Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…The findings underscore the significant potential of optimized machine learning approaches in predicting extreme events, such as wildfires, and improving fire management strategies. …”
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Optimal parameter extraction of equivalent circuits for single- and three- phase Power transformers based on arctic puffin algorithm accomplished with experimental verification by Amlak Abaza, Ragab A. El-Sehiemy, Mohamed Assaad Hamida, Raphael Chenouard, Ahmed Bayomyi

“…This paper addresses one of the major problems which hopes to enhance the accuracy of estimation of parameters, which is critical in power transformer modeling, maintenance, and operating efficiency. In that context, this work estimates the parameters of single- and three-phase power transformers by a new optimizer called Arctic Puffin Optimization Algorithm (APO). …”
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Estimation of Lithium-Ion Battery SOC Based on IFFRLS-IMMUKF by Xianguang Zhao, Tao Wang, Li Li, Yanqing Cheng

“…To tackle the challenge of precise SOC estimation in complex environments, this study introduces an improved forgetting factor recursive least squares (IFFRLS) method, which integrates the Golden Jackal optimization (GJO) algorithm with the traditional FFRLS method. …”
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Daily runoff forecasting using novel optimized machine learning methods by Peiman Parisouj, Changhyun Jun, Sayed M. Bateni, Essam Heggy, Shahab S. Band

“…This study addresses these challenges by introducing a novel bio-inspired metaheuristic algorithm, Artificial Rabbits Optimization (ARO), integrated with various machine learning (ML) models for runoff forecasting in the Carson and Chehalis River basins. …”
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Precise Rail Transit Sleeper Positioning Technology Based on Improved YOLOv8n Model by YAN Xiaoxia, GUO Jianqin, ZHAI Huchao, LIU Yutao, LI Junxin, WANG Liangxian

“…Through optimization of loss function and structural constraints on sleeper counting, a sleeper object detection model YOLOv8n_SC is proposed based on the improved YOLOv8n model. …”
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A model for shale gas well production prediction based on improved artificial neural network by LIN Hun, SUN Xinyi, SONG Xixiang, MENG Chun, XIONG Wenxin, HUANG Junhe, LIU Hongbo, LIU Cheng

“…Moreover, the model exhibits superior prediction accuracy and stability compared to the traditional BP（error backpropagation algorithm） neural network model. …”
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An optimal design method of the resonant-free C-type filter by XU Fangwei, JIA Junwei, GUO Kai, XU Lin, CHEN Jiale, LU Yuguo

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Optimization of Offshore Saline Aquifer CO₂ Storage in Smeaheia Using Surrogate Reservoir Models by Behzad Amiri, Ashkan Jahanbani Ghahfarokhi, Vera Rocca, Cuthbert Shang Wui Ng

“…This research will demonstrate SRMs’ potential in long-term simulations and optimization of geological carbon storage in a real-world geological setting and address challenges in big data curation and model training. …”
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Optimization of trusted wireless sensing models based on deep reinforcement learning for ISAC systems by Hao Zhang, Yi Jing, Wenhui Xu, Ronghui Zhang

“…Abstract This paper investigates using deep reinforcement learning (DRL) methods for optimizing trustworthy federated learning models, with a focus on integrated sensing and communication in practical wireless sensing scenarios. …”
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Voltage Quality Enhancement of Low-Voltage Smart Distribution System Using Robust and Optimized DVR Controllers: Application of the Harris Hawks Algorithm by Mohamed Metwally Mahmoud, Yahia M. Esmail, Basiony Shehata Atia, Omar Makram Kamel, Kareem M. AboRas, Mohit Bajaj, Syed Sabir Hussain Bukhari, Daniel Eutyche Mbadjoun Wapet

“…To enhance the DVR’s control system, for surpassing nonstandard voltage with a quick response and harmonics reduction at LVL under harsh operating events, an optimal controller design using the Harris Hawks algorithm (HHA) is proposed. …”
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Structured Summarization of League of Legends Match Data Optimized for Large Language Model Input by Jooyoung Kim, Wonkyung Lee, Jungwoon Park

