Application of adaptive virtual synchronous generator based on improved active power loop in photovoltaic storage systems by Youzhuo Zheng, Yutao Xu, Yekui Yang, Long Hua, Yuqing Yang

“…Then, the adaptive inertia algorithm is incorporated into the active power loop of the VSG control, and an adaptive inertia control method based on the improved active power loop is proposed. …”
Get full text

Implementation of personalized customization and enhanced experiences for cultural tourism resources using genetic algorithm-based virtual reality technology by Huiya Xing, Xiangyi Li, Min Liu, Yicong Zhong

“…By adjusting to these individual parameters, the algorithm cleverly optimizes tourist itineraries. The DDE-GA-powered VR system works better than current methods, according to experimental data, with improvements in reaction time (1.1 s), accuracy (98 %), precision (97 %), and modeling error (0.10). …”
Get full text

Diverse solitons wave structures for coupled NLSEs in birefringent fibers with higher nonlinearities using the modified extended mapping algorithm by Karim K. Ahmed, Njah A. Alsahafi, Hamdy M. Ahmed, Salah Boulaaras, M. S. Osman

Get full text

Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…The K-fold cross-validation method with K=10 and hyperparameter tuning were applied to obtain the optimal performance of both models. The results showed that SVM without undersampling achieved 92% accuracy, while with undersampling the accuracy decreased to 76%. …”
Get full text

Flaw-YOLOv5s: A Lightweight Potato Surface Defect Detection Algorithm Based on Multi-Scale Feature Fusion by Haitao Wu, Ranhui Zhu, Hengren Wang, Xiangyou Wang, Jie Huang, Shuwei Liu

“…To elevate detection accuracy as well as shorten the computational load of the model, this paper proposes a lightweight Flaw-YOLOv5s algorithm for potato surface defect detection. …”
Get full text

Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…The preprocessing process includes imputing missing values and normalizing numerical features so that the model can learn optimally. Performance evaluation shows that the use of SMOTE increases classification accuracy from 95% to 97%, as well as improving precision, recall, and F1-score metrics at almost all anxiety levels. …”
Get full text

Adversarial Reinforcement Learning-Based Converged Communication Efficiency Improvement Method for Power Distribution Network by Linyu PENG, Xu LIU, Wei TANG, Qing LIU, Hao FANG, Guanghui ZHANG

Get full text

Multi-Objective Optimization of Insulation Thickness with Respect to On-Site RES Generation in Residential Buildings by Agis M. Papadopoulos, Konstantinos Polychronakis, Elli Kyriaki, Effrosyni Giama

“…This paper investigates the optimization of insulation thickness with respect to the integration of renewable energy systems in residential buildings in order to improve energy efficiency, maximize the contribution of renewables and reduce life cycle costs. …”
Get full text

Cognitive FDA-MIMO Radar Network’s Transmit Element Selection Algorithm for Target Tracking in a Complex Interference Scenario by Yingfei Yan, Haihong Tao, Jingjing Guo, Biao Yang

Get full text

BIT*+TD3 Hybrid Algorithm for Energy-Efficient Path Planning of Unmanned Surface Vehicles in Complex Inland Waterways by Yunze Xie, Yiping Ma, Yiming Cheng, Zhiqian Li, Xiaoyu Liu

“…To address the limitations of traditional path planning algorithms in dynamic environments, the proposed BIT*+TD3 model leverages the BIT* algorithm to generate initial paths in static environments through elliptical informed sampling and heuristic search. …”
Get full text

Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Furthermore, low-level optimization techniques like genetic algorithms as well as particle swarm optimization are used to fine tune the specific model parameters and to reduce the computational overhead for improving the detection efficacy still more. …”
Get full text

Innovative IoT-enabled mask detection system: A hybrid deep learning approach for public health applications by Parul Dubey, Vinay Keswani, Pushkar Dubey, Gunjan Keswani, Dhananjay Bhagat

“…The novelty of the paper lies in combining AFSO with a hybrid deep learning architecture for parameter optimization and improved scalability. Performance metrics such as accuracy, sensitivity, precision, and F1-score were used to evaluate the model. …”
Get full text

Autonomous Maneuver Decision of UCAV Air Combat Based on Double Deep Q Network Algorithm and Stochastic Game Theory by Yuan Cao, Ying-Xin Kou, Zhan-Wu Li, An Xu

“…Then, the double deep Q network (DDQN) algorithm in reinforcement learning (RL) is introduced to train the agent by the interaction with the environment and combined with Minimax algorithm in stochastic game theory to solve the optimal value function in each specific state, and the optimal maneuver decision of UCAV is obtained. …”
Get full text

Reliability evaluation and multi-objective optimization of combustion chamber’s key components of marine engine by Lei Hu, Wentong Wang, Xu Wang, Jianguo Yang, Yonghua Yu, Chunyang Mei

“…Constrained multi-objective optimization of reliability is conducted through contrastive analysis of different optimization algorithms. …”
Get full text

Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci by Jie Lu, Xinhao Lu, Yixiao Wang, Hengdong Zhang, Lei Han, Baoli Zhu, Boshen Wang

“…Compared to conventional LR, the evaluated ML models Generalized Regression Neural Network (GRNN), Probabilistic Neural Network (PNN), Genetic Algorithm-Random Forests (GA-RF) demonstrate superior performance and were considered to be the optimal models for processing large-scale SNP loci dataset. …”
Get full text

Enhancing Port Energy Autonomy Through Hybrid Renewables and Optimized Energy Storage Management by Dimitrios Cholidis, Nikolaos Sifakis, Nikolaos Savvakis, George Tsinarakis, Avraam Kartalidis, George Arampatzis

“…The paper adopts a genetic algorithm (GA)-based optimization framework to assess four energy management scenarios that embed wind turbines (WTs), photovoltaic energy (PV), an energy storage system (ESS), and an energy management system (EMS). …”
Get full text

Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…Significance: Furthermore, the study highlights the potential of AI to transform traditional farming practices, reduce labor-intensive processes, and improve decision-making accuracy. The proposed approach serves as a blueprint for agricultural enterprises aiming to adopt AI technologies while ensuring optimal utilization of human and technological resources. …”
Get full text

Review of Demand Response-based Optimal Scheduling of Electric and Thermal Integrated Energy Systems by Jingshan MO, Guangxian YAN, Na SONG, Mingyang YUAN

“…Artificial intelligence algorithms are primarily divided into methods based on group optimization problems and machine learning algorithms. …”
Get full text

Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…Second, fuzzy clustering, instead of the softmax classification layer, is employed in ResNet for its characteristic of requiring no subsequent data training. The improved model requires only a small amount of sample training to optimize the parameters of the GAP layer, thereby accommodating state diagnosis in scenarios with limited data availability. …”
Get full text

ADMET evaluation in drug discovery: 21. Application and industrial validation of machine learning algorithms for Caco-2 permeability prediction by Dong Wang, Jieyu Jin, Guqin Shi, Jingxiao Bao, Zheng Wang, Shimeng Li, Peichen Pan, Dan Li, Yu Kang, Tingjun Hou

“…We believe that the model developed in this study could represent a reliable tool for assessing Caco-2 permeability during early-stage drug discovery and the chemical transformation rules derived here could provide insights for optimizing Caco-2 permeability. …”
Get full text