A Microgrid Stability Improvement Method by Applying Virtual Adaptive Resistor Paralleling with a Grid-Connected Inverter by Mingming Shi, Xian Zheng, Juntao Fei, Wenqiang Xie, Jianyu Yu

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A study of dominant factors in the coupled coordination of population–ecology–energy–digital economy in China based on random forest algorithm by Qikang Zhong, Jiawei Zhu, Zhe Li

“…Using panel data from 31 Chinese provinces over the period 2011–2020, we construct a PEED coordination index and analyze its evolution through coupling coordination models, spatial autocorrelation (Moran’s I), the Geodetector model, and a Random Forest algorithm with SHAP analysis. …”
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Driveway Detection for Weed Management in Cassava Plantation Fields in Thailand Using Ground Imagery Datasets and Deep Learning Models by Ithiphat Opasatian, Tofael Ahamed

“…In this context, deep learning algorithms have the potential to train models to detect driveways through furrow image segmentation. …”
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Preoperative Planning Using 3D Printing as a Way to Improve the Outcomes of Surgical Treatment for Pilon Fractures by A. B. Koshkin, M. V. Parshikov, S. V. Novikov, A. A. Prokhorov, A. M. Fai

“…At the same time, in the treatment for comminuted intra-articular pilon fractures, there is no clearly defined operation algorithm: choice of access, reduction and fixation techniques. …”
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DMRG study of the theta-dependent mass spectrum in the 2-flavor Schwinger model by Etsuko Itou, Akira Matsumoto, Yuya Tanizaki

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Research on Pose Error Modeling and Compensation of Posture Adjustment Mechanism Based on WOA-RBF Neural Network by Hongyu Shen, Honggen Zhou, Yiyang Jin, Lei Li, Bo Deng, Jiawei Xu

“…Subsequently, based on the closed-loop vector method, a pose error model for the moving platform is established, which includes eight categories of error terms. …”
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Optimization method of building energy efficiency design based on decomposition multi objective and agent assisted model by Bai Chaoqin, Yang Zhuoyue

“…For the same building type, the average volume measurements of the multi-objective particle swarm optimization algorithm assisted by the decomposed surrogate model are 21153 and 40230, respectively. …”
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Theoretical investigations on analysis and optimization of freeze drying of pharmaceutical powder using machine learning modeling of temperature distribution by Turki Al Hagbani, Jawaher Abdullah Alamoudi, Majed A. Bajaber, Huda Ibrahim Alsayed, Halah Jawad Al-fanhrawi

“…Additionally, the integration of the Fireworks Algorithm for model refinement yields advantages in improving the predictive performance of these models.…”
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Automatic Brain Tumor Segmentation from MRI using Greedy Snake Model and Fuzzy C-Means Optimization by C. Jaspin Jeba Sheela, G. Suganthi

“…A mask is formed by thresholding the reconstructed image and is eroded to improve the accuracy of segmentation in Greedy Snake algorithm. …”
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Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.) by Fazilat Fakhrzad, Warqaa Muhammed ShariffAl-Sheikh, Mohammed M. Mohammed, Heidar Meftahizadeh

“…To identify optimal combinations of genotype and planting date for maximizing morphological traits, the RF model was integrated with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). …”
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Enhancing patient rehabilitation outcomes: artificial intelligence-driven predictive modeling for home discharge in neurological and orthopedic conditions by Leonardo Buscarini, Paola Romano, Elena Sofia Cocco, Carlo Damiani, Sanaz Pournajaf, Marco Franceschini, Francesco Infarinato

“…This process involved variables recoding, scaling, and the evaluation of different dataset balancing methods to optimize model performance. Following a thorough review and comparison of algorithms commonly employed in the clinical-rehabilitative field, the Random Over Sampling (ROS) technique, in combination with the Random Forest (RF) machine learning model, was selected. …”
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An integrated model of threshold-based scaling and fractional admission controlling to improve resource utilization efficiency in 5G core networks. by Ly Cuong Hoa, Thanh Chuong Dang, Viet Minh Nhat Vo

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Wind–Photovoltaic–Hydropower Joint Output Model Study Based on Probability Distribution and Correlation Analysis by Ligui Wu, Benhong Wang, Peng Zhang, Yiming Ke, Fangqing Zhang, Jiang Guo

“…Furthermore, the probability distribution of wind and photovoltaic output is calculated with the maximum likelihood method, and a correlation analysis between wind and photovoltaic output is conducted, where a wind–photovoltaic joint output model is established. Lastly, the k-means clustering algorithm is adopted to process typical scenarios of wind–photovoltaic joint output, and a case study is conducted to validate the wind–photovoltaic–hydropower joint output model. …”
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Integration of multi-temporal SAR data and robust machine learning models for improvement of flood susceptibility assessment in the southwest coast of India by Pankaj Prasad, Sourav Mandal, Sahil Sandeep Naik, Victor Joseph Loveson, Simanku Borah, Priyankar Chandra, Karthik Sudheer

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Quaternion generative adversarial -driven Soc estimation using Tyrannosaurus optimizer for improving hybrid electric vehicles renewably powered energy management by M. Sivaramkrishnan, Jaganathan Subramani, Mohammad Mukhtar Alam, Liew Tze Hui

“…For more accurate SOC estimate, the proposed approach employs a Quaternion Generative Adversarial Network (QGAN) model. When hyper parameter tuning, the prototype is invigorated employing the Tyrannosaurus optimization algorithm (TOA) to fine-tune SOC estimate outcomes of the QGAN model. …”
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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization by Haiying Yang, Feiyang Ren, Jingbo Yin, Siqi Wang, Rafi Ullah Khan

“…This computational study, based on real historical data, verifies the effectiveness of the proposed model and algorithm. The results demonstrate notable improvements in fleet efficiency and environmental performance, increasing profitability by 4.38% while maintaining favorable CII ratings. …”
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An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

“…At the high level, a reinforcement learning strategy based on the actor–critic model is used, combined with the network architecture, to construct a framework for the selection of advanced heuristic algorithms. …”
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Sustainable soil organic carbon prediction using machine learning and the ninja optimization algorithm by Anis Ben Ghorbal, Azedine Grine, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy

“…Recent advances in machine learning (ML) have improved SOC estimation, yet these models often suffer from overfitting and computational inefficiency when effective feature selection and hyperparameter tuning are not applied. …”
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Research on optimal selection of runoff prediction models based on coupled machine learning methods by Xing Wei, Mengen Chen, Yulin Zhou, Jianhua Zou, Libo Ran, Ruibo Shi

“…Employing a “decomposition-reconstruction” strategy combined with robust optimization algorithms enhances the performance of machine learning prediction models, thereby significantly improving the runoff prediction capabilities in watershed hydrological models.…”
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Predictive models for overall health of hydroelectric equipment based on multi-measurement point output by Liu Dong, Kong Lijun, Song Jinghui, Zhou Yiming

“…These algorithms had different advantages and applicable scenarios and could complement each other to improve the precision and robustness of prediction models. …”
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