Search Results - "Gradient-boosting algorithms"

Artificial Intelligence Techniques for Solar Irradiance and PV Modeling and Forecasting

“…Solar photovoltaic (PV) systems are pivotal and transformative technologies at the forefront of the global shift toward sustainable energy solutions. The…”
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Electroencephalography based classification of emotions associated with road traffic noise using Gradient boosting algorithm by Manohare, Manish, Rajasekar, E., Parida, Manoranjan

“…•A listening experiment is conducted with 14 participants who listened to 14 traffic noise stimuli.•EEG signals are recorded as a psychophysiological response…”
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Online comment‐based prediction of cosmetic ingredient's sensory irritation using gradient boosting algorithm by Jiang, Biao, Wang, Huijuan, Cheng, Li, Zi, Yusha, He, Congfen, Den, Yi‐Ann

“… Objective A gradient boosting algorithm is adopted in our context to integrate multisource of information including skin types, sensory response, and cosmetics ingredients to predict sensory irritation…”
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A Decision Support System For Early Stage Parkinson's Diagnosis from EEG Data Using Symbolic Mutual Information and KAC Features by Baki, Neslihan, Gürsel Özmen, Nurhan

“…Parkinson's disease (PD) is a serious neurological disease that is threatening the whole world population. The devolution of the neurons located in the…”
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Comparison of Machine Learning-based Approaches to Predict the Conversion to Alzheimer’s Disease from Mild Cognitive Impairment by Franciotti, Raffaella, Nardini, Davide, Russo, Mirella, Onofrj, Marco, Sensi, Stefano L.

“…– is far from being reached. In this study, we compared the different prognostic performances of three supervised ML algorithms fed with multimodal biomarkers of MCI subjects obtained…”
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Automatic Segmentation of Actigraphy Data Utilising Gradient Boosting Algorithm by Mikulec, Marek, Mekyska, Jiri, Sigmund, Jan, Galaz, Zoltan, Brabenec, Lubos, Moravkova, Ivona, Rektorova, Irena

“… with polysomnography (PSG). This study aims to introduce a new approach to sleep assessment that utilises the modelling of actigraphy data by a gradient boosting algorithm…”
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Improved Confidence-Interval Estimations Using Uncertainty Measure and Weighted Feature Decisions for Cuff-Less Blood-Pressure Measurements by Lee, Soojeong, Al-antari, Mugahed A., Joshi, Gyanendra Prasad

“… Thus, we proposed a method to obtain improved CIs for individual subjects by applying bootstrap and uncertainty methods using the cuff-less BP estimates of each subject obtained through GPR…”
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Significant of Gradient Boosting Algorithm in Data Management System by Hosen, Md Saikat, Amin, Ruhul

“… This study is aimed at delineating the significance of the gradient boosting algorithm in data management systems…”
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Development and validation of a multimodal deep learning framework for vascular cognitive impairment diagnosis by Fan, Fan, Song, Hao, Jiang, Jiu, He, Haoying, Sun, Dong, Xu, Zhipeng, Peng, Sisi, Zhang, Ran, Li, Tian, Cao, Jing, Xu, Juan, Peng, Xiaoxiang, Lei, Ming, He, Chu, Zhang, Junjian

“… Using these data, we developed a multimodal deep learning framework that combined the vision transformer and extreme gradient boosting algorithms…”
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Integrating Deep Learning with Electronic Health Records for Early Glaucoma Detection: A Multi-Dimensional Machine Learning Approach by Karimi, Alireza, Stanik, Ansel, Kozitza, Cooper, Chen, Aiyin

“…’ electronic health records (EHR). Three distinct machine learning classifiers, the Random Forest and Gradient Boosting algorithms, as well as the Sequential model from the Keras library of TensorFlow, were employed to conduct…”
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Activity classification using accelerometers and machine learning for complex construction worker activities by Sanhudo, Luís, Calvetti, Diego, Martins, João Poças, Ramos, Nuno M.M., Mêda, Pedro, Gonçalves, Miguel Chichorro, Sousa, Hipólito

“…Automated Construction worker activity classification has the potential to not only benefit the worker performance in terms of productivity and safety, but…”
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Comparison Between Statistical Model and Machine Learning Methods for Predicting the Risk of Renal Function Decline Using Routine Clinical Data in Health Screening by Cao, Xia, Lin, Yanhui, Yang, Binfang, Li, Ying, Zhou, Jiansong

“…) using routine clinical data. This retrospective cohort study includes datasets from 2166 subjects, aged 35-74 years old, provided by an adult health screening follow-up program between 2010 and 2020…”
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Development of Phenotyping Algorithms for the Identification of Organ Transplant Recipients: Cohort Study by Wheless, Lee, Baker, Laura, Edwards, LaVar, Anand, Nimay, Birdwell, Kelly, Hanlon, Allison, Chren, Mary-Margaret

“… We used Vanderbilt's deidentified version of its electronic health record database, which contains nearly 3 million subjects, to develop algorithms to identify OTRs…”
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SOLVING THE PROBLEM OF DETECTING PHISHING WEBSITES USING ENSEMBLE LEARNING MODELS by Kaibassova, Dinara, Nurtay, Margulan, Tau, Ardak, Kissina, Mira

“… Possible sources were examined in order to investigate the subject. Based on the collected information from previous studies, this study is devoted to solving the problem of detecting phishing websites using Ensemble Learning…”
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Development and Research of a Modified Gradient Boosting Method Effectiveness to Solve Applied Problems of Time-Series Forecasting by Fatkhulin, Timur, Leokhin, Yuri, Zanegin, Alexey, Rakhmatova, Aziza

“… The relevance of the work is due to the fact that the subject area under consideration is characterized by the presence of many different noises and anomalies in datasets…”
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Short term net load forecasting using computational intelligence techniques by Laouali, I. H., Italiano, N., Casaleiro, Â., Alvite, I., da Silva, N. P.

“…Net load forecasting has become increasingly complex due to the high penetration of renewables and evolving data subject to so-called concept drift, i.e…”
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Improved Alzheimer’s Disease Detection by MRI Using Multimodal Machine Learning Algorithms by Battineni, Gopi, Hossain, Mohmmad Amran, Chintalapudi, Nalini, Traini, Enea, Dhulipalla, Venkata Rao, Ramasamy, Mariappan, Amenta, Francesco

“… To predict the AD subject status, the MRI demographic information and pre-existing conditions of the patient…”
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Prediction of breath‐holding spells based on electrocardiographic parameters using machine‐learning model by Khalilian, Mohammad Reza, Tofighi, Saeed, Attar, Elham Zohur, Nikkhah, Ali, Hajipour, Mahmoud, Ghazavi, Mohammad, Samimi, Sahar

“…Background Breath‐holding spells (BHS) are common in infancy and early childhood and may appear like seizures. Factors such as autonomic dysfunction and iron…”
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Development of facial-skin temperature driven thermal comfort and sensation modeling for a futuristic application by Jia, Mengqi, Choi, Joon-Ho, Liu, Hanxun, Susman, Gideon

“…The human body is governed by the physiological thermoregulation principle of balancing the heat flux between the body itself and the ambient thermal…”
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Dynamic personalized human body energy expenditure: Prediction using time series forecasting LSTM models by Perez Cortes, Victoria M., Chatterjee, Arnab, Khovalyg, Dolaana

“…•Dynamic modeling of energy expenditure can capture transient thermoregulation and food intake effect.•LSTM networks promise high accuracy of time-series data…”
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