Devdiscourse

Next-gen AI biosensors promise faster, smarter pandemic surveillance

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
INSPIRE

QSVM-QNN: Quantum Support Vector Machine Based Quantum Neural Network Learning Algorithm for Brain-Computer Interfacing Systems

A brain-computer interface (BCI) system enables direct communication between the brain and external devices, offering significant potential for assistive technologies and advanced human-computer ...
Scientific Research Publishing

Hybrid Software Model for Defect Detection and Cost Evaluation Using Support Vector Machine Algorithm ()

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...
Scientific Research Publishing

Yang, H., Chan, L. and King, I. (2002) Support Vector Machine Regression for Volatile Stock Market Prediction. In: Yin, H., Allinson, N., Freeman, R., Keane, J. and Hubbard, S ...

ABSTRACT: Deep learning plays a vital role in real-life applications, for example object identification, human face recognition, speech recognition, biometrics identification, and short and long-term ...
IEEE

Support Vector Machine Regression Optimised by Genetic Algorithms for Calculating the Ageing Population

Abstract: The aging problem has an increasing impact on China's economy, employment, and medical care, so it is important to make accurate predictions of the aging population. In this paper, we use ...