Empc-based V2G scheduling strategy for multi-attribute EVs aggregator by Haoyang Tang, Zhilu Liu, Lin Zheng, Jianfeng Zheng, Hao Hu, Jinpei Lu, Zhijian Hu

“…First, a multi-attribute EVs aggregation model is established based on Markov chains. The batteries in the battery swapping station are considered in this model Second, an economic model predictive control (EMPC) algorithm is proposed to solve the aggregation model. …”
Get full text

Current Stress Optimization in Buck-Boost Mode Based on New Extended Phase-Shift Dual Active Full-Bridge Converter by TAO Haijun, WANG Hongyi, YANG Naitong

“…According to the relationship between the phase shift angles, working modes are divided into three types, and the current stress expression and power model are obtained. Moreover, the improved working mode is obtained by comparative analysis, and the optimal phase shift combination of current stress is obtained by using Lagrange multipler method algorithm. …”
Get full text

Research on the Performance Optimization of Turbulent Self-Noise Suppression and Sound Transmission of Acoustic Windows Made from Functionally Graded Material by Bing LI, Fu-Lin ZHOU, Jun FAN, Bin WANG, Liwen TAN

“…For a simplified sonar dome model, an optimization method for internal gradients of functionally graded material (FGM) acoustic windows is proposed in this paper. …”
Get full text

Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith... by S. Ajith, S. Vijayakumar, N. Elakkiya

“…Artificial intelligence algorithms efficiently process vast datasets from unmanned aerial vehicles, ground vehicles, and satellites, enabling precise and timely interventions. …”
Get full text

Refining efficiency in standalone proton exchange membrane fuel cell systems through gross hopper optimization-based maximum power point tracking control by Nethra K., Reddy K. Jyotheeswara, Dash Ritesh, Parida Prasanta Kumar, Swain Sarat Chandra, Dhanamjayulu C., Mahapatro Abinash

“…To further improve prediction accuracy, the GHO algorithm incorporates a natural cubic-spline prediction model within its iterative mechanism, which enhances power generation predictions under dynamic conditions such as abrupt changes in fuel cell temperature and reactant partial pressure. …”
Get full text

A Novel Main-Lobe Cancellation Method Based on a Single Notch Space Filter and Optimized Correlation Analysis Strategy by Jiazhi Zhang, Xin Zhang, Weibo Deng, Liang Guo, Qiang Yang

“…But the new system also brings new challenges. One of the most severe problems is that the heterogeneous environment makes a big challenge for the sea clutter suppression processing. …”
Get full text

Discovering hierarchical process models: an approach based on events partitioning by Antonina K. Begicheva, Irina A. Lomazova, Roman A. Nesterov

“…Currently, many companies are using this technology to optimize and improve their business processes. However, a discovered process model may be too detailed, sophisticated, and difficult for experts to understand. …”
Get full text

RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

“…The graphs are processed using a graph neural network with DiffPool. To optimize feature integration, we incorporate an improved dung beetle optimization algorithm, which adaptively assigns fusion weights during inference. …”
Get full text

Sparse Array Mutual Coupling Reduction by C. Larmour, N. Buchanan, V. Fusco, M. Ali Babar Abbasi

Get full text

Parametric Model for Coaxial Cavity Filter with Combined KCCA and MLSSVR by Shengbiao Wu, Huaning Li, Xianpeng Chen

“…First, the low-dimensional tuning data is mapped to the high-dimensional feature space by kernel canonical correlation analysis, and the nonlinear feature vectors are fused by the kernel function; second, the multioutput least squares support vector regression algorithm is used for parametric modeling to solve the problems of low accuracy and poor prediction performance; third, the support vector of the parameter model is optimized by the differential evolution whale algorithm (DWA) to improve the convergence and generalization ability of the model in actual tuning. …”
Get full text

Estimating the Aboveground Biomass of an Evergreen Broadleaf Forest in Xuan Lien Nature Reserve, Thanh Hoa, Vietnam, Using SPOT-6 Data and the Random Forest Algorithm by The Dung Nguyen, Martin Kappas

