Research progress on neural network algorithms for mixed gas detection in coal mines
Gong-kuang zidonghua, 2023 When coal mine gas sensors are used for mixed gas detection, there is cross interference between measurement signals. It is difficult to ensure detection accuracy.
JIAO Mingzhi +4 more
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Breast Cancer Disease Prediction With Recurrent Neural Networks (RNN) [PDF]
International Journal of Industrial Engineering and Production Research, 2020 Cancer is a consortium of diseases which comprises abnormal increase in cells growth by having potential to occupy and attack the entire body. According to study breast cancer is the most likely occurs in the women and which became the second biggest ...
sangapu venkata appaji +3 more
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THE COMPARISON OF ARIMA AND RNN FOR FORECASTING GOLD FUTURES CLOSING PRICES
BarekengIn the financial markets, accurately forecasting the closing prices of gold futures is crucial for investors and analysts. Traditional methods like ARIMA (Autoregressive Integrated Moving Average) have been widely used for this purpose, particularly for ...
Windy Ayu Pratiwi +4 more
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Modelling Time Series Data for Stock Prices Prediction Using Bidirectional Long Short-Term Memory
KnowbaseThe dynamic nature of stock markets, characterized by intricate patterns and sudden fluctuations, poses significant challenges to accurate price prediction. Traditional analytical methods are often unable to capture this complexity. This requires the use
Yenie Syukriyah, Adi Purnama
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Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition
, 2018 Recurrent Neural Networks (RNNs) are powerful sequence modeling tools. However, when dealing with high dimensional inputs, the training of RNNs becomes computational expensive due to the large number of model parameters.
Chen, Di +6 more
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Time-Series Forecasting of the Pazarcık Earthquake Using LSTM, Transformer and RNN Models
Gazi Üniversitesi Fen Bilimleri DergisiThe Earth's internal structure and mitigating seismic hazards are very important for understanding for earthquake prediction and seismic wave analysis.
Seda Şahin , Emine Çankaya
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Improved Recurrent Neural Network based BP Decoding Algorithm for Polar Codes
Guangtongxin yanjiu, 2022 In recent years, the emerging Deep Learning (DL) technology has made progress in the field of decoding. Current polar code neural network decoder has faster convergence speed and better Bit Error Rate (BER) performance than Belief Propagation (BP ...
Xue-lu DENG, Da-qin PENG
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What is the Role of Recurrent Neural Networks (RNNs) in an Image Caption Generator?
, 2017 In neural image captioning systems, a recurrent neural network (RNN) is typically viewed as the primary `generation' component. This view suggests that the image features should be `injected' into the RNN.
Camilleri, Kenneth P. +2 more
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Sequence Prediction Using Spectral RNNs [PDF]
, 2020 Source code available at https://github.com/v0lta/Spectral ...
Wolter, Moritz +2 more
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Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
, 2014 In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixed-length vector representation, and the other decodes the ...
Bahdanau, Dzmitry +6 more
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