基于改进Kriging模型的主动学习可靠性分析方法 by 陈哲, 杨旭锋, 程鑫

“…,the differential evolution algorithm is introduced to explore the optimal parameter of Kriging model and improve the accuracy of Kriging prediction information.As a result,the training point in each iteration is guaranteed to be the global optimal one and the efficiency of ALK model is largely improved.…”
Get full text

Maximum Power Exploitation of Photovoltaic System under Fast-Varying Solar Irradiation and Local Shading by Yi-Jui Chiu, Bi Li, Chin-Ling Chen, Shui-Yang Lien, Ding Chen, Ji-Ming Yi, Yung-Hui Shih

“…In addition, under fast-varying solar irradiation and local shading, the speed, ability, and stability of the improved MPPT system with the PF-MPPT algorithm when tracking the maximum power were 9.52, 1.32, and 1.84 times of the MPPT system with the P&O algorithm and 2.18, 1.41, and 2.00 times of the MPPT system with the particle swarm optimization algorithm, respectively.…”
Get full text

A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…Finally,the improved dung beetle optimization (IDBO) algorithm is used to optimize the hyper-parameters of the model. …”
Get full text

Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

“…In order to further optimize the performance of the LSTM model, the IPSO algorithm, and linear difference decreasing inertia weight are introduced to improve the global optimization ability and convergence speed of the PSO algorithm and reduce the risk of local optimal solutions. …”
Get full text

A novel hybrid model for predicting the bearing capacity of piles by Li Tao, Xinhua Xue

“…The improved PSO algorithm was used to optimize the LSSVM hyperparameters. …”
Get full text

SIC-Free Based Indoor Two-User NOMA-VLCP System by Jianli Jin, Qianlong Shang, Jianping Wang, Huimin Lu, Danyang Chen, Dongmei Yang

“…The particle swarm optimization (PSO) algorithm is employed to construct a joint optimization function that optimizes the power allocation factor of the two users and the roll-off coefficient of the square-root-raised-cosine(SRRC) filter. …”
Get full text

Iterative phase contrast CT reconstruction with novel tomographic operator and data-driven prior. by Stefano van Gogh, Subhadip Mukherjee, Jinqiu Xu, Zhentian Wang, Michał Rawlik, Zsuzsanna Varga, Rima Alaifari, Carola-Bibiane Schönlieb, Marco Stampanoni

“…Breast cancer remains the most prevalent malignancy in women in many countries around the world, thus calling for better imaging technologies to improve screening and diagnosis. …”
Get full text

Intelligent library shelf management system for open-access environments: A CNN-based approach with enhanced image recognition and disorder detection by Xueqi Zhang

“…Experimental results demonstrated that the improved algorithm exhibited superior performance to convolutional neural networks and support vector machine algorithms. …”
Get full text

Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…Furthermore, Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Marine Predators Algorithm (MPA), and Whale Optimization Algorithm (WOA) are introduced to optimize the SVR model, and the prediction performance is compared with that of the Long Short-Term Memory (LSTM) model. …”
Get full text

Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network by Tianpeng Zhang, Pengfei Ji, Dayong Tian, Rui Xu

“…The Fenton oxidation process is used to treat kitchen anaerobic wastewater, and the effects of H2O2 dosage, Fe2+ dosage, reaction time and pH value on chemical oxygen demand (COD) degradation efficiency are explored. The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO-BP neural network. …”
Get full text

Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position er... by Ruirui Liu, Ding Wang, Jiexin Yin, Ying Wu

“…Based on measurements of angle of arrival and time difference of arrival, a method is proposed to improve the accuracy of localization with imperfect sensors. …”
Get full text

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

“…Each model’s performance was assessed via measuring Root Mean Square Error (RMSE), R2, Mean Absolute Error (MAE), and Monte Carlo Cross-Validation (CV) scores using a Tabu Search method for optimization. …”
Get full text

Orchard Navigation Method Based on RS-SC Loop Frame Search Method and SLAM Technology by Ning Xu, Qingshan Meng, Fengping Liu, Zhihe Li, Guangming Wang, Na Guo, Wenxuan Wu

“…In the loop frame matching, an optimization algorithm combining normal distribution transformation and iterative nearest point is used to reduce the cumulative error significantly. …”
Get full text

