Titlebook: Construction Analytics; Forecasting and Inve Mohsen Shahandashti,Bahram Abediniangerabi,Sooin K Textbook 2023 The Editor(s) (if applicable)

enmesh

Minuet

Polydipsia

abracadabra

Charakteristika des Baumarktes,and compared with those of seasonal ARIMA and VEC models. The comparison results show that recurrent neural networks (i.e., long short-term memory and gated recurrent unit networks) can provide higher accuracies in forecasting the long-term variations of HCS than statistical linear time series models based on typical error measures.

paltry

Construction Time Series Forecasting Using Multivariate Time Series Models,s compared with the results of the univariate seasonal ARIMA model. The comparison results show that the VEC model outperforms the seasonal autoregressive integrated moving average (SARIMA) model based on typical error measures.

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reaching

Textbook 2023tion. The book maximizes students’ understanding of the necessary theoretical background of data analytics, and explains the implementation of data analytics techniques to solve the actual problems in the construction industry. . ..

古文字学

incubus

FEMUR