Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

Get full text

Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

Get full text

Self-supervised change detection of heterogeneous images based on difference algorithms by Jinsha Wu, Shuwen Yang, Yikun Li, Yukai Fu, Zhuang Shi, Yao Zheng

“…Finally, the support vector machine classifier automatically detects whether the intermediate pixels are changed and produces the change detection results. …”
Get full text

LogiTriBlend: A Novel Hybrid Stacking Approach for Enhanced Phishing Email Detection Using ML Models and Vectorization Approach by Aqsa Khalid, Maria Hanif, Abdul Hameed, Zeeshan Ashraf, Mrim M. Alnfiai, Salma M. Mohsen Alnefaie

“…The model combines multiple base learners, including Support Vector Machine (SVM), Logistic Regression, Random Forest, and XGBoost, with a Logistic Regression meta-learner. …”
Get full text

Fault Detection in Harmonic Drive Using Multi-Sensor Data Fusion and Gravitational Search Algorithm by Nan-Kai Hsieh, Tsung-Yu Yu

“…The optimized features are then input into a support vector machine (SVM) for fault classification, with K-fold cross-validation used to assess the model’s generalization capabilities. …”
Get full text

Combine photosynthetic characteristics and leaf hyperspectral reflectance for early detection of water stress by Linbao Li, Linbao Li, Linbao Li, Guiyun Huang, Guiyun Huang, Guiyun Huang, Jinhua Wu, Jinhua Wu, Jinhua Wu, Yunchao Yu, Yunchao Yu, Yunchao Yu, Guangxin Zhang, Guangxin Zhang, Guangxin Zhang, Yang Su, Yang Su, Yang Su, Xiongying Wang, Xiongying Wang, Xiongying Wang, Huiyuan Chen, Huiyuan Chen, Huiyuan Chen, Yeqing Wang, Di Wu, Di Wu, Di Wu

“…Multivariate Linear Regression (MLR) and three machine learning algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) were employed to develop models for estimating LCC and ChlF parameters. …”
Get full text

Research of a spam filter based on improved naive Bayes algorithm by 曹翠玲, 王媛媛, 袁野, 赵国冬

“…In spam filtering filed,naive Bayes algorithm is one of the most popular algorithm,a modified using support vector machine(SVM)of the native Bayes algorithm :SVM-NB was proposed.Firstly,SVM constructs an optimal separating hyperplane for training set in the sample space at the junction two types of collection,Secondly,according to its similarities and differences between the neighboring class mark for each sample to reduce the sample space also increase the independence of classes of each samples.Finally,using naive Bayesian classification algorithm for mails.The simulation results show that the algorithm reduces the sample space complexity,get the optimal classification feature subset fast,improve the classification speed and accuracy of spam filtering effectively.…”
Get full text

Development and validation of an explainable machine learning model for predicting postoperative pulmonary complications after lung cancer surgery: a machine learning studyResearch... by Shaolin Chen, Ting Deng, Qing Yang, Jin Li, Juanyan Shen, Xu Luo, Juan Tang, Xulian Zhang, Jordan Tovera Salvador, Junliang Ma

“…The stacking ensemble combining Support Vector Machine (SVM) and Decision Tree (DT) showed the highest overall performance, with an AUROC of 0.860 (95% CI: 0.809–0.911), and DCA showed higher clinical utility compared to other models. …”
Get full text

A big data analysis algorithm for massive sensor medical images by Sarah A. Alzakari, Nuha Alruwais, Shaymaa Sorour, Shouki A. Ebad, Asma Abbas Hassan Elnour, Ahmed Sayed

“…Current anomaly detection methods in healthcare systems, such as artificial intelligence and big data analytics-intracerebral hemorrhage (AIBDA-ICH) and parallel conformer neural network (PCNN), face several challenges, including high resource consumption, inefficient feature selection, and an inability to handle temporal data effectively for real-time monitoring. Techniques like support vector machines (SVM) and the hidden Markov model (HMM) struggle with computational overhead and scalability in large datasets, limiting their performance in critical healthcare applications. …”
Get full text

Personalization in Mobile Activity Recognition System Using -Medoids Clustering Algorithm by Quang Viet Vo, Minh Thang Hoang, Deokjai Choi

“…Therefore, we propose an algorithm that integrates Support Vector Machine classifier and K -medoids clustering method to resolve completely the demand.…”
Get full text

