With a large number of environmental data, the air quality prediction based on deep learning technology is studied in depth. Based on long short-term memory (LSTM), a comprehensive prediction model with multi-output and multi-index of supervised learning (MMSL) was proposed. The particle ...
the autoregressive integrated moving average (ARIMA) model, the gray model, and the multiple linear regression (MLR) model4,5proposed an algorithm to assess the pollution level of air quality parameters and create a new air quality index based on the fuzzy reasoning system ...
In order to improve the energy utilization rate and prolong the working time of the system, the dynamic programming algorithm is used to reasonably plan the sensing strategy of the sensor. In order to obtain the variation trend of indoor air quality, the LSTM network is used to predict the ...
The concentration of PM2.5 is an important index to measure the degree of air pollution. When it exceeds the standard value, it is considered to cause pollution and lower the air quality, which is harmful to human health and can cause a variety of diseases, i.e., asthma, chronic bronchiti...
In this research, the impact of different preprocessing methods on the Long-Short term memory in predicting the financial time series was examined. At first, the model was implemented on the Tehran stock exchange index by utilizing the Principal Component Analysis (PCA) model on 78 technical indic...
Human Mobility Prediction Based on Trend Iteration of Spectral Clustering. Wenzhen Jia (School of Software, Tongji University), Shengjie Zhao, Kai Zhao. TMC 2024 [link] TrajBERT: BERT-Based Trajectory Recovery With Spatial-Temporal Refinement for Implicit Sparse Trajectories. Junjun Si (School of So...
A novel hybrid model for air quality index forecasting based on two-phase decomposition technique and modified extreme learning machine Science of Total Environment, 12 (2016), p. 018 Google Scholar 18 Liu B-C, Binaykia A, Chang P-C, Tiwari MK, Tsao C Urb...
the data cleansing method is proposed for ADS-B raw data. Furthermore, considering that the spatial trajectory of the aircraft is a complex time series with continuity and interactivity, a bidirectional LSTM based aircraft trajectory prediction framework is proposed to further improve prediction ...
Here we also classify solely based on the model's description in the original paper. univariate time series forecasting: , where is the history length, is the prediction horizon length. multivariate time series forecasting: , where is the number of variables (channels). spatio-temporal forecasting...
The North Atlantic Oscillation (NAO), which manifests as an irregular atmospheric fluctuation, has a profound effect on the global climate change. The NAO index (NAOI) is the quantitative indicator that can reflect the intensity of the NAO events, and its traditional definition is the normalized...