Dynamic characteristics of a semi-active fractional-order inerter-based suspension with acceleration-velocity switch control by Yong Wang, Jiachen Li, Mingzhu Ji, Xiwen Qiao, Yang Wang

“…According to the mechanical characteristic of the inerter, the acceleration-velocity switch (AVS) control strategy is proposed to adjust the inertance of the SA-FO inerter. The dynamic model of the SA-FOIB suspension with AVS control is established, its dynamic response under road harmonic excitation is obtained using the averaging method, the dynamic performance under road harmonic and random excitations is analyzed and evaluated by the vehicle body acceleration, suspension dynamic deflection and wheel dynamic load, the optimized structural parameters are obtained using the genetic algorithm optimization method. …”
Get full text

Research on the policy inconsistency, network motifs and low carbon effects for municipal solid waste management by Bo Lv, Tianxu Cui, Daiheng Li, Weiyue Yao

“…This study combines the policy consistency formula, a four-node network motif evolution algorithm, and the Exponential Random Graph Model (ERGM), analyzing MSWM green network motifs with carbon emission data. …”
Get full text

A Passive Radar System for Monitoring of Coastal Areas Ship Traffic Using Satellite Illumination Signals by Nguyen Van Quan

“…During development and implementation of the systems, there are a number of problems related to the search of highly efficient processing algorithms, to the optimization of structure and functioning modes when the system is a part of a complex multi-position monitoring system in coastal areas. …”
Get full text

High-Precision Extraction Method for Blade Tip-Timing Signal with Eddy Current Sensor by Ji-wang Zhang, Ke-qin Ding, Guang Chen

“…A new denoising and shaping algorithm based on ensemble empirical mode decomposition (EEMD) was introduced for the errors caused by background noise. …”
Get full text

Pose measurement method for coal mine drilling robot based on deep learning by Jiangnan LUO, Jianping LI, Hongxiang JIANG, Deyi ZHANG

“…This method consists of two parts: a segmentation model based on an improved PointNet++ and a point cloud registration process using the drill head and gripper. …”
Get full text

A Study on Path Planning for Curved Surface UV Printing Robots Based on Reinforcement Learning by Jie Liu, Xianxin Lin, Chengqiang Huang, Zelong Cai, Zhenyong Liu, Minsheng Chen, Zhicong Li

“…Experimental results show that the proposed method outperforms traditional path planning methods, as well as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
Get full text

MSDP-Net: A YOLOv5-Based Safflower Corolla Object Detection and Spatial Positioning Network by Hui Guo, Haiyang Chen, Tianlun Wu

“…For object detection, we introduce an improved YOLO v5m model, referred to as C-YOLO v5m, which integrates a Convolutional Block Attention Module (CBAM) into both the backbone and neck networks. …”
Get full text

Vulnerability Assessment in Karst Aquifers with EPIK and COP Indices Calibration by Hamid Kardan Moghadam, Amir Reza Nemati Mansour, Abbas Akbarzadeh, Ali Mirarabi

“…In order to calibrate the GQI qualitative index with the zoning of the springs in the region, whale optimization algorithms were used. In this calibration, the weights and ranks of the two vulnerability indices were determined. …”
Get full text

Research on a Panoramic Image Stitching Method for Images of Corn Ears, Based on Video Streaming by Yi Huangfu, Hongming Chen, Zhonghao Huang, Wenfeng Li, Jie Shi, Linlin Yang

“…Future research will focus on the following points: 1. addressing the issue of environmental interference caused by diseases, pests, and plant nutritional status on the measurement of corn ear parameters in order to enhance the stability and accuracy of the algorithm; 2. expanding the dataset for the U-Net model to include a wider range of corn ears with complex backgrounds, different growth stages, and various environmental conditions to improve the model’s segmentation recognition rate and precision. …”
Get full text

Multiple Interface Parallel Approach of Bioinspired Routing Protocol for Mobile Ad Hoc Networks by L. J. García Villalba, D. Rupérez Cañas, A. L. Sandoval Orozco, T.-H. Kim

“…The simulation results indicate that PAntOR and PAntOR-MI improve performances of AntOR, whilst it is also noticed that PAntOR-MI is the most suitable for highly dynamic environments.…”
Get full text

Rapid acquisition and surface defects recognition based on panoramic image of small-section hydraulic tunnel by Haoyu Wang, Jichen Xie, Jinyang Fu, Cong Zhang, Dingping Chen, Zhiheng Zhu, Xuesen Zhang

