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developing based » developing a (Expand Search), developing 21st (Expand Search)
could algorithm » mould algorithm (Expand Search), carlo algorithm (Expand Search), colony algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
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521
Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma
Published 2019“…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …”
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522
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523
Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features
Published 2024“…<p dir="ltr">Stress recognition, particularly using machine learning (ML) with physiological data such as heart rate variability (HRV), holds promise for mental health interventions. …”
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524
A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
Published 2023“…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …”
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masterThesis -
525
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526
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527
EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. Lastly, the emotion of each subject is represented using the histogram of the vocabulary set collected from the raw-feature of a single channel. …”
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528
Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
Published 2022“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”
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529
Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network
Published 2020“…The developed model can be used to forecast the CMP as a function of operating temperature, the substrate composition, and chemical dose, and can be used for scaling-up and cost analysis purposes.…”
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530
A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security
Published 2023“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”
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531
Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria
Published 2020“…This study highlighted the role that solar PV-based HRESs could play in the sustainable electricity supply in rural areas of sub-Saharan Africa.…”
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532
Intelligent route to design efficient CO<sub>2</sub> reduction electrocatalysts using ANFIS optimized by GA and PSO
Published 2022“…Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. …”
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533
Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context
Published 0024“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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534
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535
Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles
Published 2024“…The MLNN observer, employing a modified back-propagation algorithm, is used for the quadrotor’s state estimation. …”
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536
Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
Published 2025“…Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”
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537
Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series
Published 2013Get full text
doctoralThesis -
538
Methods for system-on-chip test design, scheduling and optimization. (c2006)
Published 2006Get full text
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masterThesis -
539
Could Petrol Stations Play a Key Role in Transportation Electrification? A GIS-Based Coverage Maximization of Fast EV Chargers in Urban Environment
Published 2022“…The spatial optimization problem is solved using a linear-programming relaxation based MCLP algorithm developed in Python. …”
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540
Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet
Published 2025“…The model’s hyperparameters are optimized using an Enhanced Firefly Algorithm (EFA). The model performs a time series analysis to identify daily, weekly, monthly, and seasonal patterns in EV charging demand. …”