An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system by Bishwajit Dey, Gulshan Sharma, Pitshou N. Bokoro, Soham Dutta

“…Abstract The cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. …”
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Physical Health Portrait and Intervention Strategy of College Students Based on Multivariate Cluster Analysis and Machine Learning by Rong Guo, Rou Dong, Ni Lu, Lin Yu, Chaoxian Chen, Yonglin Che, Jiajin Zhang, Jianke Yang

“…This study employs an improved K-means algorithm integrated with machine learning models to analyze university students’ fitness data and develop personalized health intervention strategies. …”
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Hand gestures classification of sEMG signals based on BiLSTM-metaheuristic optimization and hybrid U-Net-MobileNetV2 encoder architecture by Khosro Rezaee, Safoura Farsi Khavari, Mojtaba Ansari, Fatemeh Zare, Mohammad Hossein Alizadeh Roknabadi

“…Bayesian optimization is employed as the metaheuristic approach to optimize the BiLSTM model’s architecture. …”
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A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in M... by Abhijeet Das

“…Our research in Mahanadi River Basin, Odisha, presents an enhanced methodology based on data, specifically designed to be beneficial for Water Quality (WQ) based on Synthetic Pollution Index (SPI) and machine learning models such as Long Short-Term Memory (LSTM) and Sparrow Search Algorithm (SSA), for its analysis and interpretation of extensive, intricate data sets on water quality, as well as the allocation of pollution sources or contributing elements, in order to improve knowledge of the water quality and the planning of monitoring networks for efficient water resource management. …”
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Protecting digital assets using an ontology based cyber situational awareness system by Tariq Ammar Almoabady, Yasser Mohammad Alblawi, Ahmad Emad Albalawi, Majed M. Aborokbah, S. Manimurugan, Ahmed Aljuhani, Hussain Aldawood, P. Karthikeyan

“…The dual-algorithm approach provided improved detection capabilities compared to traditional methods, underscoring its potential for scalable and effective cybersecurity applications. …”
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High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

“…The priors are constructed using cosine similarity, mean, and intensity, where intensity is computed using the improved Papoulis–Gerchberg algorithm. The image is reconstructed using the probabilistic maximum a posteriori estimate. …”
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Methodology of statistical synthesis and analysis methods for stochastic signal processing in multi-antenna radio direction finders by Eduard Tserne, Yevhen Holovynskyi, Olha Zhyla

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Experimental determination and theoretical calculation for CO2 liquid-solid phase equilibrium in PLNG by Zihe LI, Jianlu ZHU, Qing MIAO, Feng YAN, Xin OUYANG, Chaofei NIE, Hui HAN, Yuxing LI

“…The calculations demonstrated improved accuracy in CO2 solid solubility derived from the established model that was optimized using the genetic algorithm. …”
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Bayesian Time-Domain Ringing Suppression Approach in Impulse Ultrawideband Synthetic Aperture Radar by Xinhao Xu, Wenjie Li, Haibo Tang, Longyong Chen, Chengwei Zhang, Tao Jiang, Jie Liu, Xingdong Liang

“…This study systematically analyzes the mechanisms of ringing generation, including its physical origins and mathematical modeling in SAR systems. Building on this analysis, we propose a Bayesian ringing suppression algorithm based on sparse optimization. …”
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Fuzzy Multi-Agent Simulation for Collective Energy Management of Autonomous Industrial Vehicle Fleets by Juliette Grosset, Ouzna Oukacha, Alain-Jérôme Fougères, Moïse Djoko-Kouam, Jean-Marie Bonnin

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Intelligent System for Student Performance Prediction Using Machine Learning by Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani

“…This study aims to develop an intelligent solution for predicting student performance using supervised machine learning algorithms. This proposed focus on addressing the limitations of existing prediction models and enhancing prediction accuracy. …”
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Storage life evaluation of photodetector based on multi-parameter performance degradation and competitive failure by ZHANG Yeping, YANG Tongbo, LI Ziwei

“…This method comprehensively considered whether the key performance parameters of the sample have deteriorated or improved trend. Firstly, the optimal degradation model with a single parameter was selected by performance degradation modeling, so that the pseudo-life of the sample with increasing degradation trend was calculated according to the failure threshold, and the pseudo-life was regarded as the right-censored data for the sample with decreasing degradation trend. …”
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The analysis of sculpture image classification in utilization of 3D reconstruction under K-means++ by Xuhui Wang

“…To overcome this challenge, this study proposes an innovative image classification method that combines the ResNet50 model from the Deep Convolutional Neural Network (DCNN) with the K-means++ clustering algorithm. …”
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Trade-Space Exploration With Data Preprocessing and Machine Learning for Satellite Anomalies Reliability Classification by Abdul Mutholib, Nadirah Abdul Rahim, Teddy Surya Gunawan, Mira Kartiwi

“…Leveraging a Seradata dataset spanning 66 years and 4,455 satellite records, the framework systematically evaluates four data cleaning methods, four data transformation techniques, five normalization strategies, and seven machine learning algorithms across 480 configurations. The optimal configuration, comprising Iterative Imputation, FastText, Robust Scaling, and Decision Tree, achieved the highest testing accuracy of 95.74% with competitive computational efficiency. …”
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Quantum-enhanced digital twin IoT for efficient healthcare task offloading by Ahmed K. Jameil, Hamed Al-Raweshidy

“…Empirical evaluations show that quantum preprocessing improved Task Offloading Success Rate (TOSR) by 32% and reduced the Error Rate (ER) by 80%, significantly outperforming traditional DT-based healthcare models. …”
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Integrated energy microgrid bi-level game scheduling optimization taking into account electricity-heat-hydrogen enriched compressed natural gas coupling and shared energy storage by Changgang Wang, Xiaoning Sun

“…Finally, the proposed model is solved using the Black-winged Kite algorithm in conjunction with the CPLEX solver.Case studies demonstrate the effectiveness of the proposed method, showing revenue increases of 9.15% for integrated energy microgrid operators and 8.29% for load aggregators, alongside a reduction in carbon emissions by 8.76%.…”
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A multiobjective continuation method to compute the regularization path of deep neural networks by Augustina Chidinma Amakor, Konstantin Sonntag, Sebastian Peitz

“…Sparsity is a highly desired feature in deep neural networks (DNNs) since it ensures numerical efficiency, improves the interpretability (due to the smaller number of relevant features), and robustness. …”
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YOLOv5-DTW: Gesture recognition based on YOLOv5 and dynamic time warping for digital media design by Lu Zhao, Jing Yu

“…In the recognition stage, firstly, the background and sensor thermal noise are used to enhance the classification data set, and the background optimization preprocessing algorithm is designed to improve the adaptability of the model to the complex background. …”
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Quantum chimp-enanced SqueezeNet for precise diabetic retinopathy classification by Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, Yousef A. Alduraywish, Alishba Tahir, Haixia Long

“…This paper presents an advanced hybrid approach that utilizes the Quantum Chimp Optimization Algorithm (QCOA) integrated with SqueezeNet to enhance the accuracy and efficiency of DR classification significantly. …”
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Hybrid Techniques for Short Term Load Forecasting by Saroj Panda, Papia Ray, Surender Salkuti

“…Because of its openness in modeling, simplicity of implementation, and improved performance, the ANN-based STLF model has gained traction. …”
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