Questions tagged [time-series]

For questions related to time series analysis or forecasting in the context of AI and, in particular, ML.

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25 views

Why do we use a delay when feeding our input data to the echo state network?

I'm new to working with neural networks and have recently began implementing neural networks for time series forecasting in some of my work. I've been particularly using Echo State Networks and have ...
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9 views

Is there a difference between using 1d conv layers and 2d conv layers with kernel with size of 1 along other than time dimension?

Let's assume I use convolutional networks for time-series prediction. Data I feed to the network have 1 channel depth, height of number of periods and number of features is the width, so the frame ...
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1answer
73 views

What are modern state-of-the-art solutions in prediction of time-series?

I wanted to ask you about the newest achievements in time series analysis (mostly prediction). What state-of-the-art solutions (as in frameworks, papers, related projects) do you know that can be used ...
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1answer
57 views

What method to identify markers in data series via machine learning

I have data that is collected from several different instruments simultaneously that is generally analyzed on a location-by-location basis. A skilled interpreter can identify "markers" in the data ...
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1answer
16 views

Inner working of Bidirectional RNNs

I'm trying to understand how Bidirectional RNNs work. Specifically, I want to know whether a single cell is used with different states, or two different cells are used, each having independent ...
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0answers
28 views

How to predict an event (or action) based on a window of time-series measurements?

I have an input vector $X$, which contains a series of measurements within a period, e.g. 100 measurements in 1 sec. The goal is to predict an event, let's say, moving forward, backward or static. I ...
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23 views

Model for supervised sequence classification task

The Problem I am currently working on a sequence classification problem I try to solve with machine learning. The target variable is the current state of a system. This target variable is following a ...
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0answers
34 views

Should the RL agent be trained in an environment with real-world data or with a synthetic model?

I want to train a reinforcement learning agent in an environment with parameters (for example, the wind speed, sun irradiation, etc.) that change over time. I have recorded a limited amount of data ...
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3answers
71 views

How to predict time series with accuracy?

I am trying to predict Forex time series. The nature of the market is that 80% of the time the price can not be predicted, but in 20% of the time it can be. For example, if the price drops down very ...
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17 views

What's the best method to predict/generate signal from one sensor (source) to signal from another another (target)?

I was wondering what is the best method out there to find relationship between two 1D signals so that I can predict/generate one (source) from the other (target). For example, let's say that in ...
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10 views

How to handle multiscale time series for DNN?

I have a time-series signal with data sampled every minute. I've made different scales of the original signal like 30 minutes, 1 hour and ... . Now because the lengths of these signals are different I'...
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1answer
29 views

time-series prediction : loss going down, then stagnates with very high variance

I am trying to design a model based on LSTM cells to do time-series prediction. The ouput value is an integer in [0,13]. I have noticed that one-hot encoding it and ...
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16 views

RNN/LSTM with a large amounts of data

I have sequence data that's quite large - 4x65k per sample. I'm interested in doing classification problems. The number of classes is moderate - ~27 or so What is the suggestion for dealing with this ...
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0answers
9 views

Generation of realistic real-valued sequences using Wasserstein GAN fails

My goal is to generate artificial sequences of real-valued data (e.g. time series) with GANs. Starting simple I tried to generate realistic sine-waves using a Wasserstein GAN. But even on this simple ...
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1answer
21 views

Convert input dataset given in hex addresses to int

I have created an LSTM Neural Network which take as input the following format in an .csv file ...
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1answer
50 views

What's the best architecture for time series prediction with a long dataset?

I have to build a neural network without any architecture limitations which have to predict the next value of a time series. The dataset is composed of 400.000 values, which are given in hex format. ...
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1answer
26 views

Predicting a day's data

I have a dataset containing timestamp and temperature. For each day, I have 1440 values viz., I have data for every minute of that day(60minutes * 24hrs = 1440). The Dataset looks like this: As an ...
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0answers
32 views

How to exploit translational symmetry for extrapolation in video generation using machine learning

I'll try to rephrase my problem in the context of video processing. Imagine that initial frame of video has some translational symmetry. The frame evolves according to an update rule. I generate a ...
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2answers
116 views

Image vs Non-Image Data in CNN

When using CNN on non-image(times series) data prediction, what are some constraints or things to look out for as compared to image data? To be more precise, I ...
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0answers
14 views

Deep Learning on time series tabular data

In this new book release, at the top of page 51 the authors mention that to do deep learning on time series tabular data the developer should structure the tensors such that the channels represent the ...
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1answer
36 views

Can non-sequential deep learning models outperform sequential models in time series forecasting?

