Computational design exploration of rocket nozzle using deep reinforcement learning by Aagashram Neelakandan, Arockia Selvakumar Arockia Doss, Natrayan Lakshmaiya

“…Additionally, the use of the Single-Step Proximal Policy Optimization (SSPPO) algorithm enhances the exploration of nozzle geometries by maximizing aerodynamic performance while balancing computational efficiency. …”
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Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…The effectiveness of ML applications in this domain, however, is highly dependent on the selection of quality datasets, relevant features, and suitable algorithms. Advanced techniques such as active learning are being explored to enhance ANN model performance by improving the models’ responsiveness to diverse and nuanced battery behavior. …”
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Enhancing 4G/LTE Network Path Loss Prediction with PSO-GWO Hybrid Approach by Messaoud Garah, Nabil Boukhennoufa

“…Furthermore, a hybrid optimization model, PSO-GWO, is proposed to improve prediction accuracy. …”
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Design and Implementation of Local Threshold Segmentation Based on FPGA by Shangshang Gao, Yuanyuan Wang, Zhaofeng Chen, Feng Zhou, Rugang Wang, Naihong Guo

“…Finally, the design algorithm is verified by ModelSim simulation software and QT5 software. …”
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Dispatching strategy of shared bicycles for morning peak tidal travel based on spatial distribution by Xiangyu Lei, Jiaqi Yang

“…The study identifies the spatial distribution characteristics of the tidal phenomenon by analyzing the riding order and electronic fence data and combining them with the KD-Tree algorithm; subsequently, a demand prediction model based on the XGBoost algorithm and a hierarchical scheduling model based on the greedy algorithm are constructed to dynamically optimize the spatial distribution of the bicycle resources with the demand fluctuation as the guide. …”
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Unmet needs in the clinical management of chronic hepatitis B infection by Peter D. Block, Joseph K. Lim

“…This includes efforts to optimize delivery of perinatal HBV care, improve HBV-related hepatocellular carcinoma risk stratification models, and clarify the role of finite therapy in the HBV treatment algorithm. …”
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ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…The algorithm innovatively designs three core modules: the AdaptiveVision Network (AVN) backbone for enhanced feature extraction, the Dual-Domain Enhanced Transformer (DDET) module for spatiotemporal-frequency domain collaboration, and the Adaptive Multi-scale Feature Model (AMFM) for improved feature fusion. …”
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Communication between nodes in backscatter-assisted wireless powered communication network by Jie TAO, Haijiang GE, Minyuan WU, Qike SHAO, Kaikai CHI

“…At present, there is almost no design on information transmission between the nodes in wireless powered communication network.The high-throughput information transmission between the nodes in backscatter assisted wireless powered communication network was studied.A scheme was proposed which consisted of backscattering/energy transmission phase and active communication phase.The maximum throughput was modeled as a convex optimization problem.Then, based on the relationship between the total backscatter communication duration and the threshold of node energy capture duration, the problem was decomposed into several sub problems that only need to optimize two backscatter durations.An efficient two-level golden section search algorithm was designed to solve the sub problems, and the optimal solution of the original problem was obtained from the optimal solutions of the sub problems.Simulation results show that, compared with pure active communication scheme and pure backscatter communication scheme, the proposed scheme can effectively improve the throughput.…”
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Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME by Md. Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Arnisha Akhter, Md Ashraf Uddin, Khandaker Mohammad Mohi Uddin

“…To tackle the challenge of designing an improved diabetes classification algorithm that is more accurate, random oversampling and hyper‐tuning parameter techniques have been used in this study. …”
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Predicting the Activity Level of the Great Gerbil (Rhombomys opimus) via Machine Learning by Fan Jiang, Peng Peng, Zhenting Xu, Yu Xu, Ding Yang, Shouquan Chai, Shuai Yuan, Limin Hua, Dawei Wang, Xuanye Wen