“…Such method enables the acquisition of full-length surface images of the hydraulic tunnels with different cross-section forms and diameters by a one-way travel, and the overlap rate and accuracy of the acquired image sets meet the requirements of three-dimensional reconstruction and panoramic image generation. In addition, to improve the speed and accuracy of traditional algorithms for tunnel surface defects detection, this paper proposes an improved YOLOv5s-DECA model. …”
Get full text

Analytical framework for household energy management: integrated photovoltaic generation and load forecasting mechanisms by Zhenping Xie, Yansha Li

“…To address the challenges associated with the intermittent and variable nature of solar energy, an innovative hybrid model is proposed. Specifically, this research integrates the K-nearest neighbor (KNN) classification method and genetic algorithm (GA) to optimize a backpropagation neural network (BPNN). …”
Get full text

A Design Framework for Scalable and Adaptive Multi-Agent Coordination in Dynamic Environments: Addressing Concurrent Agent and Environment Interactions by Raza Muhammad Kazim, Guoxin Wang, Zhenjun Ming, Jinhui Cao, Janet K. Allen, Farrokh Mistree

“…In this study, we explore the integration of surrogate response surface modeling (SRSM) with optimization algorithms, comparing Stochastic Gradient Descent (SGD) with a fixed learning rate, and adaptive learning rate (ALR) optimizers—including Adaptive Moment Estimation (ADAM) and Adaptive Approximate Direction Method Algorithm (AADMA)—to enhance MAS performance metrics, such as Agent Collision Rate (ACR), Agent Movement Frequency (AMF), and Task Completion Time (TCT). …”
Get full text

Advanced predictive analytics for bio-waste management using YOLOv8-SPP to enhance waste prediction and sustainability in smart cities by Selvalakshmi Balasubramanium, Bharathiraja Nagu, Shonak Bansal, Mohammad Rashed Iqbal Faruque, Kholoud Saad Al-mugren

“…This research suggests a new predictive analytics model using the YOLOv8-SPP algorithm for improved waste management. …”
Get full text

GIS partial discharge fault diagnosis method based on SGMD-LSTM by Zhang Yun, Zhang Chao, Zhang Shiyong, Ma Pengchi, Yang Guang, Ding Hao

“…The Osprey-Cauchy-Sparrow Search Algorithm (OCSSA) is used to adaptively optimize the number of hidden layer nodes and learning rate of LSTM. …”
Get full text

Learning atomic forces from uncertainty-calibrated adversarial attacks by Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson, Morten Ledum, Simen Reine, Sigbjørn Løland Bore

“…Abstract Adversarial approaches, which intentionally challenge machine learning models by generating difficult examples, are increasingly being adopted to improve machine learning interatomic potentials (MLIPs). …”
Get full text

Application of Machine Learning to Statistical Evaluation of Artificial Rainfall Enhancement by Li Dan, Lin Wen, Liu Qun, Feng Hongfang, Hu Shuping, Wang Zhihai

“…Each statistical model is greatly improved after six root square transformations of rainfall data. …”
Get full text

An Intelligent Method for C++ Test Case Synthesis Based on a Q-Learning Agent by Serhii Semenov, Oleksii Kolomiitsev, Mykhailo Hulevych, Patryk Mazurek, Olena Chernyk

“…However, test suites in open-source libraries often grow large, redundant, and difficult to maintain. Most traditional test suite optimization methods treat test cases as atomic units, without analyzing the utility of individual instructions. …”
Get full text

The Inversion of SPAD Value in Pear Tree Leaves by Integrating Unmanned Aerial Vehicle Spectral Information and Textural Features by Ning Yan, Yasen Qin, Haotian Wang, Qi Wang, Fangyu Hu, Yuwei Wu, Xuedong Zhang, Xu Li

“…Finally, four machine learning methods, namely XGBoost, random forest (RF), back-propagation neural network (BPNN), and optimized integration algorithm (OIA), were used to construct inversion models of the SPAD value of pear trees, with different feature inputs based on vegetation indices, textural features, and their combinations, respectively. …”
Get full text

Research on fine-grained classification of rare metal granite lithology based on deep learning by ZHAO Hengqian, WANG Pan, LIU Zhiguo, MIAO Qunfeng, LI Zhibin, TANG Guanglong, QI Yunfei, XIE Yu, WANG Mengmeng

“…In the future, the accuracy of fine-grained classification of rare metal granite lithology can be further improved by improving the quantity and quality of rock samples and optimizing the model algorithm.…”
Get full text