Hybrid neural network modeling and particle swarm optimization for improved ethanol production from cashew apple juice
Sign Up to like & getrecommendations! Published in 2020 at "Bioprocess and Biosystems Engineering"
DOI: 10.1007/s00449-020-02445-y
Abstract: A hybrid neural model (HNM) and particle swarm optimization (PSO) was used to optimize ethanol production by a flocculating yeast, grown on cashew apple juice. HNM was obtained by combining artificial neural network (ANN), which… read more here.
Keywords: hybrid neural; cashew apple; swarm optimization; particle swarm ... See more keywords
A unified technique for entropy enhancement based diabetic retinopathy detection using hybrid neural network.
Sign Up to like & getrecommendations! Published in 2022 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2022.105424
Abstract: In this paper, a unified technique for entropy enhancement-based diabetic retinopathy detection using a hybrid neural network is proposed for diagnosing diabetic retinopathy. Medical images play crucial roles in the diagnosis, but two images representing… read more here.
Keywords: neural network; diabetic retinopathy; entropy enhancement; hybrid neural ... See more keywords
Hybrid neural network based on novel audio feature for vehicle type identification
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-87399-1
Abstract: Due to the audio information of different types of vehicle models are distinct, the vehicle information can be identified by the audio signal of vehicle accurately. In real life, in order to determine the type… read more here.
Keywords: information; feature; vehicle; hybrid neural ... See more keywords
A hybrid neural network model based modelling methodology for the rubber bushing
Sign Up to like & getrecommendations! Published in 2021 at "Vehicle System Dynamics"
DOI: 10.1080/00423114.2021.1933090
Abstract: To fully consider the influences of the exciting frequency (0–20 Hz) and the environmental temperature (−50–20°C) on the dynamic characteristics of the rubber bushing in the railway vehicle, a hybr... read more here.
Keywords: model based; methodology; rubber bushing; hybrid neural ... See more keywords
Short-Term Load Forecasting Based on a Hybrid Neural Network and Phase Space Reconstruction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3154362
Abstract: Most current short-term load forecasting models have difficulty in simultaneously taking into account the time-series nature of load data, the non-linear characteristics, and the ineffectiveness of extracting potential high-dimensional features from historical series. To solve… read more here.
Keywords: network; term load; load; hybrid neural ... See more keywords
A Parallel Hybrid Neural Network With Integration of Spatial and Temporal Features for Remaining Useful Life Prediction in Prognostics
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3227956
Abstract: Prediction of remaining useful life (RUL) is an indispensable part of prognostics health management (PHM) in complex systems. Considering the parallel integration of the spatial and temporal features implicated in measurement data, this article proposes… read more here.
Keywords: neural network; network; prediction; spatial temporal ... See more keywords
SincNet-Based Hybrid Neural Network for Motor Imagery EEG Decoding
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2022.3156076
Abstract: It is difficult to identify optimal cut-off frequencies for filters used with the common spatial pattern (CSP) method in motor imagery (MI)-based brain-computer interfaces (BCIs). Most current studies choose filter cut-frequencies based on experience or… read more here.
Keywords: neural network; sincnet based; eeg; hybrid neural ... See more keywords
Stability analysis of hybrid neural networks with impulsive time window
Sign Up to like & getrecommendations! Published in 2017 at "International Journal of Biomathematics"
DOI: 10.1142/s1793524517500115
Abstract: The urgent problem with impulsive moments cannot be determined in advance brings new challenges beyond the conventional impulsive systems theory. In order to solve this problem, in this paper, a novel class of system with… read more here.
Keywords: time window; networks impulsive; neural networks; hybrid neural ... See more keywords
Hybrid neural networks in cyber physical system interface control systems
Sign Up to like & getrecommendations! Published in 2020 at "Bulletin of Electrical Engineering and Informatics"
DOI: 10.11591/eei.v9i3.1293
Abstract: The calculation and results of simulation of the magnetic control system for the spacecraft momentum are presented in the paper. The simulation includes an assessment of the reliability of calculating the Earth's magnetic field parameters,… read more here.
Keywords: system; control; hybrid neural; cyber physical ... See more keywords
Automated Software Vulnerability Detection Based on Hybrid Neural Network
Sign Up to like & getrecommendations! Published in 2021 at "Applied Sciences"
DOI: 10.3390/app11073201
Abstract: Vulnerabilities threaten the security of information systems. It is crucial to detect and patch vulnerabilities before attacks happen. However, existing vulnerability detection methods suffer from long-term dependency, out of vocabulary, bias towards global features or… read more here.
Keywords: neural network; hybrid neural; vulnerability detection; vulnerability ... See more keywords
A Depression Diagnosis Method Based on the Hybrid Neural Network and Attention Mechanism
Sign Up to like & getrecommendations! Published in 2022 at "Brain Sciences"
DOI: 10.3390/brainsci12070834
Abstract: Depression is a common but easily misdiagnosed disease when using a self-assessment scale. Electroencephalograms (EEGs) provide an important reference and objective basis for the identification and diagnosis of depression. In order to improve the accuracy… read more here.
Keywords: attention mechanism; neural network; network; diagnosis ... See more keywords