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   Articles with "dnn" as a keyword



High spectrum compression scheme based on DNN post equalization for multiband quadrature dual‐quaternary coded FTN CAP 49QAM signals in visible light communication system

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recommendations! Published in 2020 at "Microwave and Optical Technology Letters"

DOI: 10.1002/mop.32412

Abstract: In this article, we utilize the Faster‐Than‐Nyquist (FTN) mechanism combined with the deep neural network (DNN) nonlinear post‐equalization scheme to achieve spectrum compression of the multiband carrierless amplitude phase (CAP) signal in the case of… read more here.

Keywords: system; dnn; ftn cap; spectrum compression ... See more keywords

A supervised deep neural network approach with standardized targets for enhanced accuracy of IVIM parameter estimation from multi‐SNR images

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recommendations! Published in 2022 at "Nmr in Biomedicine"

DOI: 10.1002/nbm.4774

Abstract: Extraction of intravoxel incoherent motion (IVIM) parameters from noisy diffusion‐weighted (DW) images using a biexponential fitting model is computationally challenging, and the reliability of the estimated perfusion‐related quantities represents a limitation of this technique. Artificial… read more here.

Keywords: accuracy; deep neural; dnn; ivim ... See more keywords

An automatic hyperparameter optimization DNN model for precipitation prediction

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recommendations! Published in 2021 at "Applied Intelligence"

DOI: 10.1007/s10489-021-02507-y

Abstract: Deep neural networks (DNN) have gained remarkable success on many rainfall predictions tasks in recent years. However, the performance of DNN highly relies upon the hyperparameter setting. In order to design DNNs with the best… read more here.

Keywords: dnn; precipitation; hyperparameter optimization; hyperparameter ... See more keywords

SenDemonNet: sentiment analysis for demonetization tweets using heuristic deep neural network

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recommendations! Published in 2022 at "Multimedia Tools and Applications"

DOI: 10.1007/s11042-022-11929-w

Abstract: Sentiment analysis is one of the efficient models for extracting opinion mining with identification and classification from unstructured text data such as product reviews or microblogs. It is used to gain feedback from political campaigns,… read more here.

Keywords: analysis; dnn; demonetization; sentiment analysis ... See more keywords

Trustworthy DNN partition for blockchain-enabled digital twin in wireless IIoT networks

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recommendations! Published in 2024 at "Science China Information Sciences"

DOI: 10.1007/s11432-024-4159-2

Abstract: Digital twin (DT) has emerged as a promising solution to enhance manufacturing efficiency in industrial Internet of Things (IIoT) networks. To promote the efficiency and trustworthiness of DT for wireless IIoT networks, we propose a… read more here.

Keywords: reputation; dnn; iiot networks; dnn inference ... See more keywords

Application of machine learning for filtered density function closure in MILD combustion

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recommendations! Published in 2021 at "Combustion and Flame"

DOI: 10.1016/j.combustflame.2020.10.043

Abstract: Abstract A machine learning algorithm, the deep neural network (DNN) 1 , is trained using a comprehensive direct numerical simulation (DNS) dataset to predict joint filtered density functions (FDFs) of mixture fraction and reaction progress… read more here.

Keywords: machine learning; dnn; combustion; mild combustion ... See more keywords

Application of deep neural network (DNN) for experimental liquid-liquid equilibrium data of water + butyric acid + 5-methyl-2-hexanone ternary systems

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recommendations! Published in 2021 at "Fluid Phase Equilibria"

DOI: 10.1016/j.fluid.2021.113094

Abstract: Abstract LLE data are important for simulation and design of extraction equipment. In this study, deep neural network (DNN) structure was proposed for modelling of the ternary liquid-liquid equilibrium (LLE). LLE data of (water +… read more here.

Keywords: neural network; dnn; liquid liquid; deep neural ... See more keywords

Deep neural networks for choice analysis: A statistical learning theory perspective

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recommendations! Published in 2021 at "Transportation Research Part B: Methodological"

DOI: 10.1016/j.trb.2021.03.011

Abstract: While researchers increasingly use deep neural networks (DNN) to analyze individual choices, overfitting and interpretability issues remain as obstacles in theory and practice. By using statistical learning theory, this study presents a framework to examine… read more here.

Keywords: learning theory; dnn; choice analysis; choice ... See more keywords

Predicting Solute Descriptors for Organic Chemicals by a Deep Neural Network (DNN) Using Basic Chemical Structures and a Surrogate Metric.

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recommendations! Published in 2022 at "Environmental science & technology"

DOI: 10.1021/acs.est.1c05398

Abstract: Solute descriptors have been widely used to model chemical transfer processes through poly-parameter linear free energy relationships (pp-LFERs); however, there are still substantial difficulties in obtaining these descriptors accurately and quickly for new organic chemicals.… read more here.

Keywords: surrogate metric; lfer descriptors; organic chemicals; dnn ... See more keywords

Enhancing the Performance of Global Optimization of Platinum Cluster Structures by Transfer Learning in a Deep Neural Network.

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recommendations! Published in 2023 at "Journal of chemical theory and computation"

DOI: 10.1021/acs.jctc.2c00923

Abstract: The global optimization of metal cluster structures is an important research field. The traditional deep neural network (T-DNN) global optimization method is a good way to find out the global minimum (GM) of metal cluster… read more here.

Keywords: dnn; global optimization; dnn method; cluster ... See more keywords

Comparative assessment of standalone and hybrid deep neural networks for modeling daily pan evaporation in a semi-arid environment

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-05985-z

Abstract: Evaporation represents a fundamental hydrological cycle process that demands dependable methods to quantify its fluctuation to ascertain sustainable agriculture, irrigation systems, and overall water resource management. Meteorological variables such as relative humidity, temperature, wind speed,… read more here.

Keywords: semi arid; evaporation semi; evaporation; dnn ... See more keywords