Neural Network-Based Imitation Learning for Approximating Stochastic Battery Management Systems by Andrea Pozzi, Alessandro Incremona, Daniele Toti

“…Traditional predictive control methods are limited by their reliance on precise models, which are often hindered by uncertainties in battery parameters due to aging, production variability, and operational conditions. While stochastic predictive control policies can address these uncertainties by incorporating them directly into the optimization process, they typically introduce considerable computational complexity. …”
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Artificial Neural Network Prediction on negative and positive activation energy of magnetohydrodynamic nanofluid flow with multiple slips by Shovan Sarkar, Hiranmoy Mondal, Prabir Kumar Kundu

“…Another important matter to discuss here that we have used feed-forward back-propagation multilayer perceptron artificial neural network with Levenberg-Marquard algorithm as the training algorithm to predict the Sherwood number for both activation energy values 1 and -1. …”
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PV<i>k</i>NN: A Publicly Verifiable and Privacy-Preserving Exact <i>k</i>NN Query Scheme for Cloud-Based Location Services by Jingyi Li, Yuqi Song, Chengliang Tian, Weizhong Tian

“…Leveraging Paillier’s homomorphic cryptosystem and public-key signature techniques, our design achieves heightened security by safeguarding databases, query access patterns, and result integrity while enabling public verification. Additionally, our scheme enhances computational efficiency through optimized data-packing techniques and simplified Voronoi diagram-based ciphertext index construction, leading to substantial savings in computational and communication overheads. …”
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Low-Power Portable System for Power Grid Foreign Object Detection Based on the Lightweight Model of Improved YOLOv7 by Yonghuan He, Rong Wu, Chao Dang

“…Foreign objects caught and entangled on power grid transmission lines, power towers and other equipment can pose potential threats to the power system. The detection algorithm for foreign objects in the power grid cannot achieve the optimal balance in terms of accuracy and efficiency. …”
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Multi-Objective-Based Multi-Heterogeneous- Agent Deep Reinforcement Learning for Minimization of Voltage Deviation and Operation Cost in Active Distribution System by Anurak Deanseekeaw, Watcharakorn Pinthurat, Boonruang Marungsri

“…Furthermore, the MATD3 algorithm reduces operational costs to 56,837.85 THB/day while generating the highest net profit of 725,943.71 THB/day from energy trading. …”
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Artificial intelligence-empowered functional design of semi-transparent optoelectronic and photonic devices via deep Q-learning by Caglar Cetinkaya, Erman Cokduygulular, Muhammed Yusuf Aykut, Okan Erkal, Fatma Aydogmus, Baris Kinaci

“…The deep Q-learning algorithm successfully identified configurations yielding a maximum photo-current density (Jph) while effectively maintaining average visible transmittance (AVT), balancing transparency, and photon harvesting by learning Maxwell’s equations. …”
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The complex treatment of acute pancreatitis using miniinvasive surgical treatment by G. I. Ohrimenko, N. G. Golovko, V. A. Grushka, T. S. Gavrilenko, P. G. Kocherov

“…Aim. In order to develop optimal diagnostic and treatment algorithm 316 patients took part in the study. …”
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Energy-efficient cooperative sensing and transmission in relay-assisted cognitive radio network by Li FENG, Yu-jun KUANG, Bin-wei WU, Xin-chuan FU

“…An innovative EE-oriented cooperative sensing and transmission scheme in relay-assisted cognitive radio networks,called energy-efficient best-relay cooperative transmission (BCT) was proposed.Based on the BCT scheme,mean energy efficiency (MEE) maximization problem with sensing duration and transmitting power as optimization variables was modeled for fading channels under constraint of minimal secondary outage probability.By virtue of Jensen’s inequality,the original optimization problem was decomposed into two relatively independent subproblems which solved sensing duration and power allocation respectively.And for the two subproblems,an efficient cross iteration based algorithm was proposed to obtain the suboptimal solutions.Both analytical and simulation results demonstrate that the proposals can achieve significantly higher EE while enhancing reliability of secondary transmission remarkably compared to non-cooperation single cognitive transmission schemesin high QoS requirement.…”
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Energy-efficient cooperative sensing and transmission in relay-assisted cognitive radio network by Li FENG, Yu-jun KUANG, Bin-wei WU, Xin-chuan FU

