Rainfall-runoff modeling, a nonlinear time series process, is challenging and important in
hydrological sciences. Among the data-driven approaches, those ones based on the long …

Short text classification is a challenging task in natural language processing. Existing
traditional methods using external knowledge to deal with the sparsity and ambiguity of short …

In addition to the tremendous loss of life due to coronavirus disease 2019 (COVID-19), the
pandemic created challenges for the energy system, as strict confinement measures such as …

Predicting system energy consumption accurately and adjusting dynamic operating
parameters of the HVAC system in advance is the basis of realizing the model predictive …

Determining a policy is often limited in a short time so that decisions are prone to
inaccuracies and are ultimately judged to be less targeted. Therefore, there is a necessity to …

Recurrent neural networks are efficient ways of training language models, and various RNN
networks have been proposed to improve performance. However, with the increase of …

Detecting the vitality of a certain distance person is important in natural disasters, search
and rescue activities, urban warfare environments and in the fight against terrorism. In this …

Recurrent neural network is an important model in the field of deep learning. Similar network
structure is used to recursively form a more complex deep network with a relatively simple …

The subject of this PhD thesis is language modeling–but what does that mean, building a
model that tries to capture a language? A language model tries to predict the patterns …