Results 61 to 70 of about 139,430 (360)

Ensemble Machine Learning of Gradient Boosting (XGBoost, LightGBM, CatBoost) and Attention-Based CNN-LSTM for Harmful Algal Blooms Forecasting

Toxins, 2023
Harmful algal blooms (HABs) are a serious threat to ecosystems and human health. The accurate prediction of HABs is crucial for their proactive preparation and management. While mechanism-based numerical modeling, such as the Environmental Fluid Dynamics
Jung Min Ahn, Jungwook Kim, Kyunghyun Kim   +2 more
semanticscholar   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Tree Boosting Data Competitions with XGBoost [PDF]

, 2017
This Master's Degree Thesis objective is to provide understanding on how to approach a supervised learning predictive problem and illustrate it using a statistical/machine learning algorithm, Tree Boosting.
Bort Escabias, Carlos
core   +1 more source

Compact Multi-Class Boosted Trees

, 2017
Gradient boosted decision trees are a popular machine learning technique, in part because of their ability to give good accuracy with small models. We describe two extensions to the standard tree boosting algorithm designed to increase this advantage ...
Colthurst, Thomas, Haykal, Salem, Hendry, Gilbert, Ponomareva, Natalia, Radpour, Soroush   +4 more
core   +1 more source

A New Deep Learning-Based Methodology for Video Deepfake Detection Using XGBoost [PDF]

, 2021
Aya Abdelsalam Ismail, Marwa Elpeltagy, Mervat S. Zaki, Kamal A. ElDahshan   +3 more
openalex   +1 more source

Precise Control of Drug Release in Machine Learning‐Designed Antibody‐Eluting Implants for Postoperative Scarring Inhibition in Glaucoma

Advanced Healthcare Materials, EarlyView.
We developed a micro‐sized, biocompatible implant for postoperative sustained delivery of anti‐fibrotic antibodies in glaucoma surgery. Machine learning‐guided optimization of polymer composition, implant geometry, and porosity enabled precise control of drug release.
Mengqi Qin, Wenbing Jiang, Kai Xin Thong, Zeynep Ulker, Brihitejas Patel, Cynthia Yu‐Wai‐Man   +5 more
wiley   +1 more source

Tree-based Intelligent Intrusion Detection System in Internet of Vehicles

, 2019
The use of autonomous vehicles (AVs) is a promising technology in Intelligent Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything (V2X) technology enables communication among vehicles and other infrastructures ...
Hamieh, Ismail, Moubayed, Abdallah, Shami, Abdallah, Yang, Li   +3 more
core   +1 more source

Flood Susceptibility Assessment with Random Sampling Strategy in Ensemble Learning (RF and XGBoost)

Remote Sensing
Due to the complex interaction of urban and mountainous floods, assessing flood susceptibility in mountainous urban areas presents a challenging task in environmental research and risk analysis.
Hancheng Ren, Bo Pang, Ping Bai, Gang Zhao, Shu Liu, Yuanyuan Liu, Min Li   +6 more
semanticscholar   +1 more source

An Optimal House Price Prediction Algorithm: XGBoost [PDF]

Analytics
An accurate prediction of house prices is a fundamental requirement for various sectors, including real estate and mortgage lending. It is widely recognized that a property’s value is not solely determined by its physical attributes but is significantly ...
Hemlata Sharma, Hitesh Harsora, Bayode Ogunleye   +2 more
semanticscholar   +1 more source