A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction by Gao Wang, Shuang Xu, Zixu Chen, Youzhu Li

“…Experimental results indicate substantial improvements in key metrics including the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R²), with R² values consistently exceeding 99.4% and achieving over 5% enhancement compared to the baseline GRU model. This research establishes a novel methodological framework for analyzing agricultural price forecasting while providing reliable technical support for market monitoring and policy regulation.…”
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Low‐carbon economic operation of multi‐energy microgrid based on multi‐level robust optimisation by Wenwen He, Xiong Wu, Xiaofei Li, Mingkang He, Binrui Cao, Xiuli Wang

“…Abstract The economic and low‐carbon operation strategy of multi‐energy microgrids (MEM) has become an important research topic in smart grids. The operation of MEM is affected by uncertain factors from renewable energy and internal load. …”
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SAR Image Registration Based on SAR-SIFT and Template Matching by Shichong Liu, Xiaobo Deng, Chun Liu, Yongchao Cheng

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Integrating Fine-Grained Classification and Motion Relation Analysis for Face Anti-Spoofing by Ziyang Cheng, Xiafen Zhang

“…By introducing an attention mechanism, the MCAN uses the RAFT optical flow algorithm to adaptively focus on the direction and intensity of micro-movements in key face regions, distinguishing the natural movement of real faces from the static or repetitive motion patterns in spoofing attacks. …”
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Knowledge Discovery Using Clustering Methods in Medical Database: A Case Study for Reflux Disease by Fatma Rıdaouı, Yunus Doğan

“…However, a large database required that is specific for Reflux disease to implement these applications is available only at the Reflux Research Center in Ege University in Turkey. By benefiting the Short Form36 and Quadrad12 questionnaire data in this database, 3,909 patients and many artificial intelligence algorithms were used to discover the hidden associations among responses in the quality of life of these patients. …”
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A novel similarity-constrained feature selection method for epilepsy detection via EEG signals by Chunlei Shi, Jun Gao, Jian Yu, Lingzhi Zhao, Faxian Jia

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Enhancing Performance and Stability of Wing-Alone UAV: A Comprehensive Mathematical Model and Simulation Approach Using MATLAB and Simulink by G. Ramanan, N. Rahul, V. E. Sathishkumar, Indraraj Upadhyaya

“…The novel objective of this study is enhancing the performance and stability aspects of the wing-alone UAV through code-based reports and the implementation of custom MATLAB algorithms. The wing-alone UAV demonstrated a 15% improvement in aerodynamic efficiency and a 10% reduction in overall weight compared to baseline designs. …”
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Comparison of Machine Learning and Classic Methods on Aerodynamic Modeling and Control Law Design for a Pitching Airfoil by Lang Yan, Xinghua Chang, Nianhua Wang, Laiping Zhang, Wei Liu, Xiaogang Deng

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Quantized convolutional neural networks: a hardware perspective by Li Zhang, Olga Krestinskaya, Mohammed E. Fouda, Ahmed M. Eltawil, Khaled Nabil Salama

“…Based on the analysis, we discuss open challenges and future research directions for both algorithms and corresponding hardware designs of quantized neural networks (QNNs).…”
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FW-S3KIFCM: Feature Weighted Safe-Semi-Supervised Kernel-Based Intuitionistic Fuzzy C-Means Clustering Method by Shirin Khezri, Nasser Aghazadeh, Mahdi Hashemzadeh, Amin Golzari Oskouei

“…Semi-supervised clustering (SSC) methods have emerged as a notable research area in machine learning. These methods integrate prior knowledge of class distribution into their clustering process. …”
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Swarm intelligence based classification rule induction (CRI) framework for qualitative and quantitative approach: An application of bankruptcy prediction and credit risk analysis by J. Uthayakumar, T. Vengattaraman, P. Dhavachelvan

“…Most of the earlier research works were carried out on quantitative methods, while few studies have proposed on qualitative methods to improvise the performance of bankruptcy prediction models. …”
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Machine Learning Approach to Quantity Management for Long-Term Sustainable Development of Dockless Public Bike: Case of Shenzhen in China by Qingfeng Zhou, Chun Janice Wong, Xian Su

“…Second, five classification algorithms were compared in the accuracy of distinguishing the type of bicycle gathering areas using 25 impact factors. …”
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Operation Optimization of Multiphase Pollutant Treatment Considering Carbon Emissions by Guo Yu, Dongjie Zhang, Hailong Deng, Chao Jiang, Quanling Zhang

“…Under the same experimental conditions, we compare our model with the multiphase pollutant treatment research only considering the waste-water flow and energy consumption. …”
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Historical Manuscripts Analysis: A Deep Learning System for Writer Identification Using Intelligent Feature Selection with Vision Transformers by Merouane Boudraa, Akram Bennour, Mouaaz Nahas, Rashiq Rafiq Marie, Mohammed Al-Sarem

“…We utilize the FAST detector for feature detection, extracting keypoints representing handwriting styles, followed by clustering with the k-means algorithm to obtain meaningful patches of uniform size. …”
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Comparison of Directional and Diffused Lighting for Pixel-Level Segmentation of Concrete Cracks by Hamish Dow, Marcus Perry, Jack McAlorum, Sanjeetha Pennada

“…A novel directional lighting image segmentation algorithm is proposed, which applies crack segmentation image processing techniques to each directionally lit image before combining all images into a single output, highlighting the extremities of the defect. …”
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Regularized K-Means Clustering via Fully Corrective Frank-Wolfe Optimization by Ahmed Yacoub Yousif, Basad Al-Sarray

“… Clustering high-dimensional data remains challenging because traditional k-means is sensitive to noise, outliers, and high dimensionality, often leading to unstable performance. The research presents a robust clustering system which combines the Fully Corrective Frank-Wolfe (FCFW) algorithm with k-means objective that uses Frobenius norm regularization. …”
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ESO-Based Non-Singular Terminal Filtered Integral Sliding Mode Backstepping Control for Unmanned Surface Vessels by Jianping Yuan, Zhuohui Chai, Qingdong Chen, Zhihui Dong, Lei Wan

“…Theoretical analysis and simulation results demonstrate that the proposed control algorithm improves the convergence speed, adaptive ability, and anti-interference ability in complex environments compared to traditional linear backstepping sliding mode control, thereby enhancing its engineering practicability. …”
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Node-Based Graph Convolutional Network With SLIC Method for Breast Cancer Ultrasound Images Classification by Kien Trang, Fung Fung Ting, Bao Quoc Vuong, Chee-Ming Ting

“…This research presents a novel node-based Graph Convolutional Network (GCN) approach for the classification of breast cancer from ultrasound images. …”
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Identifying the Peak Flowering Dates of Winter Rapeseed with a NBYVI Index Using Sentinel-1/2 by Fazhe Wu, Peng Lu, Shengbo Chen, Yucheng Xu, Zibo Wang, Rui Dai, Shuya Zhang

“…The study uses phenological characteristics and the random forest classification algorithm to create a map of winter rapeseed in parts of the middle and lower reaches of the Yangtze River Basin, achieving a Kappa coefficient of 90.57%. …”
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Artificial intelligence-assisted optimization of Eichhornia crassipes extracts and evaluation of their biological activities by Nuh Korkmaz

“…Abstract In this research, the extraction conditions for Eichhornia crassipes (Mart.) …”
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