Implementation of personalized customization and enhanced experiences for cultural tourism resources using genetic algorithm-based virtual reality technology by Huiya Xing, Xiangyi Li, Min Liu, Yicong Zhong

“…By adjusting to these individual parameters, the algorithm cleverly optimizes tourist itineraries. The DDE-GA-powered VR system works better than current methods, according to experimental data, with improvements in reaction time (1.1 s), accuracy (98 %), precision (97 %), and modeling error (0.10). …”
Get full text

Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm by Vinoth Viswanathan, Sathiyamurthy Subbarayan, Ananthi Narayanaswamy, Devi Panneerselvam, Prabhakaran Jayasankar

Get full text

A Near-Real-Time Imaging Algorithm for Focusing Spaceborne SAR Data in Multiple Modes Based on an Embedded GPU by Yunju Zhang, Mingyang Shang, Yini Lv, Xiaolan Qiu

“…To achieve on-board real-time processing for sliding-spotlight mode synthetic aperture radar (SAR), on the one hand, this paper proposes an adaptive and efficient imaging algorithm for the sliding-spotlight mode. On the other hand, a batch processing method was designed and optimized based on the AGX Orin platform to implement the algorithm effectively. …”
Get full text

Comparative Study of Time Series Analysis Algorithms Suitable for Short-Term Forecasting in Implementing Demand Response Based on AMI by Myung-Joo Park, Hyo-Sik Yang

“…This paper compares four time series forecasting algorithms—ARIMA, SARIMA, LSTM, and SVM—suitable for short-term load forecasting using Advanced Metering Infrastructure (AMI) data. …”
Get full text

A study of parameter aggregation algorithms for virtual power plant terminal decentralized resource scheduling characteristics in alpine regions by Yan Wang, Ruizhi Zhang, Ying Wang, Wen Xiang, Lu Wang

“…An improved ant colony algorithm based on continuous optimization was used to solve the aggregation parameters. …”
Get full text

A New Approach Combining RSA and ElGamal Algorithms: Advancements in Encryption and Digital Signatures Using Gaussian Integers by Yahia Awad, Douaa Jomaa, Yousuf Alkhezi, Ramiz Hindi

“…This article introduces a novel approach that integrates the ElGamal and RSA algorithms to advance the security and efficiency of public-key cryptosystems. …”
Get full text

RE-BPFT: An Improved PBFT Consensus Algorithm for Consortium Blockchain Based on Node Credibility and ID3-Based Classification by Junwen Ding, Xu Wu, Jie Tian, Yuanpeng Li

“…Experimental results indicate that RE-BPFT markedly reduces consensus latency and communication costs while achieving higher throughput and better scalability than classical PBFT, RBFT, and PPoR algorithms. …”
Get full text

A Servo Control Algorithm Based on an Explicit Model Predictive Control and Extended State Observer with a Differential Compensator by Zhuobo Dong, Shuai Chen, Zheng Sun, Benyi Tang, Wenjun Wang

“…By employing an offline optimization approach, a control law is explicitly formulated to handle system constraints while minimizing online computational overhead. …”
Get full text

Inverse design of high-strength medium-Mn steel using a machine learning-aided genetic algorithm approach by Jin-Young Lee, Seung-Hyun Kim, Hyun-Bin Jeong, KeunWon Lee, KiSub Cho, Young-Kook Lee

“…To develop medium-Mn steels with an ultimate tensile strength (UTS) exceeding 2 GPa and excellent ductility, we created a highly accurate UTS prediction machine learning (ML) model using a boosted decision tree model and 1520 dataset of tensile properties of medium-Mn steels with micro-alloying elements. We also optimized the hyper-parameters of a genetic algorithm (GA) using the Shannon diversity index to enhance search efficiency while retaining diversity. …”
Get full text

Filling-well: An effective technique to handle incomplete well-log data for lithology classification using machine learning algorithms by Sherly Ardhya Garini, Ary Mazharuddin Shiddiqi, Widya Utama, Alif Nurdien Fitrah Insani

