MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design by Anoop Raghuvanshi, Abhinav Sharma, Abhishek Kumar Awasthi, Abhishek Sharma, Rahul Singhal, Kim Soon Chong, Sew Sun Tiang, Wei Hong Lim

“…This paper presents the modified arithmetic optimization algorithm (MAOA), a swift and effective optimization algorithm specifically designed for electromagnetic applications. …”
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The Significant Effects of Threshold Selection for Advancing Nitrogen Use Efficiency in Whole Genome of Bread Wheat by Mohammad Bahman Sadeqi, Agim Ballvora, Said Dadshani, Md. Nurealam Siddiqui, Mohammad Kamruzzaman, Ahossi Patrice Koua, Jens Léon

“…By incorporating the neural network algorithm, it is possible to improve the reliability of FDR threshold and increase the probability of identifying true genetic associations while minimizing the risk of false positives in GWAS results.…”
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Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

“…In this study, a new improved meta-heuristic algorithm is proposed for solving the energy building optimization (EBO) and also hybrid energy systems optimization considering uncertainty of conditioned surface area subjected to temperature control for BEO and renewable power and load uncertainties for hybrid system. …”
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A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing by Yacine Bourek, El Mouatez Billah Messini, Chouaib Ammari, Mohamed Guenoune, Boulerbah Chabira, Bipul Krishna Saha

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Improving Forest Above-Ground Biomass Estimation Accuracy Using Multi-Source Remote Sensing and Optimized Least Absolute Shrinkage and Selection Operator Variable Selection Method by Er Wang, Tianbao Huang, Zhi Liu, Lei Bao, Binbing Guo, Zhibo Yu, Zihang Feng, Hongbin Luo, Guanglong Ou

“…The Lasso-GA method results in an ETR model with an R² of 0.73 and an RMSE of 16.70 Mg/ha. Compared to the optimal SGBoost model with the Lasso variable selection method (R² of 0.69, RMSE of 18.63 Mg/ha), the VIF-Lasso method improves R² by 0.06 and reduces RMSE by 2.15 Mg/ha, while the Lasso-GA method improves R² by 0.04 and reduces RMSE by 1.93 Mg/ha. …”
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Better care for children with appendicitis: implementation of antibiotic stewardship optimizes postoperative therapy by Beltz, Sebastian, Fischer, Stephanie, Huenger, Frank, Vahdad, Reza, Kalhoff, Hermann, Leutner, Andreas

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Improving detection of Parkinson’s disease with acoustic feature optimization using particle swarm optimization and machine learning by Elmoundher Hadjaidji, Mohamed Cherif Amara Korba, Khaled Khelil

“…This study aims to refine PD detection systems by introducing customized weighting to acoustic features, adjusting their significance based on their correlation with the disease and the classification algorithm utilized. The particle swarm optimization algorithm is employed for this purpose, with the Oxford PD dataset serving as the source data for training and validation. …”
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Analysis of optimal configuration of energy storage in wind-solar micro-grid based on improved gray wolf optimization by Huang Qian, Huang Dengke, Cai Li, Xu Qingshan

“…Comparing the difference between energy storage without an installation and energy storage with improved algorithm, it is shown that the energy storage configuration of the improved gray wolf optimization improves the economy, efficient energy use, and revenue of the whole system.…”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…In addition, it examines 2,000 random surface soil samples, ranging from 0 to 20 cm, that were optimized using genetic algorithms (GA), particle swarm optimization (PSO), and Optuna. …”
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Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

“…The focus is on maximizing the monitored area while minimizing energy usage. A Scalable coverage-based particle swarm optimization (SCPSO) algorithm integrates a probabilistic coverage model based on Euclidean distance to detect coverage gaps and guide the optimal positioning of nodes, ensuring that each target within the region of interest is covered by at least one sensor. …”
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An innovative coverage optimization method for smart information monitoring in agricultural IoT using the multi-strategy Pelican optimization algorithm by Wei Chen, Qike Cao, Bingyu Cao, Bo Jin

