P. Cucala, Antonio Fernandez-Cardador

“…This paper introduces a two-level optimization model designed to maximize the practical transport capacity of mass transit railway stations. …”
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Elastic net with Bayesian Density Estimation model for feature selection for photovoltaic energy prediction by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…The findings specify a substantial improvement in accuracy in prediction, emphasizing how the model can be used for improving solar power grid integration and energy for improved RE management.…”
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ACO-NM hybrid optimization calculation method for transit time of oxygen activation logging in CO2 injection profile by WANG Zhengyan, CHEN Meng, YANG Guofeng, LIU Guoquan, PEI Yang, CHEN Qiang

“…Through the preliminary optimization of the spectral lines, a reasonable initial solution was provided for the NM algorithm, thereby improving the stability of the transit time calculation results and enabling high-precision quantitative computation of the transit time in the oxygen activation injection profile logging. …”
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Biosynthesis, applications, and mathematical modeling dynamics of lactic acid bacteria exopolysaccharides: A review by Ankit Barot, Kalyan Das, Yogesh Patel, et al.

“…These models improve the economic viability of LAB-EPS production by optimizing output and reducing substrate use. …”
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Distributionally robust microgrid formation for service restoration in distribution systems against extended extreme events by Ran Zhu, Hongzhe Liu, Wenwu Yu, Wei Gu, Jin Zhao

“…Furthermore, to enhance the computational efficiency, a parallel solving strategy is developed, based on the column-and-constraint generation algorithm, the alternating optimization procedure, and the progressive hedging algorithm. …”
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Modeling LTE-advanced cell capacity estimation using packet bundling and carrier aggregation by Rajiv Senapati

“…In this context, smart network planning management requires the estimation and enhancement of capacity in terms of the number of subscribers within a cell for better QoS provisioning through radio resource usage optimization. The model proposed in this article explicitly uses some long term evolution (LTE)-Advanced (LTE-A)-specific enhancements such as carrier aggregation (CA) and channel quality indication (CQI)-based resource allocation. …”
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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

“…One of the key directions for improving building performance is the optimization of building control systems. …”
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Mitigating spatial hallucination in large language models for path planning via prompt engineering by Hongjie Zhang, Hourui Deng, Jie Ou, Chaosheng Feng

“…To address this, we propose S2ERS, an LLM-based technique that integrates entity and relation extraction with the on-policy reinforcement learning algorithm Sarsa for optimal path planning. We introduce three key improvements: (1) To tackle the hallucination of spatial, we extract a graph structure of entities and relations from the text-based maze description, aiding LLMs in accurately comprehending spatial relationships. (2) To prevent LLMs from getting trapped in dead ends due to context inconsistency hallucination by long-term reasoning, we insert the state-action value function Q into the prompts, guiding the LLM’s path planning. (3) To reduce the token consumption of LLMs, we utilize multi-step reasoning, dynamically inserting local Q-tables into the prompt to assist the LLM in outputting multiple steps of actions at once. …”
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Systematic Review on Algorithmic Trading by David Jukl, Jan Lansky

“…This review provides a robust foundation for academics and practitioners to innovate and optimize algorithmic trading strategies.…”
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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

“…While deep learning (DL) offers strong capabilities for pattern recognition, single-model architectures often lack robustness. Thus, hybrid and optimized DL models are increasingly necessary to improve detection performance and address data imbalance and noise. …”
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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

“…Optimal prediction accuracy was observed in clear weather (RMSE = 0.71 °C), whereas rainy/snowy conditions showed a 42.9% improvement in MAPE compared to the PSO-BP model. …”
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Hybrid model for wind power estimation based on BIGRU network and error discrimination‐correction by Yalong Li, Ye Jin, Yangqing Dan, Wenting Zha

“…Additionally, a sequential model‐based algorithmic configuration optimizes bidirectional gating recurrent unit's network hyperparameters. …”
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A Detailed Review for Predicting the Quantity of Sugar From Sugarcane Using Various Models by Kathirvel Narayanasamy, Ilayaraja Venkatachalam

“…To improve prediction accuracy and overcome existing limitations, future research should concentrate on developing advanced models that mitigate multicollinearity. …”
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FPCAM: A Weighted Dictionary-Driven Model for Single-Cell Annotation in Pulmonary Fibrosis by Guojun Liu, Yan Shi, Hongxu Huang, Ningkun Xiao, Chuncheng Liu, Hongyu Zhao, Yongqiang Xing, Lu Cai

“…It achieves accurate and efficient cell-type annotation through similarity matrix construction and optimized matching algorithms. To evaluate its performance, we compared FPCAM with state-of-the-art annotation models, including SCSA, SingleR, and SciBet. …”
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Diagnostic models for sepsis-associated encephalopathy: a comprehensive systematic review and meta-analysis by Tengfei Zhou, Tengfei Zhou, Xinming Tian, Wei Wang, Zhe Chu

“…A total of 29 predictive models were developed, comprising 10 optimal models, primarily utilizing logistic regression or machine learning algorithms. …”
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