An Improved Crop Disease Identification Method Based on Lightweight Convolutional Neural Network by Tingzhong Wang, Honghao Xu, Yudong Hai, Yutian Cui, Ziyuan Chen

“…In order to improve the training learning rate, Adam optimizer combining momentum algorithm and RMSprop algorithm is used to dynamically adjust the learning rate; the combination of the two algorithms makes the loss function converge to the lowest point faster. …”
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Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM by Hongqiao Huang, Wen Ye, Li Liu, Wenjing Wang, Yan Wang, Huiliang Cao

“…This study proposes a novel parallel denoising and temperature compensation fusion algorithm for MEMS ring gyroscopes. First, the particle swarm optimization (PSO) algorithm is used to optimize the time-varying filter-based empirical mode decomposition (TVFEMD), obtaining optimal decomposition parameters. …”
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Improving energy efficiency and network performance in IaaS cloud with virtual machine placement by Jian-kang DONG, Hong-bo WANG, Yang-yang LI, Shi-duan CHENG

“…The existing virtual machine(VM) placement schemes mostly reduce energy consumption by optimizing utilization of physical server or network element.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,a VM placement scheme was proposed to achieve two objectives.One is to minimize the number of activating physical machines and network elements to reduce the energy consumption,and the other is to minimize the maximum link utilization to improve the network performance.This scheme is able to reduce the energy consumption caused by physical servers and network equipment while optimizing the network performance,making a trade off between energy efficiency and network performance.A novel two-stage heuristic algorithm for a solution was designed.Firstly,the hierarchical clustering algorithm based on minimum cut and best fit algorithm was used to optimize energy efficiency,and then,local search algorithm was used to minimize the maximum link utilization.The simulations show that this solution achieves good results.…”
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Data-driven framework for prediction of mechanical properties of waste glass aggregates concrete by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Hamza Imran, Miguel Angel Duque Vaca, Greys Carolina Herrera Morales, Nestor Ulloa, Krishna Prakash Arunachalam

“…Abstract This research presents a novel data-driven framework for predicting the mechanical properties of waste glass aggregate concrete using six advanced metaheuristic optimization algorithms: Bat Algorithm (Bat), Cuckoo Search Algorithm (Cuckoo), Elephant Herding Optimization (Elephant), Firefly Algorithm (Firefly), Rhinoceros Optimization Algorithm (Rhino), and Gray Wolf Optimizer (Wolf). …”
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Structural knowledge-driven meta-learning for task offloading in vehicular networks with integrated communications, sensing and computing by Ruijin Sun, Yao Wen, Nan Cheng, Wei Wang, Rong Chai, Yilong Hui

“…Although this non-convex problem can be handled by the alternating minimization (AM) algorithm that alternatively minimizes the divided four sub-problems, it leads to high computational complexity and local optimal solution. …”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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Faster quantum subroutine for matrix chain multiplication via Chebyshev approximation by Xinying Li, Pei-Lin Zheng, Chengkang Pan, Fei Wang, Chunfeng Cui, Xian Lu

“…The algorithm can be applied to any complex matrix. Furthermore, we discuss integrating our QMM algorithm as a subroutine in other matrix operations and propose strategies to optimize QMM for matrices with large condition numbers with numerical simulation.…”
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Adaptive Multi-Robot Exploration for Unknown Environments Using Edge-Weighted Path Planning by Farhad Baghyari, Tyler Parsons, Jaho Seo, Byeongjin Kim, Mingeuk Kim, Hanmin Lee

“…Experimental results demonstrate that the algorithm achieves improved exploration efficiency and adaptability compared to a real-time scheduling method while maintaining computational feasibility. …”
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Microgrid system for electric vehicle charging stations integrated with renewable energy sources using a hybrid DOA–SBNN approach by Kommoju Naga Durga Veera Sai Eswar, M. Arun Noyal Doss, Mohammad Shorfuzzaman, Ali Elrashidi

“…The manuscript introduces a hybrid technique for efficient electric vehicle (EV) charging integrating the Dollmaker Optimization algorithm (DOA) and spatial Bayesian neural network (SBNN). …”
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Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks by Shakil Ahmed, Mostafa Zaman Chowdhury, Saifur Rahman Sabuj, Md Imtiajul Alam, Yeong Min Jang

