Predictive channel scheduling algorithm between macro base station and micro base station group by Yinghai XIE, Ruohe YAO, Bin WU

“…A novel predictive channel scheduling algorithm was proposed for non-real-time traffic transmission between macro-base stations and micro-base stations in 5G ultra-cellular networks.First,based on the stochastic stationary process characteristics of wireless channels between stationary communication agents,a discrete channel state probability space was established for the scheduling process from the perspective of classical probability theory,and the event domain was segmented.Then,the efficient scheduling of multi-user,multi-non-real-time services was realized by probability numerical calculation of each event domain.The theoretical analysis and simulation results show that the algorithm has low computational complexity.Compared with other classical scheduling algorithms,the new algorithm can optimize traffic transmission in a longer time dimension,approximate the maximum signal-to-noise ratio algorithm in throughput performance,and increase system throughput by about 14% under heavy load.At the same time,the new algorithm is accurate.Quantitative computation achieves a self-adaption match between the expected traffic rate and the actual scheduling rate.…”
Get full text

Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors by Michael Reich, Njira Lugogo, Laurie D Snyder, Megan L Neely, Guilherme Safioti, Randall Brown, Michael DePietro, Roy Pleasants, Thomas Li, Lena Granovsky

“…This analysis aimed to determine if a machine learning algorithm capable of predicting impending exacerbations could be developed using data from an integrated digital inhaler.Patients and methods A 12-week, open-label clinical study enrolled patients (≥40 years old) with COPD to use ProAir Digihaler, a digital dry powder inhaler with integrated sensors, to deliver their reliever medication (albuterol, 90 µg/dose; 1–2 inhalations every 4 hours, as needed). …”
Get full text

Safety-critical nonlinear optimal predictive control with adaptive error elimination algorithm for robotic system by Wang Helin

Subjects: “…nonlinear optimal predictive control…”
Get full text

Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm by Chandragandhi S, Arvind C, Srihari K

Subjects: Get full text

Predictive modeling of adolescent suicidal behavior using machine learning: Key features and algorithmic insights by Priya Metri, Swetta Kukreja

“…Among these, Random Forest and SVM emerged as the most commonly used algorithms, featured in 35 % and 27 % of studies respectively. …”
Get full text

Predictors of Occupational Adaptation in Individuals With Parkinson’s Disease by Jafar Haj Ghani, Ghorban Taghizadeh, Akram Azad, Seyed Amir Hasan Habibi

Subjects: Get full text

Benchmarking Variants of Recursive Feature Elimination: Insights from Predictive Tasks in Education and Healthcare by Okan Bulut, Bin Tan, Elisabetta Mazzullo, Ali Syed

“…Originally developed as an effective feature selection method in healthcare predictive analytics, Recursive Feature Elimination (RFE) has gained increasing popularity in Educational Data Mining (EDM) due to its ability to handle high-dimensional data and support interpretable modeling. …”
Get full text

Machine Learning Applications for Predicting High-Cost Claims Using Insurance Data by Esmeralda Brati, Alma Braimllari, Ardit Gjeçi

“…This study aimed to empirically evaluate the performance of classification algorithms, including Logistic Regression, Decision Tree, Random Forest, XGBoost, K-Nearest Neighbors, Support Vector Machine, and Naïve Bayes to predict high insurance claims. …”
Get full text

AVS3 intra frame prediction parallel algorithm based on minimum CU cost by ZHANG Quan, WANG Shun, LIU Yangyi, DUAN Chang, PENG Bo

“…To address the time-consuming issue of audio video coding standard 3(AVS3) intra frame prediction, an intra frame prediction parallel algorithm based on the cost of the minimum coding unit (CU) was proposed. …”
Get full text

Sensor-Based Bermudagrass Yield Prediction Models Using Random Forest Algorithm in Oklahoma by Gabriel Camargo de Campos Jezus, Lucas Freires Abreu, Daryl Brian Arnall, Lucas Martins Stolerman, Alexandre Caldeira Rocateli

“…Current literature states that (i) machine learning algorithms are promising in agriculture, and (ii) proximity and multispectral sensors can be employed to predict biomass. …”
Get full text

Stability prediction of circular sliding failure soil slopes based on a genetic algorithm optimization of random forest algorithm by Shengming Hu, Yongfei Lu, Xuanchi Liu, Cheng Huang, Zhou Wang, Lei Huang, Weihang Zhang, Xiaoyang Li

Subjects: Get full text

A systematic literature review of diabetes prediction using metaheuristic algorithm-based feature selection: Algorithms and challenges method by Sirmayanti, Pulung Hendro PRASTYO, Mahyati, Farhan RAHMAN

“…To address the problems, we can employ metaheuristic algorithm-based feature selection. However, there has been limited research on metaheuristic algorithm-based feature selections for Diabetes prediction. …”
Get full text

Predicting Optimum Moisture Content by the individual and hybrid approach of machine learning by Yinghui Yang, Yahui Dai, Qunting Yang

“…Machine learning offers a promising alternative by enabling the creation of advanced predictive models and algorithms that can improve the accuracy and efficiency of OMC predictions compared to traditional empirical methods. …”
Get full text

Machine Learning Approaches for Predicting Employee Turnover: A Systematic Review by Hojat Talebi, Amid Khatibi Bardsiri, Vahid Khatibi Bardsiri

Subjects: Get full text

An Uncertainty-Aware Lane Change Motion Planning Algorithm Based on Probabilistic Trajectory Prediction Distribution by Zhiqiang Zhang, Lei Zhang, Mingqiang Wang, Cong Wang, Zhenpo Wang

Get full text

Analyzing Financial Stability by Predicting Bankruptcy Situations with Machine Learning by Mohd Naved, Ravi Kumar, Shaiku Saheb

“…Machine learning (ML) may help in bankruptcy prediction by analyzing massive quantities of historical financial data, identifying trends and anomalies that indicate trouble, and developing predictive models to estimate the possibility of default. …”
Get full text

Predictive algorithms and criminal justice: expectations, challenges and a particular view of the Spanish VioGén system by Pilar Martín Ríos

Get full text

Toward Sustainable Campus Energy Management: A Comprehensive Review of Energy Management, Predictive Algorithms, and Recommendations by Noor Islam Jasim, Saraswathy Shamini Gunasekaran, Nouar AlDahoul, Ali Najah Ahmed, Ahmed El-Shafie, Mohsen Sherif, Moamin A Mahmoud

“…The paper states that to facilitate energy efficiency and manage consumption, it is important to extract patterns of energy consumption by data modelling and predictive algorithms to achieve the ultimate goal of consumption recommending and advising. …”
Get full text

Comparing and Predicting Hepatic Encephalopathy Complications Using Random Forest Algorithm in Active Men by Bakhtyar Tartibian, Leila Fasihi, Rasoul Eslami, Ahmad Fasihi

“…Results: There was no significant difference in predicting encephalopathy complications by random forest algorithm between active and inactive men. …”
Get full text

Comparison and Prediction of Breast Cancer Using Discriminant Analysis Algorithm in Active and Inactive Women by Leila Fasihi, Hamid Agha-Alinejad, Reza Gharakhanlou, Francisco J. Amaro Gahete

Subjects: Get full text