“…Because traditional assessment methods are difficult to monitor and cannot effectively predict the population growth trend of R. opimus, an R. opimus activity prediction model was constructed using the particle swarm optimization algorithm‐extreme learning machine (PSO‐ELM). …”
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A Minimal Path-Based Method for Computing Multistate Network Reliability by Xiu-Zhen Xu, Yi-Feng Niu, Can He

“…To advance the solution efficiency of d-MPs, an improved model is developed by redefining capacity constraints of network components and minimal paths (MPs). …”
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Berth Allocation and Quay Crane Assignment Considering the Uncertain Maintenance Requirements by Siwei Li, Liying Song

“…To address this novel problem, we propose a proactive-reactive method that incorporates a reliability-based model into the Swarm Optimization with Differential Evolution (SWO-DE) algorithm. …”
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Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System by Hossein Jokar, Taher Niknam, Moslem Dehghani, Pierluigi Siano, Khmaies Ouahada, Mokhtar Aly

“…Simulation results under various scenarios demonstrate the model’s superior performance. Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. …”
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Support vector neural network based fuzzy hybrid filter for impulse noise identification and removal from gray-scale image by Sagenela Vijaya Kumar, C. Nagaraju

“…The SVNN classifier is trained based on the Genetic Algorithm (GA) for identifying the optimal weights and the bias. …”
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Hunting Stability Enhancement of a Train Bogie Employing Inerter-Based Suspension Mechanism by Yong Wang, Chenyang Hong, Haodong Meng

“…The structural parameter analysis of inerter-based suspension mechanism is conducted, and the structural parameters are optimized using the nondominated sorting whale optimization algorithm (NSWOA). …”
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Protein docking by the underestimation of free energy funnels in the space of encounter complexes. by Yang Shen, Ioannis Ch Paschalidis, Pirooz Vakili, Sandor Vajda

“…This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. …”
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YOLOX-LS: Strong Gravitational Lenses Detection in the DECaLS with Deep Learning by Yangyang Liu, Liangping Tu, Jianxi Li, Jiawei Miao, Gengqi Lin, Chenying Zhao

“…In this paper, we construct a data set for strong gravitational lensing searches that consist of known lenses and lens candidates from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys (the DESI Legacy Imaging Surveys) and the Dark Energy Survey (DES) and non-lenses from the Legacy Surveys Data Release 9 (DR9). We apply the YOLOX algorithm as the basic framework and improve it by selecting the optimal optimizer, activation function, attention mechanism, and loss function. …”
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Discrete Phase Shift IRS-Assisted Energy Harvesting in Cognitive Radio Networks With Spectrum Sensing by Lilian Chiru Kawala, Guoquan Li, Mihertie Habtamu Demeke, Junzhou Xiong, Hao Xiong, Hang Hu

“…Simulation results demonstrate the superior performance of the proposed framework and the novel resource allocation algorithm based on alternating optimization. These results highlight the transformative potential of IRS with discrete phase shifts in enhancing EH-CRN efficiency, particularly in improving energy harvesting and SU throughput under practical constraints.…”
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Composing problem solvers for simulation experimentation: a case study on steady state estimation. by Stefan Leye, Roland Ewald, Adelinde M Uhrmacher

“…To support those users, we propose a general scheme to aggregate such algorithms to so-called synthetic problem solvers, which exploit algorithm differences to improve overall performance. …”
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SR-YOLO: Spatial-to-Depth Enhanced Multi-Scale Attention Network for Small Target Detection in UAV Aerial Imagery by Shasha Zhao, He Chen, Di Zhang, Yiyao Tao, Xiangnan Feng, Dengyin Zhang

“…Second, a small target detection layer and a bidirectional feature pyramid network mechanism are introduced to enhance the neck network, thereby strengthening the feature extraction and fusion capabilities for small targets. Finally, the model’s detection performance for small targets is improved by utilizing the Normalized Wasserstein Distance loss function to optimize the Complete Intersection over Union loss function. …”
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