Vehicle-To-Grid (V2G) Charging and Discharging Strategies of an Integrated Supply–Demand Mechanism and User Behavior: A Recurrent Proximal Policy Optimization Approach by Chao He, Junwen Peng, Wenhui Jiang, Jiacheng Wang, Lijuan Du, Jinkui Zhang

“…This approach enhances system convergence and improves grid stability while maximizing benefits for EV owners. Finally, a simulation platform is used to validate the practical application of the RPPO algorithm in optimizing V2G and grid-to-vehicle (G2V) charging strategies, providing significant theoretical foundations and technical support for the development of smart grids and sustainable transportation systems.…”
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A Novel ANN-PSO Method for Optimizing a Small-Signal Equivalent Model of a Dual-Field-Plate GaN HEMT by Haowen Shen, Wenyong Zhou, Jinye Wang, Hangjiang Jin, Yifan Wu, Junchao Wang, Jun Liu

“…We initially train an ANN model to predict the S-parameters of the device, and subsequently utilize the PSO algorithm for parameter optimization. Comparative analysis with the NSGA2 and DE algorithms, based on convergence speed and accuracy, underscores the superiority of the PSO algorithm. …”
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Deep learning-based semantic segmentation with novel navigation line extraction for autonomous agricultural robots by Chijioke Leonard Nkwocha, Ning Wang

“…The results of the experiments showed that PSPNet achieved the highest mean intersection over union (mIoU) of 96.50%, followed by Deeplabv3+ (96.30%) and ENet (95.13%). While ENet showed more consistent performance across various lighting conditions, the novel algorithm demonstrated remarkable accuracy, reducing angle errors to an average of 1.1°, 1.6°, and 1.6° for ENet, Deeplabv3+, and PSPNet, respectively, compared to 4.6°, 4.9°, and 6.7° using the baseline method. …”
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Spatial dynamics and competitive pricing in charging-as-a-service markets: The quest for cleaner urban development by Guanyu Zhou, Qianyu Dong, Chenyang Feng, Youwei Jia

“…The proposed model is validated using real world data from Shenzhen, and results indicate the efficacy of the equilibrium solving algorithm in reducing computational burden. This study reveals that deregulated competition among CaaS providers, while promoting social welfare, poses risks to long-term sustainability due to regional inequality and market saturation. …”
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An assessment of the long-term change of the Mersin west coastline using digital shoreline analysis system and detection of pattern similarity using fuzzy C-means clustering by Ozcan Zorlu, Lutfiye Kusak

“…A Support Vector Machine (SVM) classification algorithm was applied to distinguish land from water. …”
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EnSCAN: ENsemble Scoring for prioritizing CAusative variaNts across multiplatform GWASs for late-onset alzheimer’s disease by Onur Erdogan, Cem Iyigun, Yeşim Aydın Son

“…Machine learning (ML) algorithms can capture hidden, novel, and significant patterns while considering nonlinear interactions between variants to understand the genetic predisposition for complex genetic disorders. …”
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Automated classification of online reviews of otolaryngologists by Jake G. Stenzel, Nicholas R. Schultz, Michael J. Marino

“…The algorithm was then applied to the entire dataset with comparison of review categorization according to 1‐ and 5‐star reviews. …”
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An energy-balanced multi-sensor scheduling scheme for collaborative target tracking in wireless sensor networks by Pengcheng Fu, Hongying Tang, Yongbo Cheng, Baoqing Li, Hanwang Qian, Xiaobing Yuan

“…This article incorporates this contradiction into a problem of multi-objective optimization in tracking networks where multiple sensor nodes are scheduled for collaborative target tracking by adopting the unscented Kalman filter algorithm. We propose an effective scheme to extend the lifespan of wireless sensor networks while guaranteeing preset tracking quality. …”
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Optimization of D2D emergency communication resources for UAV relay based on DA-STD3 by Xiaofang Deng, Zijian Deng, Lin Zheng, Chao Yang, Chuanxu Chen

“…The feasibility and effectiveness of the algorithm is verified by comparing the baseline algorithm.…”
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An Automatic Generalization Method of a Block-Based Digital Depth Model Based on Surface Curvature Features by Dong Wang, Jian Dong, Lulu Tang, Mengkai Ma, Tian Xie

