TY - GEN
T1 - Big Data Analysis and Mining For People's Livelihood Appeal
AU - Lin, Lin
AU - Li, Ning
AU - Lei, Gaoming
AU - Qin, Wei
AU - Liang, Lixin
AU - Shen, Lu
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/5/26
Y1 - 2023/5/26
N2 - In this paper, by using the dataset of people's livelihood appeal published by government, we construct a combined model of Decomposing Module and Long Short-Term Memory (DM-LSTM) neural network, and conduct the short-term analysis of people's livelihood appeal events and nowcasting of regional Gross Domestic Product (GDP). The experimental results show that the sequence decomposition algorithm has an impact on the prediction accuracy. The Wavelet Package Decomposition (WPD) and Variational Mode Decomposition (VMD) decomposition algorithms have better performance in the task of predicting people's livelihood appeal events, while the Empirical Wavelet Transform Decomposition (EWD) algorithm is more suitable for the task of regional GDP nowcasting.
AB - In this paper, by using the dataset of people's livelihood appeal published by government, we construct a combined model of Decomposing Module and Long Short-Term Memory (DM-LSTM) neural network, and conduct the short-term analysis of people's livelihood appeal events and nowcasting of regional Gross Domestic Product (GDP). The experimental results show that the sequence decomposition algorithm has an impact on the prediction accuracy. The Wavelet Package Decomposition (WPD) and Variational Mode Decomposition (VMD) decomposition algorithms have better performance in the task of predicting people's livelihood appeal events, while the Empirical Wavelet Transform Decomposition (EWD) algorithm is more suitable for the task of regional GDP nowcasting.
KW - Big Data Analysis and Mining
KW - Decomposing Module and Long Short-Term Memory (DM-LSTM)
KW - People's Livelihood Appeal
UR - https://www.scopus.com/pages/publications/85180410332
U2 - 10.1145/3624288.3624293
DO - 10.1145/3624288.3624293
M3 - Conference contribution
AN - SCOPUS:85180410332
T3 - ACM International Conference Proceeding Series
SP - 32
EP - 40
BT - ICBDC 2023 - 2023 8th International Conference on Big Data and Computing
PB - Association for Computing Machinery
T2 - 8th International Conference on Big Data and Computing, ICBDC 2023
Y2 - 26 May 2023 through 28 May 2023
ER -