EMUs Electrical Connector Life Prediction Based on Accelerated Degradation Data by Jie MA, Lide WANG, Chuan YUE, Ping SHEN, Ji QIU

“…Using physical model of life prediction and data processing algorithm and accelerated degradation data modeling process based on degradation distribution, the reliability and life evaluation of EMUs electrical connectors were realized. …”
Get full text

Comparison of traffic flow prediction based on AR model and BP model by Tingting ZHANG, Wuxiong ZHANG, Dong PEI, Cheng ZHAO, Han YU

“…Based on Shanghai’s traffic flow data，the performance of the two different models was compared using auto regressive（AR）model and back-propagation（BP） network model，and the corresponding prediction result was given. Research finds that both of the two models can efficiently predict the traffic data，but they have different prediction accuracy for the data of different periods. …”
Get full text

Design and Implementation of Stock Market Prediction System for Used Cars in Nigeria by A. A. Ibrahim, A. A. Alabi, O. A. Ayilara-Adewale, F. R. Olokun-Olukotun

“…Hence, the objective of this study was to design and implement a stock market price prediction system for used cars in Nigeria using machine learning techniques, the extra tree algorithm and support vector machine (SVM). …”
Get full text

Traffic prediction and load balancing based on in-band network telemetry data by ZHANG Xu, ZHAO Chenxi, FENG Chuan, WEN Ting, LIU Wei, GUO Lei

“…The control module dynamically adjusted service flow paths using SRv6 technology, based on the prediction results from the analysis module. Simulation results show that the proposed model outperforms other methods in prediction accuracy and successfully achieves congestion avoidance.…”
Get full text

Efficient Prediction of Superlattice and Anomalous Miniband Topology from Quantum Geometry by Valentin Crépel, Jennifer Cano

“…In this article, we develop a versatile and computationally inexpensive method to predict the topological properties of materials subjected to a superlattice potential by combining degenerate perturbation theory with the method of symmetry indicators. …”
Get full text

Predicting the Risk of Loneliness in Children and Adolescents: A Machine Learning Study by Jie Zhang, Xinyi Feng, Wenhe Wang, Shudan Liu, Qin Zhang, Di Wu, Qin Liu

“…Background: Loneliness is increasingly emerging as a significant public health problem in children and adolescents. Predicting loneliness and finding its risk factors in children and adolescents is lacking and necessary, and would greatly help determine intervention actions. …”
Get full text

Predicting Electromagnetic Performance Under Wrinkling in Thin-Film Phased Arrays by Xiaotao Zhou, Jianfei Yang, Lei Zhang, Huanxiao Li, Xin Jin, Yesen Fan, Yan Xu, Xiaofei Ma

“…Parametric studies across stiffness ratios confirm the framework’s ability to predict shifts in pattern, gain, and impedance due to wrinkling. …”
Get full text

Research and Application of Capacitor Fault Prediction forLocomotive Traction Converter by ZHAN Yanhao, YANG Jiawei, LU Qingsong

“…In order to avoid the increase of input power load caused by the performance degradation of locomotive traction converter capacitor that affects the safe and reliable operation of a traction system, a capacitor fault prediction method is proposed in this paper. Capacitor parameters are identified by detecting output voltage ripples of capacitor, and capacitor parameters are fitted based on LS-SVM algorithm to identify the degradation characteristics of capacitor, so as to realize fault prediction of capacitor. …”
Get full text

Storage Life Prediction Based on Kernel Path Classification and Estimation Model by PAN Yuxiong, ZHOU Guifa, WANG Xu

“…A new individual-based prognostic algorithm, named the kernel path classification and estimation (KPACE) model, which is entirely based on the converted degradation data, has been developed to predict remaining storage life estimation of electronic product. …”
Get full text

HEVC information hiding approach based on intra prediction modes modulation by Jie YANG, Song-bin LI, Hao-jiang DENG

“…For further improving the embedding efficiency in the processing of HEVC information hiding,a method for HEVC information hiding based on intra prediction models modulation was proposed.The space lattice dimen-sion N(N = 2,3,4)of each CTU was generated according to the key.The selection rule of intra prediction mode was utilized to select N modes which were located at vertex angle.The N modes were mapped to the value F through the space lattice mapping algorithm.Then N bits secret information were read from the bit file and converted to a deci-mal number D.In this way,N secret information bits were embedded in N intra prediction modes by modifying at most one mode.The experimental results approve that the proposed method has high embedding efficiency,small rate increase and minimal influence on the video quality and the anti-steganalysis experiment confirms that the pro-posed method has high concealment.…”
Get full text

