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Cited by 3

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Prediction of House Price Using Stacked LSTM Model

Goswami, Shruti, Bramhe, Vijendra Singh, Khepra, Shaveta·2022·2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)
DOI 10.1109/icac3n56670.2022.10074011
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Abstract

House price is used as an economic indicator. Prediction of house price is important as it can be helpful for those who want to buy or plan to buy a house in the future or near future. It can give them an idea of the future price. It is also be helpful for sellers who are willing to sell their house as they can understand the future trend of the price of their houses. House price prediction is beneficial for the investors who want to invest in real estate. It helps to know the future trends of the real estate of a locality. In this paper, we have used deep learning Long Short-term memory model to predict house price. This model performed quiet well. Here our main motive is to see how data size influences a deep learning model. In a single model we have used different data size (specifically 12 different data sizes) and compared the results. It is evident from the results that data size plays a significant role in our model’s performance.

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Crossref · 10.1109/icac3n56670.2022.10074011

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1 of 1 references verified0 citation errors · 0 not checkable

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Citations

Cites

Show all 1 references

Research works printed but not linked: 9

  1. 10.1109/mdm.2019.00-15 · DOI
  2. 10.1109/iccsnt47585.2019.8962443 · DOI
  3. 10.1002/for.2678 · DOI
  4. 10.3390/su12187520 · DOI
  5. 10.1109/icdm.2019.00123 · DOI
  6. 10.1007/s11146-011-9359-3 · DOI
  7. 10.1109/icsai48974.2019.9010071 · DOI
  8. 10.53347/rid-88648 · DOI
  9. 10.1109/cc.2017.8068761 · DOI

Cited by

Metadata

Authors
Goswami, S., Bramhe, V. S., & Khepra, S.
Affiliations
Sharda University,Department of Engineering and Technology,Greater Noida,India
Venue
2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)
Publisher
IEEE
Published
2022-12-16
Pages
778-783
DOI
10.1109/icac3n56670.2022.10074011
Cited by
3
References
1
Licence

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