“…Adding texture features into the predictor variables did not improve the model performance. In addition, the SPOT-6 sensor has the potential to predict forest AGB using the RF algorithm.…”
Get full text

A Ship Heading Estimation Method Based on DeepLabV3+ and Contrastive Learning-Optimized Multi-Scale Similarity by Weihao Tao, Yasong Luo, Jijin Tong, Qingtao Xia, Jianjing Qu

“…The framework introduces the Multi-Scale Structural Similarity (MS-SSIM) algorithm enhanced by a triplet contrastive learning mechanism that dynamically optimizes feature weights across scales, thereby improving robustness against image degradation and partial occlusion. …”
Get full text

Embedded Rough-Neck Helmholtz Resonator Low-Frequency Acoustic Attenuator by Xianming Sun, Tao Yu, Lipeng Wang, Yunshu Lu, Changzheng Chen

“…Moreover, by coupling the BP network with the Golden Jackal Optimization (GJO) algorithm, a BP-GJO optimization model is developed to refine the structural parameters. …”
Get full text

An Optimization Framework for Waste Treatment Center Site Selection Considering Nighttime Light Remote Sensing Data and Waste Production Fluctuations by Junbao Xia, Yanping Liu, Haozhong Yang, Guodong Zhu

“…Distinct from prior studies, this study suggests that service point waste quantities are not fixed values but rather adhere to a normal distribution within specified ranges and thus provides a more realistic simulation of fluctuations in waste production while enhancing both the robustness and predictive accuracy of the model. In conclusion, by incorporating nighttime light remote sensing data along with advanced machine learning techniques, this study markedly improves forecasting accuracy for waste production while offering effective optimization strategies for site selection and recovery route planning—thereby establishing a robust data foundation aimed at refining urban solid waste management systems.…”
Get full text

Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Saleh Ba-swaimi, Renuga Verayiah, Vigna K. Ramachandaramurthy, Ahmad K. ALAhmad, Sanjeevikumar Padmanaban

“…This work presents a stochastic two-stage mixed-integer nonlinear programming (MINLP) optimization model for the long-term planning of a distribution system (DS) to improve renewable energy integration over a ten-year period. …”
Get full text

A multi task learning framework using DeBERTa and BWO optimization for enhancing long term english vocabulary memory by Jiasheng Zhu

“…This study shows that the BWO-optimized DeBERTa multi-task learning model can effectively improve the long-term memory retention of English words and has stronger anti-interference ability in complex memory environments.…”
Get full text

Migraine triggers, phases, and classification using machine learning models by Anusha Reddy, Ajit Reddy

“…These models are run with the dataset without optimal tuning across the entire dataset for different migraine types; which is further improved with selective sampling and optimal tuning. …”
Get full text

An Optimal Energy Management Strategy With Time-Varying Equivalent Factor Based on Transformer for Multi-Mode Hybrid Electric Mining Trucks by Xinxin Zhao, Jiaqi Li, Menglei Liu, Jinggang Zhang, Nasser Lashgarian Azad

“…This paper introduces an advanced Transformer network model aimed at an adaptive Energy Management Strategy (EMS) to improve the fuel efficiency of Hybrid Electric Mining Trucks (HEMTs). …”
Get full text

Efficiency assessment of micro hydropower for agriculture using modern modeling by Urishev Omadjon, Salomov Uktam, Ergashev Sirojiddin, Kuchkarov Akmaljon, Madaliev Murodil, Abdukarimov Bekzod, Juraev Nurmakhamad

“…Using modern numerical analysis methods, including computational turbulence modeling algorithms, the study evaluates the energy production and optimization of micro-hydropower plant operation under various conditions. …”
Get full text

Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…Experimental results of antennas modeling demonstrate that the proposed algorithm improves the prediction accuracy and fitting performance relative to BNN. …”
Get full text