“…We derive EE UAV relay-user maximization problem in the adversarial wireless networks at last. While the problem is non-convex, we propose an iterative and sub-optimal algorithm to optimize EE UAV relay with constraints, such as ICC, trajectory, speed, acceleration, and transmit power. …”
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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods by Zhehao Huang, Benhuan Nie, Yuqiao Lan, Changhong Zhang

“…Empirical evidence demonstrates that this framework not only accurately captures the diverse characteristics of different data components but also significantly outperforms traditional benchmark models in predictive accuracy. By optimizing the GRU model with the grey wolf optimizer (GWO) algorithm, the framework enhances both prediction stability and adaptability, while the nonlinear integration approach effectively mitigates error accumulation. …”
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Multi-Armed Bandit Approaches for Location Planning with Dynamic Relief Supplies Allocation Under Disaster Uncertainty by Jun Liang, Zongjia Zhang, Yanpeng Zhi

“…We introduce a multi-armed bandit algorithm, named the Geometric Greedy algorithm, to optimize transfer station planning while accounting for subsequent dynamic relief supply distribution and allocation in a stochastic environment. …”
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Energy Efficiency Maximization for Device-to-Device Communication Underlaying Cellular Networks on Multiple Bands by Yuan Zhang, Yang Yang, Linglong Dai

“…Finally, simulation results demonstrate that the proposed algorithm can achieve the near-optimal EE with much better performance than the conventional algorithm.…”
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Mixed Balanced Truncation for Reducing the Complexity of Large-Scale Electrical and Electronic System Simulations by Huy-Du Dao, Thanh-Tung Nguyen, Ngoc-Kien Vu, Van-Ta Hoang, Hong-Quang Nguyen

“…This paper proposes the Mixed Balanced Truncation (MBT) algorithm, which combines the strengths of Balanced Truncation (BT) and Positive-Real Balanced Truncation (PRBT) while addressing their respective limitations. …”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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Auxiliary Stopping Area Layout Method for High-Speed Maglev considering Multiple Speed Profiles and Bidirectional Operation by Danyang Dong, Yi Yu, Huahua Zhao, Pengzi Chu, Hui Lin

“…Aiming at the layout of the ASA along the track, this article constructs an optimized model of ASA layout and proposes a solving algorithm based on the single target genetic algorithm by analyzing the influence factors of ASA layout. …”
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A global object-oriented dynamic network for low-altitude remote sensing object detection by Daoze Tang, Shuyun Tang, Yalin Wang, Shaoyun Guan, Yining Jin

“…This study introduces the Global Object-Oriented Dynamic Network (GOOD-Net) algorithm, comprising three fundamental components: an object-oriented, dynamically adaptive backbone network; a neck network designed to optimize the utilization of global information; and a task-specific processing head augmented for detailed feature refinement. …”
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Design of precoding matrices in MIMO full duplex two-way security communication system by Weijia LEI, Yang ZHOU, Xianzhong XIE, Hongjiang LEI

“…The design of precoding matrices was studied in the multiple input multiple output (MIMO) full-duplex two-way security communication system where legitimate nodes transmit the confidential information accompanied by the artificial noise while receiving information.For the scenario where the perfect channel state information (CSI) of legitimate channels and eavesdropping channels was available,the difference of concave/convex (DC) programming was used to optimize the precoding matrices of the information signal and the artificial noise for the maximization of the secrecy sum rate.For the scenario where the CSI was imperfect,the channels were modeled by using worst-case criterion and the weighted minimum mean square error algorithm was used to get the robust precoding matrices of the information signal and the artificial noise.The simulation results prove that the proposed algorithm can effectively promote the secrecy sum rate of the system.…”
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Key Nodes Identification Method in Scale-Free Network Based on Structural Holes by Weiyan Liu

“…The proposed algorithm achieves higher accuracy in structural hole-aware ranking compared to benchmarks while maintaining <inline-formula> <tex-math notation="LaTeX">${ O}\left ({{ m+n.logn }}\right)$ </tex-math></inline-formula> complexity. …”
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Gaussian Process Regression with Soft Equality Constraints by Didem Kochan, Xiu Yang

“…Additionally, we introduce an adaptive learning algorithm to optimize the selection of constraint locations to further enhance the flexibility of the method. …”
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