An Underground Goaf Locating Framework Based on D-InSAR with Three Different Prior Geological Information Conditions by Kewei Zhang, Yunjia Wang, Feng Zhao, Zhanguo Ma, Guangqian Zou, Teng Wang, Nianbin Zhang, Wenqi Huo, Xinpeng Diao, Dawei Zhou, Zhongwei Shen

“…Furthermore, this investigation discusses the influence of deformation spatial resolution, the impacts of azimuth determination methodologies, and performance comparisons between non-hybrid and hybrid optimization algorithms. This study demonstrates that aligning the selection of deformation models with different types of prior geological information significantly improves the accuracy of underground goaf detection. …”
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Application of a GA-BP Neural Network in Accurately Characterizing the Diffusion Range of Groundwater Pollutants by Jiayun JI, Xiao XIAO, Pinlu YANG, Yang LIU, Yahong ZHOU

“…The GA-BP neural network, optimized with a Genetic Algorithm, showed the best performance, filling gaps in data and allowing for a more accurate concentration distribution map. …”
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The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…Some models integrate with Internet of Things (IoT) frameworks or federated learning for real-time diagnostics and privacy, often paired with optimization algorithms. …”
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Climate risk and low-carbon policies: implications for sports economics and global events by Siyu Fu, Chen Kong

“…ICSF, on the other hand, leverages game theory and optimization algorithms to enhance decision-making in areas such as resource allocation, salary cap management, and sustainability-oriented strategic planning.ResultsEmpirical results from multiple datasets and experiments confirm that the integration of climate risk and low-carbon policy variables significantly improves the predictive accuracy and resilience of economic planning in the sports sector.DiscussionThis research provides theoretical advancements and practical insights for policymakers, sports managers, and investors seeking to navigate the complex interplay between sustainability and profitability in a rapidly changing global environment.…”
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Power quality solutions for rail transport using AI-based unified power quality conditioners by D. K. Nishad, A. N. Tiwari, Saifullah Khalid, Sandeep Gupta

“…Abstract This paper proposes an artificial intelligence-based Unified Power Quality Conditioner (AI-UPQC) and a unique Dynamic K-factor PI (DKPI) algorithm for PI-UPQC to address power quality issues in electrified railway systems. …”
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Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

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Deep Q-Networks for Minimizing Total Tardiness on a Single Machine by Kuan Wei Huang, Bertrand M. T. Lin

“…Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. …”
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Rolling window for detecting multiple Chan signatures to diagnose excessive water production by Ahmed MohamedSalih Musa Hamdoon, A. P. Mohammed Abdalla Ayoub Mohammed, A. P. Khaled Abdalla Elraies

“…A successful interactive model with the rolling window feature was developed to track slope changes in Chan signatures, resulting in a 7–10% improvement in pattern detection accuracy compared to static features. …”
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Development of intelligent tools to predict neuroblastoma risk stratification and overall prognosis based on multiphase enhanced CT and clinical features by Wei Zhao, Yahui Han, Xiaokun Yu, Jianing Liu, Jiao Zhang, Juan Li

“…The aim of this study was to develop a deep learning model based on multiphase enhanced CT images and clinical features to improve the accuracy of risk stratification and prognostic assessment of NB.MethodsMulti-phase enhanced CT images and clinical features from 202 NB patients were collected. …”
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Dual-Modal Approach for Ship Detection: Fusing Synthetic Aperture Radar and Optical Satellite Imagery by Mahmoud Ahmed, Naser El-Sheimy, Henry Leung

“…This framework incorporates a detection system for optical images that utilizes Contrast Limited Adaptive Histogram Equalization (CLAHE) in combination with the YOLOv7 model to improve accuracy and processing speed. For SAR images, a customized Detection Transformer model, SAR-EDT, integrates advanced denoising algorithms and optimized pooling configurations. …”
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Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

“…After the water conservation retrofit, non-saline soil increased by 326.5 km2, indicating improved soil conditions. The overall accuracy of the Gradient Boosting Tree classification model is 95.00 % and the Kappa coefficient is 0.93, which is the optimal model for land use type classification. …”
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HASSDE-NAS: Heuristic–Adaptive Spectral–Spatial Neural Architecture Search with Dynamic Cell Evolution for Hyperspectral Water Body Identification by Feng Chen, Baishun Su, Zongpu Jia

“…Additionally, a bidirectional fusion alignment cell jointly optimizes spectral and spatial dependencies. A heuristic cell search algorithm optimizes the network architecture through architecture stability, feature diversity, and gradient sensitivity analysis, which improves search efficiency and model robustness. …”
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Research of Regenerative Braking Strategy for Electric Vehicles by Van Nghia Le, Hoang Phuc Dam, Trong Hoan Nguyen, S. V. Kharitonchik, V. A. Kusyak

“…The carried out investigations confirm the available significant potential for improving the efficiency of the electric vehicles usage by developing the control strategy and algorithms of the braking energy regeneration.…”
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Multi-Source Heterogeneous Data-Driven Digital Delivery System for Oil and Gas Surface Engineering by Wei Zhang, Zhixiang Dai, Taiwu Xia, Gangping Chen, Yihua Zhang, Jun Zhou, Cui Liu

“…To address the challenges of data fragmentation, inconsistent standards, and weak interactivity in oil and gas field surface engineering, this study proposes an intelligent delivery system integrated with three-dimensional dynamic modeling. Utilizing a layered collaborative framework, the system combines optimization algorithms and anomaly detection methods during data processing to enhance the relevance and reliability of high-dimensional data. …”
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Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning by Feng Lu, Yingying Liu, Zhen Chen, Shuning Chen, Weidong Liang, Fuzhou Hua, Maolin Zhong, Lifeng Wang

“…A total of 113 diagnostic models were developed through 12 machine learning algorithms, with the optimal model, “Lasso + Stepglm[both],” featuring six genes: Abca1, Cdh1, Glipr1, Glt8d2, Il10ra, and Pde5a. …”
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Enhancing Autonomous Driving Perception: A Practical Approach to Event-Based Object Detection in CARLA and ROS by Jingxiang Feng, Peiran Zhao, Haoran Zheng, Jessada Konpang, Adisorn Sirikham, Phuri Kalnaowakul

“…While the previous research on event-based object detection has predominantly focused on algorithmic enhancements via advanced preprocessing and network optimizations to improve detection accuracy, the practical engineering and integration challenges of deploying these sensors in real-world systems remain underexplored. …”
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Deep learning-based semantic segmentation with novel navigation line extraction for autonomous agricultural robots by Chijioke Leonard Nkwocha, Ning Wang

“…This improvement is critical for ensuring precise and stable robot navigation in agricultural fields. …”
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Know your competitor! Analyzing and predicting the location of competing stores: The case study of Valora at Swiss railway stations by Thomas Wieland

“…Machine learning algorithms are used to check and optimize the predictive ability of the models. …”
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Signal Mining and Analysis of Drug-Induced Myelosuppression: A Real-World Study From FAERS by Kaiyue Xia MM, Shupeng Chen MD, Yingjian Zeng MD, Nana Tang MD, Meiling Zhang MD

“…Conclusion This study identifies new DIM-related drug signals and emphasizes the need for early detection to improve clinical management and optimize treatment regimens. …”
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Simulation of Minefield Installation in a Video Game Engine by Maksym Maksymov, Oleksii Neizhpapa, Oleksandr Toshev, Maksym Kiriakidi

“…The first objective of this research is to improve damage prediction algorithms, enabling the simulation to more accurately estimate the consequences of ships passing through a minefield. …”
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