Machine learning analysis of pharmaceutical cocrystals solubility parameters in enhancing the drug properties for advanced pharmaceutical manufacturing by Tareq Nafea Alharby, Bader Huwaimel

“…Abstract A new computational framework based on machine learning was developed for prediction of Hansen solubility parameters in preparation of pharmaceutical cocrystals with improved properties. The models of Kernel Ridge Regression (KRR), Multi-Linear Regression (MLR), and Orthogonal Matching Pursuit (OMP) were optimized in prediction of three Hansen solubility parameters. …”
Get full text

Prediction of Carbonate Reservoir Porosity Based on CNN-BiLSTM-Transformer by Yingqiang Qi, Shuiliang Luo, Song Tang, Jifu Ruan, Da Gao, Qianqian Liu, Sheng Li

“…Compared with traditional machine learning and deep learning models, the improved model better captures domain-specific information, resulting in an R² increase of 0.23 and reductions in RMSE and MAE by 0.016 and 0.014, respectively. …”
Get full text

Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning by Ali Can Erüst, Fatma Yıldız Taşcıkaraoğlu

“…A recently proposed on‐policy actor–critic method, phasic policy gradient (PPG) which extends the proximal policy optimization algorithm with an auxiliary optimization phase to improve training by distilling features from the critic to the actor network, is used to make EVCS decisions on the network where EV travels through the optimal path from origin node to EVCS by considering dynamic traffic conditions, unit value of EV owner and time‐of‐use charging price. …”
Get full text

UAV-Assisted Unbiased Hierarchical Federated Learning: Performance and Convergence Analysis by Ruslan Zhagypar, Nour Kouzayha, Hesham ElSawy, Hayssam Dahrouj, Tareq Y. Al-Naffouri

“…While applicable to terrestrial base stations (BSs), the proposed algorithm relies on UAVs for local model aggregation thanks to their ability to enhance wireless channels with lower latency and improved coverage. …”
Get full text

Research on Unbalanced Electromagnetic Force Under Static Eccentricity of the Wheel Hub Motor Based on BP Neural Network by Xiangpeng Meng, Yunquan Zhang, Renkai Ding, Wei Liu, Ruochen Wang

“…A BP neural network optimization algorithm can reduce the time of electromagnetic force model simulation for 10 s from 1 h to about 50 s, which greatly improves the calculation efficiency of the electromagnetic force on the basis of ensuring the accuracy of the model, thus providing an unbalanced electromagnetic force model that is more suitable for the dynamic simulation of wheel hub direct-drive electric vehicles, which effectively solves the problem that the traditional electromagnetic force is difficult to couple with the vehicle dynamics model and lays a better foundation for subsequent research on the vertical vibration effect of wheel hub direct-drive electric vehicles.…”
Get full text

An integrated IKOA-CNN-BiGRU-Attention framework with SHAP explainability for high-precision debris flow hazard prediction in the Nujiang river basin, China. by Hao Yang, Tianlong Wang, Nikita Igorevich Fomin, Shuoting Xiao, Liang Liu

“…This study proposes an explainable deep learning framework, the Improved Kepler Optimization Algorithm-Convolutional Neural Network-Bidirectional Gated Recurrent Unit-Attention (IKOA-CNN-BiGRU-Attention) model, for precise debris flow hazard prediction in the Yunnan section of the Nujiang River Basin, China. …”
Get full text

Electric Vehicle Charging Load Forecasting Based on K-Means++-GRU-KSVR by Renxue Shang, Yongjun Ma

“…Then, a combination of kernel support vector regression (KSVR) and gated recurrent unit (GRU) models was used to handle nonlinear features and time-dependent data, where particle swarm optimization (PSO) further optimized the model parameters to improve the forecasting accuracy. …”
Get full text

Research on an Intelligent Prediction Method for the Carbon Emissions of Prefabricated Buildings During the Construction Stage, Based on Modular Quantification by Yang Yang, Xiaodong Cai, Xinlong Ma, Gang Yao, Ting Lei, Hongbo Tan, Ying Wang

“…Based on the machine learning algorithm, a carbon emissions prediction model for prefabricated buildings’ construction stage was established and hyperparameter optimization was conducted. …”
Get full text

Thinning and Weighting of Planar/Conformal Arrays Considering Mutual Coupling Effects by You-Feng Cheng, Wei Shao, Ran Zhang, Xiao Ding, Meng-Xia Yu

“…As an effective optimization algorithm, the differential evolution algorithm (DEA) is adopted in order to achieve low sidelobe. …”
Get full text

Classification and Recognition of Soybean Quality Based on Hyperspectral Imaging and Random Forest Methods by Man Chen, Zhichang Chang, Chengqian Jin, Gong Cheng, Shiguo Wang, Youliang Ni

“…The model parameters were optimized using particle swarm optimization (PSO) and differential evolution (DE) algorithms to improve performance. …”
Get full text