“…Furthermore, this paper designs validity and comparative experiments to analyze the proposed algorithm through experimental analysis. The results demonstrate that the algorithm can be applied to the multi-scale construction of DDM seabed terrain, while maintaining the integrity of both flat and complex seabed landforms, and significantly enhancing the computational efficiency of the DDM automatic generalization process.…”
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Hybrid Renewable Energy Systems—A Review of Optimization Approaches and Future Challenges by Akvile Giedraityte, Sigitas Rimkevicius, Mantas Marciukaitis, Virginijus Radziukynas, Rimantas Bakas

“…Using comprehensive methodologies, the review examines state-of-the-art algorithms such as Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), alongside Crow Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Levy Flight-Salp Swarm Algorithm (LF-SSA), Mixed-Integer Linear Programming (MILP) and tools like HOMER Pro 3.12–3.16 and MATLAB 9.1–9.13, which have been instrumental in optimizing HRESs. …”
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Research on Fault Diagnosis Method of High-Speed EMU Air Compressor Based on ICEEMDAN and Wavelet Threshold Combined Noise Reduction by Liqiang Peng, Akang Guo, Shuzhao Zhang

“…This approach ensures denoising while preserving the integrity of the original signal. …”
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Analysis and Prediction of Grouting Reinforcement Performance of Broken Rock Considering Joint Morphology Characteristics by Guanglin Liang, Linchong Huang, Chengyong Cao

“…Notably, the Random Forest (RF) algorithm excels in rapid and accurate predictions when handling similar training data, while the ANN-based MCD algorithm consistently delivers stable and precise results across diverse datasets.…”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. …”
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Low cost network traffic measurement and fast recovery via redundant row subspace-based matrix completion by Kai Jin, Kun Xie, Jiazheng Tian, Wei Liang, Jigang Wen

“…Secondly, based on the identified subspace rows, we design our sampling scheduling algorithm, which takes full measurement samples in subspace rows while taking partial measurement samples in the remaining rows. …”
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Optimizing Sampling Points and Path Planning for Soil Monitoring in Agricultural Land by Jing Wang, Zhiqiang Zhai, Guangdong Xu, Ruoyu Zhang, Xin Zhang, Rong Hu

“…Furthermore, the threshold-based hybrid algorithm consistently yields optimal or near-optimal paths while reducing the path planning time, with an average duration of 1.0783 s for path planning. …”
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Replica exchange enhanced adaptively weighted stochastic gradient Langevin dynamics for Bayesian sampling and optimization by Zhenqing Wu, Wenwu Gong, Ziying Yu, Liuxin Zhu, Lili Yang

“…Abstract We propose the replica exchange adaptively weighted stochastic gradient Langevin dynamics (REAWSGLD) algorithm, designed explicitly for Bayesian learning with complex energy landscapes encountered in big data problems. …”
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Intelligent energy optimization for advanced IoT analytics edge computing on wireless sensor networks by Israel Edem Agbehadji, Samuel Ofori Frimpong, Richard C Millham, Simon James Fong, Jason J Jung

“…During the simulation, the dynamic nature of the proposed DEEC-KSA was observed using different parameters, which were expressed in percentages as 0.1%, 4.5%, 11.3%, and 34% while the percentage of the parameter for comparative algorithms was 10%. …”
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Impact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets by Muhammad Khahfi Zuhanda, Lisya Permata, Hartono, Erianto Ongko, Desniarti

“…In this study, we also compared the application of ADASYN and SMOTE on the Naïve Bayes algorithm. The results show that ADASYN outperforms SMOTE across all key metrics—accuracy, precision, recall, and F1-Score—while the accuracy improvements were statistically significant (p-value = 0.00903).…”
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A Continuous Space Path Planning Method for Unmanned Aerial Vehicle Based on Particle Swarm Optimization-Enhanced Deep Q-Network by Le Han, Hui Zhang, Nan An

“…This method divides the agent’s surrounding space into discrete and continuous action spaces. The PSO algorithm performs a global search in the continuous space to obtain a continuous candidate solution, while DQN learns a policy in the discrete space to obtain a discrete candidate solution. …”
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