Implementing a dung beetle optimization algorithm enhanced with multi-strategy fusion techniques by xiaojie zhou, Majid Khan Majahar Ali, Farah Aini Abdullah, Lili Wu, Ying Tian, Tao Li, Kaihui Li

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Self-Adaptive Quantiles for Precipitation Forecasting by Zied Ben Bouallègue, Maxime Taillardat

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Adaptive Scheduling in Cognitive IoT Sensors for Optimizing Network Performance Using Reinforcement Learning by Muhammad Nawaz Khan, Sokjoon Lee, Mohsin Shah

“…The main factors evaluated are joint Gaussian distributions and event correlations, with derived results of signal strengths, noise, prediction accuracy, and energy efficiency with a combined reward score. …”
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Natural hazards in electricity grids: from landscape dynamics to optimal mitigation and adaptation approaches by Ayat-Allah Bouramdane

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Optimizing learning outcomes: a deep dive into hybrid AI models for adaptive educational feedback by Hafiz Muhammad Qadir, M. Taseer Suleman, Rafaqat Alam Khan, Muhammad Sohaib, Md Junayed Hasan, Syed Abid Hussain

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Data Biases in Geohazard AI: Investigating Landslide Class Distribution Effects on Active Learning and Self-Optimizing by Jing Miao, Zhihao Wang, Tianshu Ma, Zhichao Wang, Guoming Gao

“…While active learning (AL) offers promise for mitigating annotation costs and addressing data biases, the interplay between landslide class proportions and AL efficiency remains poorly quantified; additionally, self-optimizing mechanisms to adaptively manage class imbalances are underexplored. …”
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SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks by Sneh Pandya, Purvik Patel, Brian D Nord, Mike Walmsley, Aleksandra Ćiprijanović

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PCRFed: personalized federated learning with contrastive representation for non-independently and identically distributed medical image segmentation by Shengyuan Liu, Ruofan Zhang, Mengjie Fang, Hailin Li, Tianwang Xun, Zipei Wang, Wenting Shang, Jie Tian, Di Dong

“…The proposed weighted model-contrastive loss provides additional regularization for local models, optimizing their respective distributions while effectively utilizing information from all clients to mitigate performance challenges caused by insufficient local data. …”
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Hybrid strategy enhanced crayfish optimization algorithm for breast cancer prediction by Yu-Jiong Li

“…Finally, an adaptive ternary optimization mechanism is introduced in the exploration phase: a curve growth acceleration factor is used to collaboratively guide global and individual optimal information, while a hybrid adaptive cosine exponential weigh dynamically adjusts the search intensity. …”
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Bayesian Denoising Algorithm for Low SNR Photon-Counting Lidar Data via Probabilistic Parameter Optimization Based on Signal and Noise Distribution by Qi Liu, Jian Yang, Yue Ma, Wenbo Yu, Qijin Han, Zhibiao Zhou, Song Li

“…Existing methods, relying on fixed parameters, struggle to adapt to dynamic noise distribution in rugged mountain regions where signal and noise change rapidly. …”
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The agriculture specialization through the lens of PESTLE analysis by Khachatryan Liana, Asatryan Hovhannes, Poghosyan Shogher, Azatyan Liana, Kocharyan Tsovinar, Matinyan Alvard, Manucharyan Meri

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A Robust Authentication and Trust Detection With Privacy Preservation of Data for Fog Computing in VANET Using Adaptive Deep Neural Network by Jia Jia, Sathiya Sekar Kumarasamy, Kiran Sree Pokkuluri, K. Suresh Kumar, Thella Preethi Priyanka, Feng Wang

“…Initially, node authentication and trust detection in vehicular networks is conducted using Adaptive Deep Neural Networks (ADNN). Verification of the node’s authenticity and evaluating its trust scores will considerably minimize the chance of cyber attacks and fraudulent behavior across the system, thus enhancing the security of the entire system. …”
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Data-Driven Dynamic Optimization for Hosting Capacity Forecasting in Low-Voltage Grids by Md Tariqul Islam, M. J. Hossain, Md Ahasan Habib

“…The sustainable integration of Distributed Energy Resources (DER) with the next-generation distribution networks requires robust, adaptive, and accurate hosting capacity (HC) forecasting. …”
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Clustering of High School Students Academic Scores Using K-Means Algorithm by Chairunisa Azzahra, Sriani Sriani

“…The issue addressed in this study is how to optimally group students based on their academic scores to help schools understand the distribution of student abilities. …”
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Adapting Ensemble‐Calibration Techniques to Probabilistic Solar‐Wind Forecasting by N. O. Edward‐Inatimi, M. J. Owens, L. Barnard, H. Turner, M. Marsh, S. Gonzi, M. Lang, P. Riley

“…Making spatial perturbations to the coronal model output at 0.1 AU, we produce ensembles of inner‐boundary conditions for HUXt, evaluating how forecast accuracy was impacted by the scales of perturbations applied. We found optimal spatial perturbations described by Gaussian distributions with variances of 20° latitude and 10° longitude; these might represent spatial uncertainty within the coronal model. …”
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Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…The aim of this study was to compare the performance of three adaptive neuro-fuzzy inference systems (ANFIS) classification methodologies in classifying mastitis in Holstein dairy cattle: gradient descent (GD)-based ANFIS (GD-ANIFIS), particle swarm optimization (PSO)-based ANFIS (PSO-ANFIS) and genetic algorithm (GA)-based ANFIS (GA-ANFIS). …”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

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An enhanced substation equipment detection method based on distributed federated learning by Zhuyun Li, Qiutong Qin, Yingyi Yang, Xiaoming Mai, Yuya Ieiri, Osamu Yoshie

“…The framework’s novelty lies in its dual focus: optimizing detection performance through architectural enhancements and ensuring secure, efficient distributed learning. …”
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Optimizing Niosomal Formulations for Enhanced Cellular Applications by Nilufer Cakir, Naile Ozturk, Asli Kara, Ali Zarrabi, Nur Mustafaoglu

“…One of the most promising niosomes was selected and optimized to evaluate drug encapsulation performance of niosomes for further drug delivery adaptations by one of the chemotherapy drugs, paclitaxel (PTX). …”
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Detecting Out-of-Distribution Samples in Complex IoT Traffic Based on Distance Loss by Chengye Zhao, Jinxin Zuo, Mingrui Fan, Yun Cai, Yueming Lu, Chonghua Wang

“…Our framework utilizes Mahalanobis distance for robust OOD scoring and Kernel density estimation (KDE) for adaptive threshold selection, enabling precise boundary estimation under varying data distributions. …”
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