Research on Lateral Motion Prediction and Control of Autonomous-rail Rapid Tram by YAN Yongjun, WANG Jinxiang, HU Yunqing, YUAN Xiwen, WU Mengyang, HUANG Ruipeng, WANG Bin

“…In this paper, model predictive control (MPC) method is used to study the path tracking control of autonomous-rail rapid tram. …”
Get full text

Analysis of Heuristic Uniform Theory of Diffraction Coefficients for Electromagnetic Scattering Prediction by Diego Tami, Cássio G. Rego, Dinael Guevara, Andrés Navarro, Fernando J. S. Moreira, Jordi Giménez, Hernan G. Triana

“…We compare not only the results of the canonical models but also their implementation in real outdoor scenarios. To predict the coverage of mobile networks, we used propagation models for outdoor environments by using a 3D ray-tracing model based on a brute-force algorithm for ray launching and a propagation model based on image theory. …”
Get full text

An enhanced Transformer framework with incremental learning for online stock price prediction. by Yiming Qian

“…To address the limitations of existing stock price prediction models in handling real-time data streams-such as poor scalability, declining predictive performance due to dynamic changes in data distribution, and difficulties in accurately forecasting non-stationary stock prices-this paper proposes an incremental learning-based enhanced Transformer framework (IL-ETransformer) for online stock price prediction. …”
Get full text

The Utilization of Naive Bayes and C.45 in Predicting The Timeliness of Students’ Graduation by Agung Wibowo, Danny Manongga, Hindriyanto Dwi Purnomo

Get full text

BIMLP Model Based on Deep Learning for Predicting Electrical Load Demand by Somayeh Talebzadeh, Reza Radfar, Abbas Toloei Ashlaghi

“…The accurate prediction of electricity demand is crucial for efficient energy management and grid operation. …”
Get full text

Predicting Rainfall for Farming in the Bantul Region Using an Artificial Neural Network by Salsalbilla Septya, Riyadi Slamet, Zaki Ahmad, Nursetiawan Nursetiawan

“…This data is processed using Artificial Neural Networks to accurately predict rainfall in the region. The test results show that the comparison of the actual data results of rainfall prediction using the Levenberg Marquart algorithm with 1,080 training data of 80% data composition, validation data 10 and test data 10 with layer 4 size with layer 10 hidden neural produces predictions with a good level of accuracy and obtains a value of R = 0.900.…”
Get full text

Combination of dynamic TOPMODEL and machine learning techniques to improve runoff prediction by Pin‐Chun Huang

“…The present study aims to evaluate the optimal combination of these parameters within the dynamic TOPMODEL framework using machine learning techniques to improve the accuracy of runoff predictions and bolster the model's reliability. An innovative training method is suggested to elevate the model's performance by integrating the Long Short‐Term Memory (LSTM) algorithm and a topological classification, which relies on the evolving spatial distribution of runoff conditions during floods. …”
Get full text

Predicting the diversity of photosynthetic light-harvesting using thermodynamics and machine learning. by Callum Gray, Samir Chitnavis, Tamara Buja, Christopher D P Duffy

“…Using a generalized thermodynamic model of light-harvesting, coupled with an evolutionary algorithm, we predict the type of light-harvesting structures that might evolve in light of different intensities and spectral profiles. …”
Get full text

Crystal structure prediction based on diffusion model and graph network optimization by Tao Hong, Jiong Yang, Guixin Cao

“…In this work, we propose a crystal structure prediction method called DiffOA, which combines a diffusion model with an optimization algorithm based on GNNs. …”
Get full text

Method and System for Heart Rate Estimation Using Linear Prediction Filtering by Vitor O. T. Souza, Fabrício G. S. Silva, José M. Araújo, Jaimilton S. Lima

“…This work presents a method and system for heart rate estimation using Linear Prediction Coefficients (LPCs) centered on an ESP32 microprocessor module and an AD8232 ECG signal conditioning module. …”
Get full text