The vessel movement optimisation with excessive control by С. Зинченко, А. Бень, П. Носов, И. Попович, В. Матейчук, О. Грошева

Get full text

Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…The article discusses various approaches, including supervised learning, regression models, and Q-learning algorithms, highlighting their ability to reduce design time, improving system efficiency, and mitigate risks associated with misalignment and object interference. …”
Get full text

A Global Coverage Path Planning Method for Multi-UAV Maritime Surveillance in Complex Obstacle Environments by Yiyuan Li, Weiyi Chen, Bing Fu, Zhonghong Wu, Lingjun Hao

“…Secondly, a method for calculating obstacle-avoidance path costs based on the Voronoi diagram is proposed, laying the foundation for obtaining the optimal access order. Thirdly, an improved discrete grey wolf optimizer (IDGWO) algorithm integrated with variable neighborhood search (VNS) operations is proposed to perform task assignment for multiple UAVs and achieve workload balancing. …”
Get full text

A typical scenario generation method for renewable energy power systems based on time-sequenced operational simulations by PENG Zhuyi, SONG Shan, XU Sixuan, GU Kanghui, GE Yi, WANG Quanquan, SUN Wentao

“…Firstly， a unit combination model that incorporates AC power flow constraints is constructed， and a two-stage solution strategy based on second-order cone relaxation is adopted to perform 8，760-hour time-sequenced simulations in the multi-period optimal power flow model. …”
Get full text

Pig Aggression Tracking and Analysis Application Based on A RPMeMOTR Method by Shuqin Tu, Haoxuan Ou, Aqing Yang, Yun Liang, Jiaying Du, Yuefei Cao, Ruilin He, Fang Yuan

“…To address the above challenges, this study proposes an RPMeMOTR approach by combining the RKNet model and the P-ids algorithm based on MeMOTR for pig aggression tracking and analysis. …”
Get full text

An Integrated Electricity–Gas–Heat Energy System Based on the Synergy of Long- and Short-Term Energy Storage by Min Zhang, Jinhao Wang, Huiqiang Zhi, Jun Zhao, Xiao Chang, Shifeng Zhang, Xiangyu Guo, Tengxin Wang

“…Therefore, this paper proposes an integrated energy system planning and optimization method based on hybrid energy storage. Firstly, an adaptive noise integration empirical modal decomposition method based on the optimization improvement of the grey wolf algorithm is designed for the power allocation strategy of the hybrid energy storage system; secondly, for the electric–gas system, an energy management strategy for the hybrid electric–gas energy storage system, taking into account the operating characteristics of the alkaline electrolyzer, is proposed in order to strengthen the complementary mechanism between electric energy storage and gas energy storage. …”
Get full text

Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…A combined model was further constructed by integrating both feature sets, and model performance was compared to identify the optimal predictive model.Results‍　‍This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model. …”
Get full text

Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…This study integrated hyperspectral technology with machine learning algorithms to model complex nonlinear relationships and to select the optimal SWHC model. …”
Get full text

Revolutionize 3D-Chip Design With Open3DFlow, an Open-Source AI-Enhanced Solution by Yifei Zhu, Zhenxuan Luan, Dawei Feng, Weiwei Chen, Lei Ren, Zhangxi Tan

“…<italic>Open3DFlow</italic>&#x2019;s open-source nature allows seamless integration of custom AI optimization algorithms. As a showcase, we leverage large language models (LLMs) to help the bonding pad placement. …”
Get full text

Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…These models were trained based on different datasets, and their hyper-parameters were optimized using algorithms such as grid search, Bayesian optimization, and K-fold cross-validation. …”

Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Given the instability and high volatility of wind power generation, this study proposes a short-term wind power prediction method based on BWO‒VMD and TCN‒BiGRU to improve the accuracy of wind power prediction and better support the energy transition under the “dual carbon” strategy.MethodsA short-term wind power generation prediction model based on the beluga whale optimization (BWO) algorithm, variational mode de-composition (VMD), temporal convolutional network (TCN), and bidirectional gated recurrent unit (BiGRU) was carefully proposed to improve the prediction accuracy of wind power generation, particularly considering its inherent instability and high volatility. …”
Get full text

