Results 41 to 50 of about 33,486 (254)

Advanced forecasting of building energy loads with XGBoost and metaheuristic algorithms integration

Energy Storage and Saving
Accurate forecasting of cooling and heating loads in buildings is vital for effective energy management, cost efficiency, and environmental sustainability.
Zuriani Mustaffa, Mohd Herwan Sulaiman
doaj   +1 more source

Application of XGBoost Algorithm in Fingerprinting Localisation Task

, 2017
An Indoor Positioning System (IPS) issues regression and classification challenges in form of an horizontal localisation and a floor detection. We propose to apply the XGBoost algorithm for both tasks. The algorithm uses vectors of Received Signal Strengths from Wi–Fi access points to map the obtained fingerprints into horizontal coordinates and a ...
Marcin Luckner, Bartosz Topolski, Magdalena Mazurek   +2 more
openaire   +1 more source

Thalamo‐Lesional Connectivity Signatures of Bilateral Tonic–Clonic Seizures in Focal Cortical Dysplasia‐Related Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie, Xiaotong Li, Venkata Sita Priyanka Illapani, Leigh N. Sepeta, Jason Schroeder, Chima O. Oluigbo, Madison M. Berl, William D. Gaillard, Nathan T. Cohen   +8 more
wiley   +1 more source

Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning

Cejing jishu
The lithology of the first member of the Maokou formation in the Middle Permian of Central Sichuan is complex and the longitudinal variation is large. There are many influencing factors and difficulty in the prediction of total organic carbon content, so
TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng   +5 more
doaj   +1 more source

Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu, Jie‐Jie Li, Jing Jing, Jin‐Xi Lin, Xia Meng, Yong Jiang, Yong‐Jun Wang, Hong‐Qiu Gu   +7 more
wiley   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Study on real-time prediction and warning technology for negative acceleration flight test of civil airplanes

Xibei Gongye Daxue Xuebao
The flight test of modern civil aircraft verifies the limits of aircraft design performance through a series of rigorous flight tests. Flight test mission is characterized by high risk and complex technology.
MI Yi, LI Aijun, WEN Yajun, FAN Zhipeng, HU Xuesong   +4 more
doaj   +1 more source

Detection of Parkinson’s Disease Using XGBOOST Algorithm

International Journal for Research in Applied Science and Engineering Technology, 2022
Abstract: PREDICTING PARKINSON’S DISEASE using XGBOOST ALGORITHM. In this project we will be using python to build a model using which we can accurately detect the presence of Parkinson’s disease in one’s body. XGBOOST algorithm is a technique for regression and classification problems. It produces a prediction model in form of a decision tree. Data is
Sanika Narayanpethkar, M. Rishitha, S. Chandana, Dr. T. Vijaya Saradhi   +3 more
openaire   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source