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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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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation
Published 2024“…Effective and reliable assessment methods are required to accurately classify and estimate brain age. In this study, a brain age classification and estimation framework is proposed using structural magnetic resonance imaging (sMRI) scans, a 3-D convolutional neural network (3-D-CNN), and a kernel ridge regression-based random vector functional link (KRR-RVFL) network. …”
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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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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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Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier
Published 2023“…Earlier diagnosis of ASD from brain image is necessary for reducing the effect of disorder. …”
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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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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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A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance
Published 2024“…Hence, in this study, deep learning algorithms, such as VGG16, EfficientNetB4, and ResNet, are utilized to diagnose various diseases, such as Alzheimer's, brain tumors, skin diseases, and lung diseases. …”
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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). …”