Ensemble long short-term memory (EnLSTM) network

04/26/2020
by   Yuntian Chen, et al.
0

In this study, we propose an ensemble long short-term memory (EnLSTM) network, which can be trained on a small dataset and process sequential data. The EnLSTM is built by combining the ensemble neural network (ENN) and the cascaded long short-term memory (C-LSTM) network to leverage their complementary strengths. In order to resolve the issues of over-convergence and disturbance compensation associated with training failure owing to the nature of small-data problems, model parameter perturbation and high-fidelity observation perturbation methods are introduced. The EnLSTM is compared with commonly-used models on a published dataset, and proven to be the state-of-the-art model in generating well logs with a mean-square-error (MSE) reduction of 34 drilling are generated based on logging-while-drilling (LWD) data. The EnLSTM is capable to reduce cost and save time in practice.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

10/10/2019

Transportation Mode Classification from Smartphone Sensors via a Long-Short-Term-Memory Network

This article introduces the architecture of a Long-Short-Term Memory net...
05/06/2019

RSL19BD at DBDC4: Ensemble of Decision Tree-based and LSTM-based Models

RSL19BD (Waseda University Sakai Laboratory) participated in the Fourth ...
06/12/2018

Knowledge Amalgam: Generating Jokes and Quotes Together

Generating humor and quotes are very challenging problems in the field o...
07/28/2021

Estimating Respiratory Rate From Breath Audio Obtained Through Wearable Microphones

Respiratory rate (RR) is a clinical metric used to assess overall health...
08/09/2017

Tikhonov Regularization for Long Short-Term Memory Networks

It is a well-known fact that adding noise to the input data often improv...
12/23/2017

An Approximate Bayesian Long Short-Term Memory Algorithm for Outlier Detection

Long Short-Term Memory networks trained with gradient descent and back-p...
07/20/2017

Prolongation of SMAP to Spatio-temporally Seamless Coverage of Continental US Using a Deep Learning Neural Network

The Soil Moisture Active Passive (SMAP) mission has delivered valuable s...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.