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algorithm loss » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
loss function » cost function (Expand Search)
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm
Published 2023Subjects: Get full text
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”
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Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures
Published 2017“…In this paper, we trade off exact computation for enabling the use and study of more complex loss functions for coreference resolution. Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. …”
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Blood Glucose Regulation Modelling and Intelligent Control
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Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm
Published 2024“…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. …”
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Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia
Published 2023“…We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). Limma-based differential expression analysis reported the dysregulation of 61 proteins in the plasma of those with dementia compared with controls, and machine learning algorithms identified 17 stable diagnostic biomarkers that differentiated individuals with AUC = 0.98 ± 0.02. …”
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A new reactive power optimization algorithm
Published 2003“…A new implementation for the particle swarm algorithm has been applied. The objective function of the proposed algorithm is to minimize the system active power loss. …”
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Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling
Published 2017“…Aortic valve diseases are among the most common cardiovascular defects. Since a non-functioning valve results in disturbed blood flow conditions, the diagnosis of such defects is based on identification of stenosis via echocardiography. …”
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Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling
Published 2017“…Aortic valve diseases are among the most common cardiovascular defects. Since a non-functioning valve results in disturbed blood flow conditions, the diagnosis of such defects is based on identification of stenosis via echocardiography. …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”
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Android Malware Detection Using Machine Learning
Published 2024“…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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Defense against adversarial attacks: robust and efficient compressed optimized neural networks
Published 2024“…A cumulative updating loss function was employed for overall optimization, demonstrating remarkable superiority over traditional optimization techniques. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. For image datasets, we employ Multi-Level Autoencoders, consisting of Convolutional and Fully Connected Autoencoders. …”
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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network
Published 2024“…At the same time, the mean square error value serves as the loss function for the ANN model (i.e., the loss function values were 2.84 × 10<sup>−7</sup> and 6.40 × 10<sup>−7</sup>, respectively, for X1 and X2 loading conditions at 45° angle). …”
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Optimal shunt compensators at nonsinusoidal busbars
Published 1995“…This model was solved employing the penalty function approach and the golden Section Search algorithm for solving the linear load case. …”
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OPTIMAL SHUNT COMPENSATORS AT NON-SINUSOIDAL BUSBARS
Published 2020“…This model was solved employing the penalty function approach and the golden Section Search algorithm for solving the linear load case. …”
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