Robust Framework for PMU Placement and Voltage Estimation of Power Distribution Network by Nida Khanam, Mohd. Rihan, Salman Hameed

“…The suggested method uses a hybrid Multi-Objective Particle Swarm Optimization and Differential Evolution (MOPSO-DE) algorithm to find the best PMU positions and the Weighted Least Squares (WLS) method to estimate voltage magnitude. …”
Get full text

Using machine learning techniques to evaluate the impact of future climate change on wheat yields in Xinjiang, China by Xuehui Gao, Jian Liu, Haixia Lin, Tehseen Javed, Feihu Yin, Rui Chen, Yue Wen, Jinzhu Zhang, Kefan Yi, Zhenhua Wang

“…Additionally, the impacts of climate change scenarios on wheat yield were predicted using two emission scenarios (SSP45 and SSP85) from global climate models (GCMs) and machine learning (ML) algorithms. …”
Get full text

Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China: a longitudinal st... by Gege Zhang, Sijie Dong, Li Wang

“…LASSO regression was used to screen for risk factors, and three machine learning algorithms—logistic regression (LR), random forest (RF), and XGBoost—were employed to build predictive models. …”
Get full text

Intelligent Path Tracking for Single-Track Agricultural Machinery Based on Variable Universe Fuzzy Control and PSO-SVR Steering Compensation by Huanyu Liu, Zhihang Han, Junwei Bao, Jiahao Luo, Hao Yu, Shuang Wang, Xiangnan Liu

“…Additionally, a heading deviation prediction model based on Support Vector Regression (SVR) optimized by Particle Swarm Optimization (PSO) is introduced, and a steering angle compensation controller is designed to improve the turning accuracy. …”
Get full text

Investigation of Hysteresis Phenomena and Compensation in Piezoelectric Stacks for Active Rotor by Xiancheng Gu, Weidong Yang, Linghua Dong, Jinlong Zhou

“…Subsequently, the Bouc–Wen model is adopted to establish the hysteresis model of the piezoelectric actuator, with its parameters identified through the particle swarm optimization (PSO) algorithm. …”
Get full text

The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…During the model training phase, gradient descent is used to optimize weight parameters, and quantum algorithms are integrated to continuously adjust network weights to minimize prediction errors. …”
Get full text

Construction of a Prediction Model for Sleep Quality in Embryo Repeated Implantation Failure Patients Undergoing Assisted Reproductive Technology Based on Machine Learning: A Singl... by Zhao Y, Xu C, Qin N, Bai L, Wang X, Wang K

“…Yanjun Zhao,1,&amp;ast; Chenying Xu,1,&amp;ast; Ningxin Qin,2,&amp;ast; Lina Bai,1 Xuelu Wang,1 Ke Wang2 1Operating Room, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, People’s Republic of China; 2Reproductive Medicine Center, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, People’s Republic of China&amp;ast;These authors contributed equally to this workCorrespondence: Xuelu Wang, Email wangxuelu@51mch.com Ke Wang, Email wangkeyfy@126.comObjective: Constructing a predictive model for sleep quality in embryo Repeated Implantation Failure(RIF) patients using multiple machine learning algorithms, verifying its performance, and selecting the optimal model.Methods: Retrospective collection of clinical data from RIF patients who underwent assisted reproductive technology at the Reproductive Medicine Center of Tongji University Affiliated Obstetrics and Gynecology Hospital from January 2022 to June 2022, divided into a training set and a validation set in an 8:2 ratio. …”
Get full text

Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students by Yagyanath Rimal, Yagyanath Rimal, Navneet Sharma

“…The grid search for random forest algorithms achieved a score of 79% when optimally tuned; however, the training accuracy was 99%. …”
Get full text

Application of Fuzzy Logic Sliding Mode Control Approach With PID Structure for Electro-Hydraulic Actuator Tracking System by Muhamad Fadli Ghani, Ahmad Athif Mohd Faudzi, Rozaimi Ghazali, Shahrol Mohamaddan

“…The proposed control strategy was designed with the switching function modification based on an FL approach in the conventional SMC algorithm. Due to the difficulty of concurrent hybrid design, a particle swarm optimization (PSO) algorithm was employed to determine the optimal control variables value. …”
Get full text