Predicting human design decisions with deep recurrent neural network combining static and dynamic data
نویسندگان
چکیده
منابع مشابه
Deep Gate Recurrent Neural Network
This paper explores the possibility of using multiplicative gate to build two recurrent neural network structures. These two structures are called Deep Simple Gated Unit (DSGU) and Simple Gated Unit (SGU), which are structures for learning long-term dependencies. Compared to traditional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), both structures require fewer parameters and le...
متن کاملEstimating Efficiency of Bank Branches by Dynamic Network Data Envelopment Analysis and Artificial Neural Network
Network data envelopment analysis models assess efficiency of decision-making unit and its sections using historical data but fail to measure efficiency of its units and their internal stages in the future. In this paper we aim to measure efficiency of stages of bank branches and obtain efficiency trend of stages during the time, then to estimate their efficiency in the future therefore we can ...
متن کاملAdaptive stimulus design for dynamic recurrent neural network models
We present a theoretical application of an optimal experiment design (OED) methodology to the development of mathematical models to describe the stimulus-response relationship of sensory neurons. Although there are a few related studies in the computational neuroscience literature on this topic, most of them are either involving non-linear static maps or simple linear filters cascaded to a stat...
متن کاملPredicting Auction Price of Vehicle License Plate with Deep Recurrent Neural Network
In Chinese societies where superstition is of paramount importance, vehicle license plates with desirable numbers can fetch for very high prices in auctions. Unlike auctions of other valuable items, however, license plates do not get an estimated price before auction. In this paper, I construct a deep recurrent neural network to predict the prices of vehicle license plates in Hong Kong based on...
متن کاملComparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange
During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis, different types of these models have been used in forecasting. Now, there is a question that which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this, the present paper made a comparison betw...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Design Science
سال: 2020
ISSN: 2053-4701
DOI: 10.1017/dsj.2020.12