“…However, the ANN can suffer from overfitting and requires large datasets for optimal performance. In contrast, KNN struggled with missing-not-at-random (MNAR) data due to its reliance on the k parameter and distance metric, making it less effective in mapping missing data relationships. • Missing values in well-log data can hinder lithology classification accuracy for efficient resource exploration in the oil and gas industry. • This research aims to address the problem of missing values in well-log datasets by applying machine learning algorithms such as XGBoost, ANN, and KNN to enhance classification performance. • XGBoost demonstrated superior performance in handling extreme missing data (30 %) in well-log datasets. …”
Get full text

Magnetic resonance imaging measurement of the femoral antetorsional angle: Comparison with computer tomography and clinical application in a diagnostic algorithm by Ewa Tramś, Maciej Liszka, Krzysztof Kuliński, Kamila Malesa, Marcin Tyrakowski, Jerzy Białecki, Rafał Kamiński

Get full text

An adaptive k-means clustering algorithm based on grid and domain centroid weights for digital twins in the context of digital transformation by Wei Cai, Fei Yang, Bo Yao, Chuanxian Li, Guangyu Sun

“…The algorithm automatically determines the optimal number of clusters k and initial centroids. …”
Get full text

Dynamic Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC Algorithm by Manzhi Yang, Hao Ren, Shijia Liu, Bin Feng, Juan Wei, Hongyu Ge, Bin Zhang

“…Our methodology comprises four key stages: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based decomposition of historical error data, development of component-specific prediction models using Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) algorithms for each Intrinsic Mode Function (IMF), integration of component predictions to generate initial values, and application of the Adaptive Prediction Correction (APC) module to produce final predictions. …”
Get full text

ADMET evaluation in drug discovery: 21. Application and industrial validation of machine learning algorithms for Caco-2 permeability prediction by Dong Wang, Jieyu Jin, Guqin Shi, Jingxiao Bao, Zheng Wang, Shimeng Li, Peichen Pan, Dan Li, Yu Kang, Tingjun Hou

“…We believe that the model developed in this study could represent a reliable tool for assessing Caco-2 permeability during early-stage drug discovery and the chemical transformation rules derived here could provide insights for optimizing Caco-2 permeability. Scientific contribution A comprehensive validation of various machine learning algorithms combined with diverse molecular representations on a large dataset for predicting Caco-2 permeability was reported. …”
Get full text

Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm by Qiyuan Cui, Jianhong Pu, Wei Li, Yun Zheng, Jiaxi Lin, Lu Liu, Peng Xue, Jinzhou Zhu, Mingqing He

“…Feature selection, parameter optimization, and model construction were performed in the training set, while the validation set was used to evaluate the predictive performance of the models. …”
Get full text

Crops Disease Detection, from Leaves to Field: What We Can Expect from Artificial Intelligence by Youssef Lebrini, Alicia Ayerdi Gotor

Get full text

Identifying key factors influencing maize stalk lodging resistance through wind tunnel simulations with machine learning algorithms by Guanmin Huang, Ying Zhang, Shenghao Gu, Weiliang Wen, Xianju Lu, Xinyu Guo

“…Climate change has intensified maize stalk lodging, severely impacting global maize production. While numerous traits influence stalk lodging resistance, their relative importance remains unclear, hindering breeding efforts. …”
Get full text

Disaggregated and Distributed Near-Real-Time RIC for Large Scale User-Centric RAN by Amr Amrallah, Yu Tsukamoto, Takahide Murakami, Akio Ikami, Hiroyuki Shinbo, Yoshiaki Amano

“…Our proposed divide-and-conquer (D&C) and heuristic-greedy (HG)-based algorithms significantly reduce computational complexity while maintaining near-optimal performance. …”
Get full text

Unmanned trackless rubber wheeler based on LD improved Cartographer mapping algorithm underground SLAM autonomous navigation method and test by Fangwei LI, Jiusheng BAO, Chen WANG, Xiaoming YUAN, Yan YIN, Shirong GE, Maosen WANG, Yuhan LV

“…Firstly, a two-dimensional raster map of the underground roadway environment is constructed based on the Cartographer algorithm, and the Lazy Decision (LD) algorithm is introduced to optimize it, which solves the overlapping and fuzzy phenomena during Cartographer mapping and improves the mapping accuracy. …”
Get full text

Development of a PYTHON library for a mathematical model of nuclear reactor kinetics by Aleksei G. Goryunov, Danil D. Kachanov, Kirill D. Kachanov

Get full text