An intelligent prediction method for rock core integrity based on deep learning by Zhaoxia Hu, Hua Mei, Lei Yu

“…Abstract To address the issue of serious inefficiency in the traditional manual evaluation methods of rock core integrity, a deep learning-based algorithm named IDA-RCF (Intelligent detection algorithm for Rock Core Fissure) is proposed in this paper, which realizes the automatic evaluation of rock core integrity in accordance with the fissure identification results. …”
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CT Radiomics Nomogram Prediction for Tumor Deposits and Prognosis in Colorectal Cancer by Manman LI, Yigang FU, Yong XIAO, Wang CHEN, Feng FENG, Guodong XU

“…Objective: To establish computed tomography (CT) radiomics nomogram for preoperative prediction of tumor deposits (TD) and recurrence-free survival (RFS) in patients with colorectal cancer (CRC). …”
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Use Self-Training Random Forest for Predicting Winter Wheat Yield by Yulin Shen, Benoît Mercatoris, Qingzhi Liu, Hongxun Yao, Zongpeng Li, Zhen Chen, Wensheng Wang

“…The effectiveness of supervised ML heavily depends on having a large, accurate, and diverse annotated dataset, which poses a challenge in applying ML for yield prediction. To address this issue, we developed a self-training random forest algorithm capable of automatically expanding the annotated dataset. …”
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Convolution of the physical point cloud for predicting the self-assembly of colloidal particles by Seunghoon Kang, Young Jin Lee, Kyung Hyun Ahn

“…This paper presents a novel algorithm for predicting the kinetic and thermodynamic pathways of colloidal systems. …”
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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

“…Experimental results show that the porosity prediction model based on the CNN-BiLSTM-Transformer algorithm achieves lower average relative error and better prediction performance. …”
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Fast Prediction for Roll Motion of a Damaged Ship Based on SVR by LIU Han, SU Yan, ZHANG Guoqiang

“…Finally, a fast prediction model for rolling motion is constructed and validated, offering a significant improvement in the prediction efficiency compared with traditional computational fluid dynamics models.…”
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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. …”
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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. …”
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Pattern mining and prediction techniques for user behavioral trajectories in e-commerce. by Xin Wang, Dong-Feng Liu

“…Second, it introduces a frequent sub-trajectory mining algorithm that emphasizes the order of user visits for trajectory analysis and prediction. …”
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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). …”
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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.…”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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.…”
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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. …”
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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. …”
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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. …”
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