Enhancing microgrid forecasting accuracy with a TCNN-TLS framework: A novel approach to mitigating uncertainty in renewable energy and load predictions by Md. Omer Faruque, Md. Majharul Islam, Md Jakaria Talukder, Arif Mia, Shahriar Tasnim, Md. Alamgir Hossain, S.M. Muyeen

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Stochastic Movement Swarm Performing a Coverage Task with Physical Parameters by Krzysztof FALKOWSKI, Michał DUDA

“…This paper describes an attempt of implementing physical parameters into a virtual swarm algorithm solution. It defines which physical parameters of the single object need to be known to properly transfer a virtual algorithm into a physical system. …”
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Advanced Technologies for Smart Fertilizer Management in Agriculture: A Review by Jian-Jun Liu, Hao Wu, Imran Riaz

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Multi-resource joint management strategy for 5 G network slicing based on POMDP by Yale Li

“…Furthermore, the model employs a hybrid heuristic value iterative algorithm to optimize computational efficiency, reduce network latency, improve throughput, and enhance resource utilization. …”
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College psychological stress assessment system based on LabVIEW and WTA integration by Ting Wang

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Improving classifier decision boundaries and interpretability using nearest neighbors by Johannes Schneider, Arianna Casanova

“…To address this issue, we propose a simple algorithm that performs a weighted average of a sample’s prediction and those of its nearest neighbors (computed in latent space), leading to minor but favorable outcomes across a variety of important performance measures for neural networks. …”
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Parameterization of user functions in digital signal processing for obtaining angular superresolution by A. A. Shchukin, A. E. Pavlov

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MAT-FHE: arbitrary dimension matrix multiplication scheme for floating point over fully homomorphic encryption by Yatao Yang, Zhaofu Li, Yucheng Ding, Man Hu

“…However, it has not come up with an optimal solution for modern machine learning frameworks, partially due to a lack of efficient matrix computation mechanisms. …”
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Fields2Benchmark: An open-source benchmark for coverage path planning methods in agriculture by Gonzalo Mier, Ana María Casado Faulí, João Valente, Sytze de Bruin

“…Results demonstrate its ability to handle complex field geometries, compare algorithms effectively, and evaluate computational performance. …”
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An interpretable CT-based machine learning model for predicting recurrence risk in stage II colorectal cancer by Ziqi Wu, Liya Gong, Jingwen Luo, Xiaobo Chen, Fan Yang, Junyan Wen, Yanyu Hao, Zhishan Wang, Ruozhen Gu, Yuqin Zhang, Hai Liao, Ge Wen

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Efficient quantum circuit research and implementation for 16-bit S-boxes based on composite field by Lei Zhang, Guoyuan Li, Jingchen Dai, Ruipeng Hong, Chaoen Xiao, Jianxin Wang, Yifan Zhang

“…In the linear component, a dynamic optimal pivot selection strategy is proposed to effectively optimize the Gaussian elimination process while maintaining the row echelon form of the matrix, thereby reducing the number of CNOT gates. …”
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Structure for interaction software process modules in the development of technological processes of cast by Yu. N. Fasevich, F. I. Rudnitsky

“…The software algorithm uses the means of computational experiment to determine the optimal values of the parameters in the development of cast processes. …”
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The Fine Feature Extraction and Attention Re-Embedding Model Based on the Swin Transformer for Pavement Damage Classification by Shizheng Zhang, Kunpeng Wang, Zhihao Liu, Min Huang, Sheng Huang

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A Validity Index for Clustering Evaluation by Grid Structures by Jiachen Wang, Zuojing Zhang, Shihong Yue

“…Most existing indexes are designed for the evaluation of results from the most-used K-means clustering algorithm; it can identify only spherical clusters rather than arbitrary clusters. …”
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University proceedings. Volga region. Technical sciences by Yu.V. Dubenko, E.E. Dyshkant, V.A. Demidov

“…Reinforcement learning paradigm methods, genetic algorithm. Results. As a result, a method for synthesizing and automatically adapting the architecture of a hierarchical MAS was developed, characterized by automatic modification of a set of agent connections during the operation of the MAS (as well as basic rules that determine the conditions for the emergence of connections), the ability to determine the optimal parameters of the MAS for a specific environment using a genetic algorithm, as well as the ability to model several types of MAS architectures. …”

Robust InceptionV3 with Novel EYENET Weights for Di-EYENET Ocular Surface Imaging Dataset: Integrating Chain Foraging and Cyclone Aging Techniques by Muhammad Ahmad Khan, Saif Ur Rehman Khan, Hafeez Ur Rehman, Suliman Aladhadh, Ding Lin

“…We couple MRFO with hierarchical feature learning to optimize the InceptionV3 model, achieving optimal hyperparameter configuration and enhancing both accuracy and computational efficiency. …”
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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

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Application of Feedforward Artificial Neural Networks to Predict the Hydraulic State of a Water Distribution Network by Leandro Evangelista, Débora Móller, Bruno Brentan, Gustavo Meirelles

“…Usually, a hydraulic model is used jointly with optimization methods, which require considerable computational effort, hindering real-time interventions. …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Despite their success, machine learning methods face fundamental limitations in optimizing complex high-dimensional energy landscapes, which motivates research into new methods to improve the robustness and performance of optimization algorithms. …”
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Active RIS-Assisted Uplink NOMA with MADDPG for Remote State Estimation in Wireless Sensor Networks by Rongzhen Li, Lei Xu

“…To address the high computational complexity and non-convex optimization challenges, this letter proposes an optimization framework based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm. …”
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