“…This paper introduces the League of Legends Match Data Compactor (LoL-MDC), a tool designed to transform extensive match data into a concise and structured format optimized for LLM processing. By systematically summarizing structured match information—including match overviews, player and team statistics, timeline summaries, and algorithmically selected key events—the LoL-MDC significantly reduces the data size from approximately 80,000 tokens to under 2000 tokens while retaining analytical value. …”
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A two stage differential evolution algorithm for parameter estimation of proton exchange membrane fuel cell by Mohammad Aljaidi, Sunilkumar P. Agrawal, Pradeep Jangir, Sundaram B. Pandya, Anil Parmar, Arpita, Ali Fayez Alkoradees, Bhargavi Indrajit Trivedi, Mohammad Khishe

“…Most traditional parameter estimation methodologies depend on optimization algorithms which are limited in their efficiency, convergence speed, and robustness. …”
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Rice disease and pest identification integrating albert pre-trained language model and improved BILSTM by Zhigui Dong, Tianyi Yang, Yanchao Wang

“…At the same time, a bidirectional long short-term memory network is introduced for further recognition, and the model is optimized using conditional random fields to design a fusion algorithm for rice disease and pest recognition. …”
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Development of a Mathematical Model and Structural Optimization of the Specific Resistance of a Broken Line Subsoiler by Da Qiao, Qian Shi, Pinyan Lv, Yingjie Guo, Daping Fu, Min Liu, Limin Jiang, Yang Wang, Jingli Wang, Weizhi Feng

“…Aiming at the problems of shallow subsoiling depth, large subsoiling specific resistance and small soil bulkiness in subsoiling operation in saline-alkali soil, this paper establishes a mathematical model of the specific resistance of a broken line subsoiler and uses genetic algorithm and the discrete element method to optimize the structure design of the subsoiler. …”
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Learning Improvement Heuristics for Multi-Unmanned Aerial Vehicle Task Allocation by Boyang Fan, Yuming Bo, Xiang Wu

“…In this paper, a NeuroSelect Discrete Particle Swarm Optimization (NSDPSO) algorithm is presented for the Multi-UAV Task Allocation (MUTA) problem. …”
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Rapid Path Planning Algorithm for Percutaneous Rigid Needle Biopsy Based on Optical Illumination Principles by Jian Liu, Shuai Kang, Juan Ren, Dongxia Zhang, Bing Niu, Kai Xu

“…Traditional methods relying on clinician expertise or slow algorithms struggle with complex anatomical modeling for structures such as blood vessels. …”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“… In view of the difficulty of snow leopard detection and recognition in infrared camera images, a snow leopard detection algorithm is proposed based on EfficientDet, which combines domain migration and new attention mechanism.Firstly, the algorithm adopts image enhancement to expand the training sample and adds non-snow leopard images to optimize the dataset structure to improve the robustness of the model. …”
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A Novel Overload Control Algorithm for Distributed Control Systems to Enhance Reliability in Industrial Automation by Taikyeong Jeong

“…The proposed method is integrated with a modular multi-functional processor (MFP) architecture, designed to enhance system reliability, optimize resource utilization, and improve fault resilience under dynamic operational conditions. …”
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Improved Dab-Deformable Model for Runway Foreign Object Debris Detection in Airport Optical Images by Yang Cao, Yuming Wang, Yilin Zhu, Rui Yang

“…First, this paper introduces a Lightweight Deep-Shallow Feature Fusion algorithm (LDSFF), which integrates a hotspot sensing network and a spatial mapping enhancer aimed at focusing the model on significant regions. …”
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A population spatialization method based on the integration of feature selection and an improved random forest model. by Zhen Zhao, Hongmei Guo, Xueli Jiang, Ying Zhang, Changjiang Lu, Can Zhang, Zonghang He

“…Additionally, considering the imbalanced in population spatial distribution, we used the K-means ++ clustering algorithm to cluster the optimal feature subset, and we used the bootstrap sampling method to extract the same amount of data from each cluster and fuse it with the training subset to build an improved random forest model. …”
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