Toward accurate and scalable rainfall estimation using surveillance camera data and a hybrid deep-learning framework by Fiallos-Salguero Manuel, Soon-Thiam Khu, Jingyu Guan, Mingna Wang

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High-resolution surface soil moisture retrieval: A hybrid machine learning framework integrating change detection and downscaling for precision water management by Zihao Wang, Qi Gao, Michele Crosetto, Maria Jose Escorihuela

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A Hybrid Deep Learning–Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Survivors of Cancer: Cross-Sectional Study by Tracy Huang, Chun-Kit Ngan, Yin Ting Cheung, Madelyn Marcotte, Benjamin Cabrera

“…MethodsWe devised a hybrid deep learning–based feature selection approach to support early detection of negative long-term behavioral outcomes in survivors of cancer. …”
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Innovative Sandia Frequency Shift Islanding Detection for Microgrids Using Interval Type-II Fuzzy Logic and VP-PSO Optimization by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Yeonwoo Lee, Sun-Kyoung Kang, Ilhami Colak, El Manaa Barhoumi, Kei Eguchi

“…The proposed approach further integrates a variable-parameter PSO (VP-PSO) algorithm to optimize both fuzzy membership functions and controller parameters. …”
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A Novel Method for Inverting Deep-Sea Sound-Speed Profiles Based on Hybrid Data Fusion Combined with Surface Sound Speed by Qiang Yuan, Weiming Xu, Shaohua Jin, Xiaohan Yu, Xiaodong Ma, Tong Sun

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Sustainable phytoprotection: a smart monitoring and recommendation framework using Puma Optimization for potato pathogen detection by Amal H. Alharbi, Faris H. Rizk, Khaled Sh. Gaber, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Pushan Kumar Dutta, Doaa Sami Khafaga

“…Ensuring sustainable and resilient agricultural systems in the face of intensifying crop disease threats requires intelligent, data-driven tools for early detection and intervention. This study proposes a novel hybrid framework for potato disease classification that integrates copula-based dependency modeling with a Restricted Boltzmann Machine (RBM), further enhanced through hyperparameter tuning using the biologically inspired Puma Optimization (PO) algorithm. …”
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Hybrid deep learning for IoT-based health monitoring with physiological event extraction by Sivanagaraju Vallabhuni, Kumar Debasis

“…Methods This paper presents a novel hybrid machine-learning model by amalgamating Convolutional Neural Networks (CNNs) with Long Short-Term Memory models (LSTMs) to boost prediction accuracy. …”
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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…The methodology consists of three main phases: (i) data preprocessing, including anomaly detection and missing value handling; (ii) exploratory analysis to identify trends and correlations between PM concentrations (PMs) and predictor variables; and (iii) model development using 23 machine learning and deep learning algorithms, enhanced by 50 feature selection techniques. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…The algorithm began with the initialization of optimization variables， constraints， Pareto front size， and key parameters such as frequency， loudness， and pulse rates. …”
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Hybrid Optimized Feature Selection and Deep Learning Method for Emotion Recognition That Uses EEG Data by asmaa Bashar Hmaza, Rajaa K. Hasoun

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Integrating transcriptomics and hybrid machine learning enables high-accuracy diagnostic modeling for nasopharyngeal carcinoma by Hehe Wang, Junge Zhang, Peng Cheng, Lujie Yu, Chunlin Li, Yaowen Wang

“…The findings provide a scalable framework for early NPC detection and novel insights into immune microenvironment dysregulation.…”
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Insurance claims estimation and fraud detection with optimized deep learning techniques by P. Anand Kumar, S. Sountharrajan

“…Overcoming challenges such as local minima and slow convergence, dynamic population adjustment, momentum-based updates, and hybrid fine-tuning are used with the EHOA. The experimental results reveal that the newly proposed EHOA-CNN-12 attains excellent accuracy (92%) and efficiency in comparison to other state-of-the-art approaches in claims estimation and fraud detection tasks.…”
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Automatic melanoma detection using an optimized five-stream convolutional neural network by Vida Esmaeili, Mahmood Mohassel Feghhi, Hadi Seyedarabi

“…However, automatic melanoma detection has several significant challenges. These challenges include the lack of a balanced dataset, high variability within melanoma lesions, differences in the locations of skin lesions in images, the similarity between different skin lesions, and the presence of various artifacts. …”
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Diagnostic accuracy of artificial intelligence for obstructive sleep apnea detection: a systematic review by Sara Haghighat, Muhammed Joghatayi, Julien Issa, Sarina Azimian, Janet Brinz, Ali Ashkan, Akhilanand Chaurasia, Zahra Rahimian, Linda Sangalli

“…Artificial intelligence (AI) algorithms can facilitate diagnosis by detecting patients’ signs and symptoms. …”
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Hybrid closed-loop systems for managing blood glucose levels in type 1 diabetes: a systematic review and economic modelling by Asra Asgharzadeh, Mubarak Patel, Martin Connock, Sara Damery, Iman Ghosh, Mary Jordan, Karoline Freeman, Anna Brown, Rachel Court, Sharin Baldwin, Fatai Ogunlayi, Chris Stinton, Ewen Cummins, Lena Al-Khudairy

“…The individual must self-administer insulin and monitor their blood glucose levels. Hybrid closed-loop systems provide a control algorithm that reviews data and the impact of its past actions. …”
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Improving Segmentation of MRI Images of Brain Glial Cells Using Fuzzy C-Means Algorithm and Combination of PET Images by Wei Wang, Wu Beibei

“…The Fuzzy C-means (FCM) algorithm is employed to cluster MRI images, which are then enhanced by applying PET-derived masks. …”
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Enhanced Heart Disease Classification Using Dual Attention Mechanisms and 3D-Echo Fusion Algorithm in Echocardiogram Videos by S Deepika, N. Jaisankar

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DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

“…However, due to the variability in scale and shape of PV installations in complex environments, the detection results often fail to capture detailed information and struggle to scale for multi-scale PV systems. …”
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A Deep Learning Approach for Fault Detection and Localization in MT-VSC-HVDC System Utilizing Wavelet Scattering Transform by Manohar Mishra, Debadatta Amaresh Gadanayak, Abha Pragati, Jai Govind Singh

“…This study presents a novel algorithm for automatic fault detection in multi-terminal voltage source converter-based high voltage direct current (MT-VSCHVDC) systems. …”
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Characterization of Historical Aerosol Optical Depth Dynamics Using LSTM and Peak Enhancement Techniques by Horia-Alexandru Cămărășan, Alexandru Mereuță, Lucia-Timea Deaconu, Horațiu-Ioan Ștefănie, Andrei-Titus Radovici, Camelia Botezan, Zoltán Török, Nicolae Ajtai

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