“…An innovative EE-oriented cooperative sensing and transmission scheme in relay-assisted cognitive radio networks,called energy-efficient best-relay cooperative transmission (BCT) was proposed.Based on the BCT scheme,mean energy efficiency (MEE) maximization problem with sensing duration and transmitting power as optimization variables was modeled for fading channels under constraint of minimal secondary outage probability.By virtue of Jensen’s inequality,the original optimization problem was decomposed into two relatively independent subproblems which solved sensing duration and power allocation respectively.And for the two subproblems,an efficient cross iteration based algorithm was proposed to obtain the suboptimal solutions.Both analytical and simulation results demonstrate that the proposals can achieve significantly higher EE while enhancing reliability of secondary transmission remarkably compared to non-cooperation single cognitive transmission schemesin high QoS requirement.…”
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Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts by Changhong XU, Shusheng ZHANG, Jiachen LIANG, Rui HUANG, Rong BIAN

“…The PSD-based ant colony algorithm is proposed and described in detail to generate several locally optimal paths. …”
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Design of Nonlinear PID and FOPID Controllers for Electronic Throttle Valve Plate’s Position by Mohamed Jasim Mohamed, Luay Thamir Rasheed

“…However, all these control schemes above have been studied with and without considering the technique of manipulating the windup problem or antiwindup. A metaheuristic optimization technique, namely, the grey wolf optimization (GWO) algorithm, is introduced for optimizing the controllers’ parameters while minimizing the integral of the cube time square error (IT^3SE) cost function. …”
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Research on SeaTreasure Target Detection Technology Based on Improved YOLOv7-Tiny by Xiang Shi, Yunli Zhao, Jinrong Guo, Yan Liu, Yongqi Zhang

“…Experimental results demonstrate that our optimized algorithm achieves a mAP0.5 of 79.5%, representing a 2.0 percentage point improvement over the baseline YOLOv7-tiny model (77.5%) while maintaining computational efficiency at 45.2 GFLOPs. …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…This database captures essential thermal characteristics of the battery module, allowing for accurate temperature predictions without exhaustive simulations. The Gappy POD algorithm is further enhanced by incorporating a correlation coefficient filtering technique, which identifies a minimal set of optimal measurement points to ensure high accuracy in the reconstructed temperature field while reducing sensor requirements. …”
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An online tool based on the Internet of Things and intelligent blockchain technology for data privacy and security in rural and agricultural development by Krishnaprasath Vellimalaipattinam Thiruvenkatasamy, Hayder M. A. Ghanimi, Sudhakar Sengan, Meshal Ghalib Alharbi

“…Central to this model is the proposed Quantum Neural Network + Bayesian Optimization (QNN + BO), a practiced algorithm that, when combined with methods like the Elliptic Curve Cryptography (ECC) and Coyote Optimization Algorithm (COA), guarantees secure data flow, processing, and storage. …”
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An Efficient Fine-Grained Access Control Scheme Based on Policy Protection in SGs by Xiaoqing Guo, Huayi Wu, Zhen Qin, Ruonan Ying, Jilai Yang

“…Security analysis demonstrates that the proposed scheme meets the defined security requirements, while performance evaluation indicates that it incurs minimal computational overhead while achieving enhanced privacy protection.…”
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Task offloading and resource allocation for blockchain‐enabled mobile edge computing by Renbin Fang, Peng Lin, Yize Liu, Yan Liu

“…To manage the allocation of computing resources between task offloading and blockchain consensus, the task offloading and resource allocation are formulated as a joint optimization problem. The aim of the problem is to minimize the energy consumption of UTs while guaranteeing the delay requirement. …”
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Assessing ornamental tree maturity and spray requirements using depth sensing and LiDAR technologies by Aleena Rayamajhi, Guoyu Lu, Ernest William Tollner, Jean Williams-Woodward, Md Sultan Mahmud

“…Effective assessment of tree maturity and agrochemical application requirements is important for optimizing resource use and sustainability in woody ornamental nurseries. …”
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Scalable Hyperspectral Enhancement via Patch-Wise Sparse Residual Learning: Insights from Super-Resolved EnMAP Data by Parth Naik, Rupsa Chakraborty, Sam Thiele, Richard Gloaguen

“…The spectral and spatial characteristics of the scene encoded in the dictionary enable reconstruction through a first-order optimization algorithm to ensure an efficient sparse representation. …”
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Service Function Chain Migration: A Survey by Zhiping Zhang, Changda Wang

“…Traditional optimization algorithms often fall short in large-scale, heterogeneous networks due to limited computational efficiency and scalability. …”
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Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…To address these challenges, we propose a novel multi-aircraft autonomous decision-making approach based on graphs and multi-agent reinforcement learning (MADRL) under zero-order optimization, implemented through the GraphZero-PPO algorithm. …”
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