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

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Quantum Perceptron in Predicting the Number of Visitors to E-Commerce Websites in Indonesian by Solikhun Solikhun, Dinda Carissa Arishandy, Ela Roza Batubara, Poningsih

“…The research results show that the Quantum Perceptron algorithm can make predictions very well compared to the classical perceptron, proven by the Quantum Perceptron having a perfect accuracy of 100% with a total of 2 epochs while the classical perceptron has 100% accuracy with a total of 10 epochs. …”
Get full text

Predicting for mortality rate using regression analysis in patient with burn injury by O. O. Zavorotniy, E. V. Zinoviev, D. V. Kostyakov

“…The final algorithm included 18 predictors. The model allows predicting a positive outcome of treatment and the likelihood of a fatal outcome with an accuracy of 93 and 87 % respectively.Conclusion. …”
Get full text

Digital Twin and Data-Driven Remaining Useful Life Prediction of Gearbox by Quanbo Lu, Mei Li, Xiaojuan Huang

“…To further improve prediction accuracy, the paper employs the Central Particle Swarm Optimization algorithm to merge both theoretical and actual RUL values. …”
Get full text

RUL prediction method based on cross-view hybrid network model by Ai Yandi, Fang Dong, Tian Zhiping, Yan Kaiyang

“…Secondly, a RUL regression algorithm integrating Transformer encoder and nonlinear fitter is developed to automatically learn the correlation between features in different views and predict RUL. …”
Get full text

Curing simulation and data-driven curing curve prediction of thermoset composites by Chenchen Wu, Ruming Zhang, Pengyuan Zhao, Liang Li, Dingguo Zhang

“…Then, the temperature–time and the resulting degree-of-cure-time curves obtained from finite element simulations were created for training the prediction models using machine learning approaches of support vector regression (SVR), back propagation (BP) neural network and BP neural network optimized by genetic algorithm (GA-BP). …”
Get full text

RUL Prediction Based on MBGD-WGAN-GRU for Lithium-Ion Batteries by Zhiguo Zhao, Ke Li, Yibo Dai, Biao Chen, Yeqin Wang, Qian Zhao

“…To address the challenges associated with acquiring complete charge-discharge cycle data and extracting health indicator factors (IHFs) from fragmented datasets in current automotive lithium-ion batteries (LIBs), this study proposes a novel online remaining useful life (RUL) prediction method. First, the IHF, which captures battery aging characteristics, is extracted from raw LIBs data, and the dataset is partitioned into training (70%) and testing (30%) subsets. …”
Get full text

Machine learning-based prediction of LDL cholesterol: performance evaluation and validation by Jing-Bi Meng, Zai-Jian An, Chun-Shan Jiang

“…Objective This study aimed to validate and optimize a machine learning algorithm for accurately predicting low-density lipoprotein cholesterol (LDL-C) levels, addressing limitations of traditional formulas, particularly in hypertriglyceridemia. …”
Get full text