Can a CNN (or other non-sequential deep learning models) outperform LSTM (or other sequential models) in time series data? I know this question is not very specific, but I experienced this when ...
2
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1answer
39 views

Feature extraction timeseries, model compatibility

I've got a timeseries with sensor data (e.g. accelerometer and gyroscope). I now want to extract the activity out of it (e.g. walking, standing, driving, ...). I Followed this Jupyter Notebook. But ...
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1answer
281 views

What is the “semantic level”?

I am reading the paper Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction (2018) by Yunzhe Tao et al. In this paper, they use several times the expression "semantic ...
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1answer
199 views

ValueError: Error when checking target: expected dense_3 to have shape (1,) but got array with shape (2,)

I am trying to build a CNN model on Keras. The data has a dimension of 921 rows × 10000 columns. Here is the code: ...
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0answers
23 views

Choosing neural network output for prediction (regression) of a dynamical system

I’m trying to train a neural network to approximate the output of a dynamical system $dy/dt=f\left(y(t), u(t) \right)$, namely, given $y(0)$ and $u(t_i), i=1,2...N$ I want the network to predict $y(...
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1answer
43 views

How can I test my trained network on the next unavailable hour?

I have data of 695 hours. I use the first 694 hours to train the network and I use 695th hour to validate it. Now my goal is to predict the next hour. How I can use my trained network to predict the ...
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0answers
15 views

What's the correct approach to standardise data from a time-series used for LSTM neural network predictions?

This question discusses the same model mentioned in Why is the value range of my LSTM model's prediction different from my test labels? Repeating the main points: I am using LSTM to do time-...
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1answer
87 views

Is it possible to use the GPT-2 model for time-series data prediction?

Is it possible and how trivial (or not) might it be (if possible) to retrain GPT-2 on time-series data instead of text?
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2answers
135 views

What kind of neural network architecture is suitable for variable length block-like time series data?

I'm not sure what this type of data is called, so I will give an example of the type of data I am working with: A city records its inflow and outflow of different types of vehicles every hour. More ...
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0answers
8 views

Looking for the right type of 1D-Convolution that only considers one column/attribute

My input has the shape of n rows (time steps) and m columns (attributes). I want to train a convolutional neural network on it to predict a class. I am currently using 1D-Convolutions. I got a good ...
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0answers
33 views

Are there any ways to model markov chains from time series data?

I want to make a thing that produces a stochastic process from time series data. The time series data is recorded every hour over the year, which means 24-hour of patterns exist for 365 days. What I ...
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2answers
73 views

Conferences for Human Activity Recognition

What are some conferences for publishing papers on Deep Learning for Human Activity recognition? Do any of the major conferences have specific tracks for Human Activity Recognition?
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63 views

Spike detection in time series using Artificial Neural Networks

I'm quite new in ANNs. I intend to use ANNs for predicting spike points in time series right before they happen. I've already used LSTM for another scenario, and I know that they can be used in ...
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1answer
95 views

How to train a LSTM model with multi dimensional data

I am trying to train my model using LTSM layer in Keras (python). I have some problems regarding the data representation and feeding it into the model. My data is 184 XY coodinates encoded as a numpy ...
2
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0answers
82 views

What are the possible neural network architecture for linear regression or time series regression?

I started modeling a linear regression problem using dense layers (layers.dense), which works fine. I am really excited, and now I am trying to model a time series linear regression problem using CNN, ...
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0answers
34 views

Is it possible to use adversarial training to learn invariant features?

Given a set of time series data that are generated from different sites where all sites are investigating the same objective but with slightly different protocols. Is it possible to use adversarial ...
1
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1answer
55 views

Can HMM, MRF, or CRF be used to classify the state of a single observation, not the entire observation sequence?

I learn that the Viterbi algorithm used for Hidden Markov Model (HMM) can classify a sequence of hidden states from the corresponding observations; Markov Random Field (MRF) and Conditional Random ...
3
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1answer
127 views

How should I design the LSTM architecture for multivariate time series forecasting problems?

There is plenty of literature describing LSTMs in a lot of detail and how to use them for multi-variate or uni-variate forecasting problems. What I couldn't find though, is any papers or discussions ...
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1answer
125 views

Train and Test Accuracy of GRU network not increasing after 2nd epoch

So I´m currently implementing my first neural network using GRUs as a model and Keras as an implementation since it´s pretty highlevel. My problem is about the classification of 8 hour long timeseries ...
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2answers
97 views

Why is it harder to achieve good results using neural network based algorithms for multi step time series forecasting?

There are different kinds of machine learning algorithms, both univariate and multivariate, that are used for time series forecasting: for example ARIMA, VAR or AR. Why is it harder (compared to ...
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2answers
333 views

Can hidden Markov models be used to model any time series data?

Can HMMs be used to model any time series data? Or does the data have to be that of a Markov process? In HTK documentation, I see that the first few lines state that it can model any time series ...