Suchergebnisse - Applications and Simulation Support Systems General Terms Algorithms

Short-term wind speed prediction model based on long short-term memory network with feature extraction von Tian, Zhongda, Yu, Xiyan, Feng, Guokui

“… 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 von Hussien, Aseel, Maksoud, Aref, Al-Dahhan, Aisha, Abdeen, Ahmed, Baker, Thar

“… 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 von Malekpour, Mohammad Mahdi, Ahmadi, Mohammad Mehdi, Gugliotta, Marcello, Tabari, Mahmoud Mohammad Rezapour, Qaderi, Kourosh

“… 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 von Subrahmanya, N., Shin, Y.C.

“… 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 von Liu, Wei, Liu, Qian, Li, Yulin

“… 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 von Alexandre Teixeira, César, Direito, Bruno, Bandarabadi, Mojtaba, Le Van Quyen, Michel, Valderrama, Mario, Schelter, Bjoern, Schulze-Bonhage, Andreas, Navarro, Vincent, Sales, Francisco, Dourado, António

“… 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 von Holm, Lene Berge, Lurås, Hilde, Dahl, Fredrik A

“… 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 von Hussain, Dostdar, Khan, Aftab Ahmed

“… ), 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 von Igwebuike, Ndubuisi, Ajayi, Moyinoluwa, Okolie, Chukwuma, Kanyerere, Thokozani, Halihan, Todd

“… 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 von Kosakovsky Pond, Sergei L., Posada, David, Gravenor, Michael B., Woelk, Christopher H., Frost, Simon D.W.

“… : 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 von Amirajlo, Poorya, Hassani, Hossein, Beiranvand Pour, Amin, Habibkhah, Narges

“… 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 von Liu, Xin, Zheng, Yuanjin, Phyu, Myint Wai, Zhao, Bin, Je, Minkyu, Yuan, Xiaojun

“… , 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 von Tamayo, Daniel, Cranmer, Miles, Hadden, Samuel, Rein, Hanno, Battaglia, Peter, Obertas, Alysa, Armitage, Philip J, Ho, Shirley, Spergel, David N, Gilbertson, Christian, Hussain, Naireen, Silburt, Ari, Jontof-Hutter, Daniel, Menou, Kristen

“… ] 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 von Shen, Zi-yi, Ban, Wen-chao

“… ),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 von Wang, Yan, Zhou, Yuqing

“… 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 von Zhou, Yanxiang, Liepe, Juliane, Sheng, Xia, Stumpf, Michael P. H., Barnes, Chris

“… 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 von Haghbin, Masoud, Sharafati, Ahmad, Motta, Davide

“… 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 von Qiu, Siyu, Liang, Ruiting, Wang, Yifu, Luo, Mi, Sun, Yujun

“… -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 von Scipioni, Lorenzo, Rossetta, Alessandro, Tedeschi, Giulia, Gratton, Enrico

“… 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 von Niknam, Azar, Zare, Hasan Khademi, Hosseininasab, Hassan, Mostafaeipour, Ali

“… 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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