Machine Learning Approach for Ground-Level Estimation of Electromagnetic Radiation in the Near Field of 5G Base Stations by Oluwole John Famoriji, Thokozani Shongwe

“…Because a machine learning algorithm is trained by utilizing data obtained from numerous 5G base stations, it exhibits the capability to estimate the strength of the electric field effectively at every point of arbitrary radiation, while the base station generates a network and serves various numbers of 5G terminals running in different modes of service. …”
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Adaptive PPO With Multi-Armed Bandit Clipping and Meta-Control for Robust Power Grid Operation Under Adversarial Attacks by Mohamed Massaoudi, Katherine R. Davis

“…This paper proposes a novel composite enhanced proximal policy optimization (CePPO) algorithm to improve power grid operation under adversarial conditions. …”
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Integrated Systemic Modeling of Production Scheduling, Maintenance, and Quality Control in Closed-Loop Supply Chains by Javad Rahim, Ali Morovati Sharifabadi, Davood Andalib Ardakani

“…A Genetic Algorithm (GA) was utilized to optimize decision variables, including sample size, sampling intervals, control limits, and maintenance schedules, ensuring robust solutions under real-world constraints. …”
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Instance-level medical image classification for text-based retrieval in a medical data integration center by Ka Yung Cheng, Markus Lange-Hegermann, Jan-Bernd Hövener, Björn Schreiweis

“…While the outcomes of these experiments are satisfactory (Precision of >75%) for less critical tasks and serve as a valuable testing ground for image retrieval, they also underscore the need for further exploration of potential challenges. …”
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Retracted: Computer Medical Image Segmentation Based on Neural Network by Xiaopeng Wang, Lei Gu, Zhongyi Wang

“…Most of the image segmentation methods in traditional vision algorithms are difficult to achieve high-resolution image segmentation due to the complexity of the algorithm. …”
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Numerical Simulation of Basic Properties of Full-Steel Slag Aggregate Concrete by Zhu Bian, Yuan Fang, Feng Yu, Xuliang Wang, Guosheng Xiang

“…In this study, the bit-level table of orthogonal test is adopted as the coding form of Genetic Algorithm (GA), and a Back Propagation (BP) neural network prediction model of the basic properties of full steel slag aggregate concrete (FSSAC) is established, and the experiment data are validated with good agreement. …”
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Capacity planning for wind, solar, thermal and energy storage in power generation systems considering coupled electricity‐carbon markets by Jiajia Huan, Yuling He, Kai Sun, Hongchang Lu, Haipeng Wang, Xuewei Wu

“…The model employs a bi‐level optimization method based on the Improved Coati Optimization Algorithm (ICOA) to optimize the system's capacity planning. …”
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Spatial transcriptomics and scRNA-seq: decoding tumor complexity and constructing prognostic models in colorectal cancer by Wei Song, Yatao Wang, Min Zhou, Fengqin Guo, Yanliang Liu

“…We developed a 13-gene prognostic signature (PS) using machine learning algorithm (StepCox backward), which predicts the prognosis of CRC patients. …”
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Deep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management by Yusuke Nomura, Ziang Liu, Tatsushi Nishi

“…To solve this problem more efficiently, we also implement a deep reinforcement learning algorithm, proximal policy optimization, to solve this problem. …”
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A Metaheuristic Approach for a Two-dimensional Fuzzy Version of the Variable Size and Cost Bin Packing Problem by Jorge Herrera Franklin, Alejandro Rosete, Guillermo Sosa-Gómez, Omar Rojas

“…We employ mechanisms from the multi-objective metaheuristic approach to maximize the degrees of relaxation while minimizing the original cost function. To demonstrate the efficacy of our proposed solution, we utilized two well-known multi-objective evolutionary P-metaheuristics (Multi-Objective Genetic Algorithm and NSGA-II) and two S-metaheuristics (Multi-Objective Local Search and Ulungu Multi-Objective Simulated Annealing) specifically tailored for the fuzzy version of the VSCBPP. …”
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Adaptive Control Strategy for Automotive Magnetorheological Dampers Based on Artificial Neural Networks by C. Steven Diaz-Choque, Luis C. Felix-Herran, Renato Galluzzi, Riccardo Cespi, Jorge de J. Lozoya-Santos, Ricardo A. Ramirez-Mendoza

“…In vehicle systems, the suspension is fundamental in achieving acceptable levels of ride comfort, while ensuring ride safety. Semi-active suspensions allow changing the suspension damping to prioritize different performance metrics. …”
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Risk Assessment of Constructing Deep Foundation Pits for Metro Stations Based on Fuzzy Evidence Reasoning and Two-tuple Linguistic Analytic Network Process by Jie Jiang, Guangyang Liu, Xi Huang, Xiaoduo Ou

“…Accidents occur frequently while constructing deep foundation pits for metro stations, thereby risking substantial economic losses and casualties. …”
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Enhancing drought prediction through machine learning: advanced techniques combining phenotypic and agrometeorological data by Efrem Yohannes Obsie, Yongguo Liu

“…Two machine learning algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGBoost), were evaluated as predictive models. …”
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Predicting Earthquake Casualties and Emergency Supplies Needs Based on PCA-BO-SVM by Fuyu Wang, Huiying Xu, Huifen Ye, Yan Li, Yibo Wang

“…Subsequently, the optimal hyperparameters for the SVM model are obtained using the Bayesian Optimization algorithm. This approach results in the development of an earthquake casualty prediction model based on PCA-BO-SVM. …”
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Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. The study aims to maximize the technical, financial, and social benefits while ensuring that all security constraints are met. …”
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Study on Resistance Loss of Fly Ash Slurry Multistage High-Pressure Grouting Pipeline Based on Fluent by Qiqing Wang, Linzhe Li, Huijie Wu, Kun Wang, Sixiang Wang

“…The inlet of the model is the velocity inlet, and the outlet is the pressure outlet. The coupled algorithm is chosen as the solution method. Under these conditions, the model converges quickly and the calculation accuracy is high. …”
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Noise Removal in Single-Lead Capacitive ECG With Adaptive Filtering and Singular Value Decomposition by Kaichen Wang, Cathy Tu, Chi Man Qian, Runwei Lin, David Doyle, Yujiro Fujiwara, Junhong Wang

“…The aim of the present study is to explore the feasibility of a cECG system with dedicated denoising algorithms for clinical diagnosis. We conducted real cECG measurements on 12 healthy subjects while simultaneously obtaining traditional wet ECG measurements as references. …”
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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

“…We employed radial basis function (RBF) and multilayer perceptron (MLP) algorithms for ANN modeling. The optimal MLP configuration, utilizing the Levenberg–Marquardt (Trainlm) algorithm, consisted of three hidden layers with 20, 17, and 9 neurons, respectively, while the optimal RBF network contained 43 neurons. …”
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Moving Toward Automated Construction Management: An Automated Construction Worker Efficiency Evaluation System by Chaojun Zhang, Chao Mao, Huan Liu, Yunlong Liao, Jiayi Zhou

“…In the Architecture, Engineering, and Construction (AEC) industry, traditional labor efficiency evaluation methods have limitations, while computer vision technology shows great potential. …”
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Practical DU-CU Placement in an Enhanced Mobile BroadBand Request During 5G Traffic by Ange Joel Nounga Njanda, Joao Filipe Muchanga, Hojjat Baghban, Karcius Day R. Assis

“…To ensure the scalability of the solution for large-scale networks and reduce computation time, we also developed a heuristic algorithm capable of providing solutions close to those obtained by the MILP solver. …”
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