“…Comparative experiments with Improved Artificial Bee Colony Algorithm (IABC), Chaotic Adaptive Firefly Optimization Algorithm (CAFA), Adaptive Particle Swarm Optimization (APSO), and Lévy Flight Strategy Chaotic Snake Optimization Algorithm (LCSO) demonstrate that MSPOA improves network coverage by 5.85%, 11.33%, 21.05%, and 20.66%, respectively. …”
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An Optimization Method for Multi-Robot Automatic Welding Control Based on Particle Swarm Genetic Algorithm by Lu Chen, Jie Tan, Tianci Wu, Zengxin Tan, Guobo Yuan, Yuhao Yang, Chiang Liu, Haoyu Zhou, Weisi Xie, Yue Xiu, Gun Li

“…The results demonstrated that the optimized production line significantly improved efficiency while maintaining safety standards.…”
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Research on Collaborative Optimization Strategy of Railway Signal Nonlinear Control System Based on BBO Algorithm and Multi-objective Optimization by Xue Li, Yixuan Yang, Zheng Li, Hui He

“…Specifically, it sets a population size of 50, a maximum number of iterations of 200, a migration rate dynamically adjusted between 0.6-0.9, and an adaptive mutation rate of 0.01-0.05, using root mean square error and response time as performance evaluation metrics for parameter optimization. Experimental data show that compared to traditional methods, this strategy can increase the average operating speed of trains by 15%, reduce signal delays by 20%, and improve system robustness indicators by 18.5%, achieving a collaborative enhancement of efficiency and safety while ensuring stable operation, thus providing an engineering-valued solution for the intelligent upgrade of railway transport.…”
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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…Besides, we propose an improved equilibrium optimizer (EO) approach whereby the previous EO is modified. …”
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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
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Leveraging AI to Drive Timely Improvements in Patient Experience Feedback: Algorithm Validation by Mustafa Khanbhai, Catalina Carenzo, Sarindi Aryasinghe, David Manton, Erik Mayer

“…Technical infrastructure, including coding environments and packages for algorithm testing and deployment, was optimized. The algorithm was iteratively trained using bag of words from anonymized data, tailored to accommodate contextual variations, and tested for change in algorithm performance while simultaneously rectifying issues identified. …”
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Resource Allocation Algorithm for the Downlink of Multi-User OFDM System with Optimized Fairness by Limei Tang, Haiyan Cao, Jun Li, Shiyi Xie

“…Simulation results show that the proposed algorithm improves the capacity of the system while ensuring the performance of fairness better compared with the algorithm in[10]. …”
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Resource Allocation Algorithm for the Downlink of Multi-User OFDM System with Optimized Fairness by Limei Tang, Haiyan Cao, Jun Li, Shiyi Xie

“…Simulation results show that the proposed algorithm improves the capacity of the system while ensuring the performance of fairness better compared with the algorithm in[10]. …”
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Research on Wellbore Trajectory Optimization and Drilling Control Based on the TD3 Algorithm by Haipeng Gu, Yang Wu, Xiaowei Li, Zhaokai Hou

“…After reinforcement learning training, the trajectory offset is significantly reduced, and the accuracy is greatly improved. This research shows that the TD3 algorithm is superior to the multi-objective optimization algorithm in optimizing key parameters, such as well deviation, kickoff point (KOP), and trajectory length, especially in well deviation and KOP optimization. …”
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Deep learning algorithm on H&E whole slide images to characterize TP53 alterations frequency and spatial distribution in breast cancer by Chiara Frascarelli, Konstantinos Venetis, Antonio Marra, Eltjona Mane, Mariia Ivanova, Giulia Cursano, Francesca Maria Porta, Alberto Concardi, Arnaud Gerard Michel Ceol, Annarosa Farina, Carmen Criscitiello, Giuseppe Curigliano, Elena Guerini-Rocco, Nicola Fusco

“…This proof-of-concept study employed a deep learning (DL) algorithm to predict TP53 mutational status from H&E-stained whole slide images (WSIs) of BC tissue. …”
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