Broad learning system based on attention mechanism and tracking differentiator by LIAO Lüchao, ZOU Weidong, YANG Jialong, LU Huihuang, XIA Yuanqing, GAO Jianlei

“…In terms of model structure, A-TD-BLS introduced self-attention mechanism to the original BLS, and further fused and transformed the extracted features through attention weighting to improve the feature learning ability.In terms of model training methods, a weight optimization algorithm based on tracking differentiator was designed.This method effectively alleviates the overfitting phenomenon of the original BLS by limiting the size of the weight values, significantly reduces the influence of the number of hidden layer nodes on model performance and makes the generalization performance more stable.Moreover, the training algorithm was extended to the BLS incremental learning framework, so that the model can improve performance by dynamically adding hidden layer nodes.Multiple experiments conducted on some benchmark datasets show that compared to the original BLS, the classification accuracy of A-TD-BLS is increased by 1.27% on average on classification datasets and the root mean square error of A-TD-BLS is reduced by 0.53 on average on regression datasets.Besides, A-TD-BLS is less affected by the number of hidden layer nodes and has more stable generalization performance. …”
Get full text

2HR-Net VSLAM: Robust visual SLAM based on dual high-reliability feature matching in dynamic environments. by Wang Yang, Huang Chao, Zhang Yi, Tan Shuyi

“…Finally, the shared matching Siamese network with a unique dual-branch feature fusion strategy and similarity optimization algorithm is proposed to enhance the accuracy of feature matching. …”
Get full text

Software and hardware co-design of lightweight authenticated ciphers ASCON for the internet of things by Jing WANG, Lesheng HE, Zhonghong LI, Luchi LI, Hang YANG

“…ASCON was the most promising algorithm to become an international standard in the 2021 NIST lightweight authenticated encryption call for proposals.The algorithm was designed to achieve the best performance in IoT resource-constrained environments, and there was no hardware IP core implementation based on this algorithm in the open literature.A software-hardware collaborative implementation method of ASCON was proposed, which improved the speed and reduced the memory footprint of ASCON in IoT security authentication applications through hardware means such as S-box optimization, prior calculation and advanced pipeline design.As a comparison, ASCON has been transplanted on the common IoT embedded processor platform.The results showed that the described method was more than 7.9 times faster, while the memory footprint was reduced by at least 90%.The schemes can be used for the design and implementation of IoT security application-specific integrated circuits or SoCs.…”
Get full text

A Rice Leaf Area Index Monitoring Method Based on the Fusion of Data from RGB Camera and Multi-Spectral Camera on an Inspection Robot by Yan Li, Xuerui Qi, Yucheng Cai, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaohu Zhang

“…The model based on the LightGBM regression algorithm has the most improvement in accuracy, with a coefficient of determination (R²) of 0.892, a root mean square error (RMSE) of 0.270, and a mean absolute error (MAE) of 0.160. …”
Get full text

Reinforcement Learning for Computational Guidance of Launch Vehicle Upper Stage by Shiyao Li, Yushen Yan, Hao Qiao, Xin Guan, Xinguo Li

“…This manuscript investigates the use of a reinforcement learning method for the guidance of launch vehicles and a computational guidance algorithm based on a deep neural network (DNN). Computational guidance algorithms can deal with emergencies during flight and improve the success rate of missions, and most of the current computational guidance algorithms are based on optimal control, whose calculation efficiency cannot be guaranteed. …”
Get full text

Optimising the Selection of Input Variables to Increase the Predicting Accuracy of Shear Strength for Deep Beams by Mohammed Majeed Hameed, Faidhalrahman Khaleel, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abdulhakim AlSaadi

“…The study found that all applied models were significantly improved by the presence of the GAITH algorithm, except for the MLR model. …”
Get full text

Optimum Design Research on the Link Mechanism of the JP72 Lifting Jet Fire Truck Boom System by Guo Tong, Wang Jiawen, Liang Yingnan, Peng Buyu, Liu Tao, Liu Yiqun

“…The fmincon function was used to realize the sequential quadratic programming (SQP) algorithm, which is one of the most effective methods to solve the constrained nonlinear optimization problems, for the optimal design. …”
Get full text