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

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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. …”
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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.…”
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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. …”
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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. …”
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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. …”
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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. …”
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Prediction Method and Characteristics of Static Acoustic Scattering for Marine Composite Propellers by Suchen XU, Zilong PENG, Fulin ZHOU, Xuhong MIU, Huicheng KE

“…This study introduces a hybrid approach to predict the acoustic scattering characteristics of composite propellers featuring variable thickness and complex curvature. …”
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Predicting Future Intrablock Links in Directed Networks Using Triadic Patterns by Lekshmi S. Nair, J. j

“…Directed multilayer networks are used to represent such networks effectively, capturing the heterogeneity exhibited by the nodes and the directionality of relationships. The link prediction problem refers to predicting relationships (links) between the entities (nodes) that may arise in the future or identifying missing links to reconstruct the network. …”
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SOIL MOISTURE PREDICTION MODEL IN PEATLAND USING RANDOM FOREST REGRESSOR by Helda Yunita Taihuttu, Imas Sukaesih Sitanggang, Lailan Syaufina

“…For this reason, this study aims to create a prediction model for soil moisture as an early prevention of fires in peatlands using the Random Forest Regressor (RFR) algorithm. …”
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The Influential Factors and Prediction of Kuroshio Extension Front on Acoustic Propagation-Tracked by Weishuai XU, Lei ZHANG, Hua WANG

“…This study employed a backpropagation neural network to predict the acoustic propagation affected by the KEF. …”
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Distributed Target Detection with Coherent Fusion in Tracking Based on Phase Prediction by Aoya Wang, Jing Lu, Shenghua Zhou, Linhai Wang

“…From historic observations on target tracking, relative phase delays in different channels are predicted by a phase lock loop and then used to compensate phases for observations in the current frame. …”
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Factors Identification and Prediction for Mind Wandering Driving Using Machine Learning by Ciyun Lin, Hongli Zhang, Bowen Gong, Dayong Wu

“…The aim of this study was to propose a framework for analyzing and predicting MW based on readily available driving status data. …”
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