Results 11 to 20 of about 30,189 (295)
FE-RNN: A fuzzy embedded recurrent neural network for improving interpretability of underlying neural network [PDF]
Information SciencesDeep learning enables effective predictions. But deep structures face some challenges on human interpretability compared to conventional techniques, e.g., fuzzy inference systems. It motivates more research works to alleviate the black box nature of deep
Qi Cao, Chai Quek
exaly +3 more sources
ELMAN-RECURRENT NEURAL NETWORK FOR LOAD SHEDDING OPTIMIZATION
Jurnal Ilmiah SINERGI, 2020 Load shedding plays a key part in the avoidance of the power system outage. The frequency and voltage fluidity leads to the spread of a power system into sub-systems and leads to the outage as well as the severe breakdown of the system utility.
Widi Aribowo
doaj +3 more sources
Hanacaraka Javanese Handwriting Detection Using Recurrent Neural Network (RNN)
Jurnal Pendidikan MultimediaHanacaraka Javanese script is a valuable Indonesian cultural heritage, but its use has declined due to a lack of knowledge and ability to read and write the script.
Ichsan Nur Rachmad Yusuf +2 more
doaj +3 more sources
IEEE Access, 2020 This article presents two novel neural network models based on recurrent neural network (RNN) for radio frequency power amplifiers (RF PAs): instant gated recurrent neural network (IGRNN) model and instant gated implict recurrent neural network (IGIRNN ...
Gang Li +4 more
doaj +1 more source
Land, 2023 Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative samples used ...
Junjie Ji +4 more
doaj +1 more source
RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks
Advances in Neural Information Processing Systems 35, 2022 Published as a conference paper at NeurIPS ...
Leo Kozachkov +2 more
openaire +3 more sources
A Deep Neural Network Model for Speaker Identification
Applied Sciences, 2021 Speaker identification is a classification task which aims to identify a subject from a given time-series sequential data. Since the speech signal is a continuous one-dimensional time series, most of the current research methods are based on ...
Feng Ye, Jun Yang
doaj +1 more source
CDS risk premia forecasting with multi-featured deep RNNs: An application on BR[I]CS countries
Borsa Istanbul Review, 2023 Using state-of-the-art recurrent neural network architectures, this study attempts to predict credit default swap risk premia for BR[I]CS countries as accurately as possible.
Yasin Kutuk
doaj +1 more source
Prediction of PCR amplification from primer and template sequences using recurrent neural network
Scientific Reports, 2021 We have developed a novel method to predict the success of PCR amplification for a specific primer set and DNA template based on the relationship between the primer sequence and the template.
Kotetsu Kayama +7 more
doaj +1 more source
CAAI Transactions on Intelligence Technology, 2023 A variety of neural networks have been presented to deal with issues in deep learning in the last decades. Despite the prominent success achieved by the neural network, it still lacks theoretical guidance to design an efficient neural network model, and ...
Mei Liu +5 more
doaj +1 more source