Retracted: Computer Medical Image Segmentation Based on Neural Network by Xiaopeng Wang, Lei Gu, Zhongyi Wang

“…It also introduces pipeline and dual cache structures to optimize memory access, and analyzes the limited resources through the Roofline model. …”
Get full text

Research on Mechanical Properties of Steel Tube Concrete Columns Reinforced with Steel–Basalt Hybrid Fibers Based on Experiment and Machine Learning by Bohao Zhang, Xiao Xu, Wenxiu Hao

“…On the basis of the experiments, a parametric expansion analysis of several structural parameters of the specimen was carried out by using ABAQUS finite element software, and a combined model NRBO-XGBoost, based on the Newton-Raphson optimization algorithm (NRBO), and the advanced machine learning model XGBoost was proposed for the prediction of the BSFCFST’s ultimate carrying capacity. …”
Get full text

Secure beamforming design for IRS-assisted SWIPT Internet of things system by Zhengyu ZHU, Jinlei XU, Gangcan SUN, Ning WANG, Wanming HAO

“…In order to meet the new requirements of intelligent signal processing deployment and physical layer security for green interconnection of things, a design method of secure beamforming was proposed to solve the problem of the shortage of sustainable energy supply in the information and energy transmission at the same time Internet of things (IoT) system assisted by intelligent reflecting surface (IRS).Considering the constraints of secrecy rate, transmit power and IRS reflection phase shift, the optimization problem was modeled as a non-convex quadratic programming problem with quadratic constraints, aiming at maximizing the acquisition power of energy collector, and jointly optimizing the base station transmit beamforming matrix, jammer covariance matrix and IRS phase shift.The non-convex quadratic problem was transformed into an equivalent convex problem by using the relaxation variable, semidefinite relaxation method, auxiliary variable and sequence parameter convex approximation method, and an alternative iterative optimization algorithm was proposed to obtain the feasible solution of the original problem.Simulation results show that the proposed algorithm can converge quickly and improve performance effectively compared with the benchmark scheme.…”
Get full text

Multi-Vehicle Object Recognition Method Based on YOLOv7-W by Xin Liu, Jingbin Zhao, Zhi Zhang, Rongxing Wu, Xun Li

“…Analysis of the XUPEI-CAR experimental dataset reveals significant variations in features across different traffic flow densities. To improve the matching accuracy of prior frames, the k-means++ clustering algorithm is employed to optimize the prior frame parameters. …”
Get full text

Shape Adjustment of a Large Planar Phased Array Antenna With Nonlinear Cable Actuators by Jiyang Zhou, Xiang Liu, Guoping Cai, Jun Sun, Dongfang Zhu

“…Giving a detailed theoretical derivation, this paper demonstrates the necessity of considering nonlinearity of the cable actuator and proposes a nonlinear model of the active cable element. Further, an optimization model is established for shape adjustment, and the genetic algorithm is used to solve this problem. …”
Get full text

Two-Dimensional ISAR Fusion Imaging of Block Structure Targets by Xiaoxiu Zhu, Limin Liu, Baofeng Guo, Wenhua Hu, Lin Shi, Juntao Ma

“…The algorithm further accelerates the iterative convergence speed and improves the imaging efficiency by combining the weighted back-adding residual and condition number optimization of the basis matrix. …”
Get full text

Intra-day dispatch method via deep reinforcement learning based on pre-training and expert knowledge by Yanbo Chen, Qintao Du, Huayu Dong, Tao Huang, Jiahao Ma, Zitao Xu, Zhihao Wang

“…In recent years, due to high self-learning and self-optimization ability, reinforcement learning has emerged in the field of economic dispatch, which can solve model-free dynamic programming problems that cannot be effectively solved by traditional optimization methods. …”
Get full text

Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…This study develops a comprehensive, physics-based quantitative model to accurately evaluate the effectiveness of fracturing stimulation, enabling data-driven optimization of shale gas extraction processes.MethodsThis study established a novel quantitative evaluation model based on principles of fluid mechanics and mathematical optimization theory. …”
Get full text

Capacity Maximization Using Nash Bargaining in Indoor Optical Multiuser Interference-Limited Poisson Channel by Sudhanshu Arya, Yeon Ho Chung

“…With power constraints imposed, the resource allocation problem can be interpreted as a downlink beamforming game. To improve the capacity in a power- and interference-limited channel, we model the problem as a cooperative game and propose an altruistic algorithm using the Nash bargaining, where each self-interested user attempts to maximize its capacity through cooperation. …”
Get full text

Deformation Characteristic Analysis and Engineering Application of a Variable Cross-sectional Flexible Pin by Chen Hengjian, Xiao Shuhong

“…The effectiveness of this method is verified by comparing with the calculation results of the engineering algorithm and the finite element method. The simulation model of the wind power gearbox is established using Romax software, and it is verified that the deformation characteristics of the variable cross-sectional flexible pin can improve the load distribution and load sharing coefficient. …”
Get full text