A Highly Discriminative Hybrid Feature Selection Algorithm for Cancer Diagnosis by Tarneem Elemam, Mohamed Elshrkawey

“…In the second stage, the modified wrapper-based sequential forward selection is utilized to discover the optimal feature subset, using ML models such as support vector machine (SVM), decision tree (DT), random forest (RF), and K-nearest neighbor (KNN) classifiers. …”
Get full text

Comparative Study for Classification Algorithms Performance in Crop Yields Prediction Systems by Halbast Rashid Ismael, Adnan Mohsin Abdulazeez, Dathar A. Hasan

“…The performance of the decision tree, naive Bayes, random forest, support vector machine and K-nearest neighbour is measured and compared to each other. …”
Get full text

Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

“…The aim of this research is to compare and analyze the prediction accuracy of machine learning algorithms, i.e., Artificial neural network (ANN), Support vector machine (SVM), Naïve Bayes (NB), Decision tree (DT), Logistic regression (LR), and K-nearest neighbor (KNN) to identify security and performance bugs from the bug repository. …”
Get full text

IDE-SVM algorithm and it's usage in physical layer security method for IoT by WANG Qiang, ZHU Chenming, PAN Su, QIN Yuxi

“…To address the problem that there is no standard for the parameter selection of support vector machine (SVM) algorithm, a parameter optimization selection method based on the integrated improved differential evolution (IDE) algorithm is proposed, which uses the minimization of the classification error rate as the optimization criterion and the improved differential evolution algorithm to optimize the combination of SVM parameters to obtain an SVM algorithm with higher classification accuracy. …”
Get full text

Scanning Micromirror Calibration Method Based on PSO-LSSVM Algorithm Prediction by Yan Liu, Xiang Cheng, Tingting Zhang, Yu Xu, Weijia Cai, Fengtian Han

“…This paper presents a novel scanning micromirror calibration method based on the prediction of a particle swarm optimization-least squares support vector machine (PSO-LSSVM). The objective is to establish a correspondence between the actual deflection angle of the micromirror and the output of the measurement system employing a regression algorithm, thereby enabling the prediction of the tilt angle of the micromirror. …”
Get full text

Extreme Gradient Boosting Algorithm for Predicting Shear Strengths of Rockfill Materials by Mahmood Ahmad, Ramez A. Al-Mansob, Kazem Reza Kashyzadeh, Suraparb Keawsawasvong, Mohanad Muayad Sabri Sabri, Irfan Jamil, Arnold C. Alguno

Get full text

Speech emotion recognition algorithm of intelligent robot based on ACO-SVM by Xueliang Kang

“…Aiming at the shortcomings of existing algorithms in the accuracy and processing of complex emotion states, a novel emotion recognition model of intelligent robot speech based on ACO algorithm and multi-level support vector machine is proposed. …”
Get full text

Application of Big Data Technology to Assessments of Female Ovarian Reserve Dysfunction by Xia Ji'An, Ma YunFei, Wu YiYun, Zhao YouLin, Ni HaoRang, Liu XinYan

“…In the big data platform, the random forest algorithm achieved the highest classification accuracy (89.47%), followed by the neural network (81.06%) and support vector machine (72.91%) methods. …”
Get full text

ALGORITHM OF PREPARATION OF THE TRAINING SAMPLE USING 3D-FACE MODELING by D. I. Samal, I. I. Frolov

“…The algorithm of preparation and sampling for training of the multiclass qualifier of support vector machines (SVM) is provided. …”
Get full text

A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Developme... by Xiaojie Jin, Yanru Wang, Jiarui Wang, Qian Gao, Yuhan Huang, Lingyu Shao, Jiali Zhao, Jintian Li, Ling Li, Zhiming Zhang, Shuyan Li, Yongqi Liu

“…ObjectiveThis study aims to construct a diagnostic model for differentiating cold and hot syndromes in viral pneumonia by integrating TCM and modern medical features using machine learning methods. MethodsThe application of 8 machine learning algorithms (gradient boosting machine [GBM], logistic regression, random forest, extreme gradient boosting [XGB], light gradient boosting machine [LGB], ridge regression, least absolute shrinkage and selection operator, and support vector machine) generated and validated (both internally and externally) a model for differentiating cold and hot syndromes in viral pneumonia, based on clinical data from 1484 patient samples collected at 2 medical centers between 2021 and 2022. …”
Get full text