Výsledky vyhledávání - Applications and Simulation Support Systems General Terms Algorithms
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Short-term wind speed prediction model based on long short-term memory network with feature extraction
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2025Vydáno v Earth science informatics (01.04.2025)“… Firstly, for reducing the uncertainty and complexity of short-term wind speed, data cluster is carried out by K-means clustering algorithm…”
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Machine learning model for predicting long-term energy consumption in buildings
ISSN: 2730-7239, 2730-7239Vydáno: Cham Springer International Publishing 01.12.2025Vydáno v Discover Internet of things (01.12.2025)“… Therefore, the study objective is to investigate the utilazation of machine learning algorithm to predict long-term energy consumption in buildings sector, aiming to improve sustainable design…”
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Estimation of suspended sediment load utilizing a super-optimized deep learning approach informed by the red fox optimization algorithm
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2025Vydáno v Earth science informatics (01.03.2025)“… In this study, we employed the Long Short-Term Memory (LSTM) model to estimate the suspended sediment concentration in the Mississippi River, United States of America…”
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Sparse Multiple Kernel Learning for Signal Processing Applications
ISSN: 0162-8828, 1939-3539, 1939-3539Vydáno: Los Alamitos, CA IEEE 01.05.2010Vydáno v IEEE transactions on pattern analysis and machine intelligence (01.05.2010)“…In many signal processing applications, grouping of features during model development and the selection of a small number of relevant groups can be useful to improve the interpretability of the learned parameters…”
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Ultra-short-term photovoltaic power prediction based on modal reconstruction and BiLSTM-CNN-Attention model
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2024Vydáno v Earth science informatics (01.06.2024)“…Accurate ultra-short-term photovoltaic (PV) power prediction is crucial for ensuring the power…”
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Epileptic seizure predictors based on computational intelligence techniques: A comparative study with 278 patients
ISSN: 0169-2607, 1872-7565, 1872-7565Vydáno: Kidlington Elsevier Ireland Ltd 01.05.2014Vydáno v Computer methods and programs in biomedicine (01.05.2014)“…The ability of computational intelligence methods to predict epileptic seizures is evaluated in long-term EEG recordings of 278 patients suffering from pharmaco-resistant partial epilepsy, also known…”
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Improving hospital bed utilisation through simulation and optimisation: with application to a 40% increase in patient volume in a Norwegian General Hospital
ISSN: 1872-8243, 1386-5056, 1872-8243Vydáno: Ireland 01.02.2013Vydáno v International journal of medical informatics (Shannon, Ireland) (01.02.2013)“… We present a generic discrete event simulation model of patient flow through the wards of a hospital…”
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Machine learning techniques for monthly river flow forecasting of Hunza River, Pakistan
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2020Vydáno v Earth science informatics (01.09.2020)“…), support vector regression (SVR), and random forest (RF), are explored to forecast Hunza river flow in Pakistan using in-situ dataset for the period from 1962 to 2008…”
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Application of machine learning and deep learning for predicting groundwater levels in the West Coast Aquifer System, South Africa
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2025Vydáno v Earth science informatics (01.01.2025)“…Groundwater models are valuable tools to quantify the response of groundwater level to hydrological stresses induced by climate variability and groundwater…”
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GARD: a genetic algorithm for recombination detection
ISSN: 1367-4803, 1367-4811, 1460-2059, 1367-4811Vydáno: Oxford Oxford University Press 15.12.2006Vydáno v Bioinformatics (15.12.2006)“…: We developed a likelihood-based model selection procedure that uses a genetic algorithm to search multiple sequence alignments for evidence of recombination breakpoints and identify putative recombinant sequences…”
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Detection of multivariate geochemical anomalies using machine learning (ML) algorithms in Dehaq Pb-Zn mineralization, Sanandaj-Sirjan zone, Isfahan, Iran
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2025Vydáno v Earth science informatics (01.01.2025)“… Regression-based machine learning algorithms such as Isolation Forest (IF) and One-Class Support Vector Machine (OCSVM…”
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Multiple Functional ECG Signal is Processing for Wearable Applications of Long-Term Cardiac Monitoring
ISSN: 0018-9294, 1558-2531, 1558-2531Vydáno: New York, NY IEEE 01.02.2011Vydáno v IEEE transactions on biomedical engineering (01.02.2011)“…, and is highly suitable for wearable applications of long-term cardiac monitoring…”
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Predicting the long-term stability of compact multiplanet systems
ISSN: 1091-6490, 1091-6490Vydáno: United States 04.08.2020Vydáno v Proceedings of the National Academy of Sciences - PNAS (04.08.2020)“…] orbits, thus achieving speed-ups of up to [Formula: see text] over full simulations. This computationally opens up the stability-constrained characterization of multiplanet systems…”
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Machine learning model combined with CEEMDAN algorithm for monthly precipitation prediction
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2023Vydáno v Earth science informatics (01.06.2023)“…),a support vector machine (SVM) and the long short-term memory (LSTM) neural network. The CEEMDAN algorithm is first used to decompose the precipitation time series data…”
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Sparrow search algorithm optimized LSTM model for CSI-based indoor localization
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2025Vydáno v Earth science informatics (01.01.2025)“… Additionally, it supports various advanced positioning algorithms, making it suitable for complex indoor environments and enabling real-time precise positioning…”
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GPU accelerated biochemical network simulation
ISSN: 1367-4803, 1367-4811, 1367-4811, 1460-2059Vydáno: Oxford Oxford University Press 15.03.2011Vydáno v Bioinformatics (15.03.2011)“…Motivation: Mathematical modelling is central to systems and synthetic biology. Using simulations to calculate statistics or to explore parameter space is a common means for analysing these models and can be computationally intensive…”
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Prediction of channel sinuosity in perennial rivers using Bayesian Mutual Information theory and support vector regression coupled with meta-heuristic algorithms
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021Vydáno v Earth science informatics (01.12.2021)“…Support Vector Regression (SVR) combined with Invasive Weeds Optimization (IWO), standalone SVR, and Radial Basis Function Neural Networks are applied to estimate channel sinuosity in perennial rivers…”
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Comparative analysis of machine learning algorithms and statistical models for predicting crown width of Larix olgensis
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2022Vydáno v Earth science informatics (01.12.2022)“…-NearestNeighbors, the Random Forest, the Gradient Boosting Decision Tree, the Support Vector Regression, the Voting…”
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Phasor S-FLIM: a new paradigm for fast and robust spectral fluorescence lifetime imaging
ISSN: 1548-7091, 1548-7105, 1548-7105Vydáno: United States Nature Publishing Group 01.05.2021Vydáno v Nature methods (01.05.2021)“… However, their combination is typically inefficient and slow in terms of acquisition and processing…”
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A hybrid approach combining the multi-dimensional time series k-means algorithm and long short-term memory networks to predict the monthly water demand according to the uncertainty in the dataset
ISSN: 1865-0473, 1865-0481Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2023Vydáno v Earth science informatics (01.06.2023)“…An authentic water consumption forecast is an auxiliary tool to support the management of the water supply and demand in urban areas…”
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