The stock market has been an attractive field for a large number of organizers and investors
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …

In this survey paper, we characterize the learning problem in cognitive radios (CRs) and
state the importance of artificial intelligence in achieving real cognitive communications …

Large volumes of event data are becoming increasingly available in a wide variety of
applications, such as healthcare analytics, smart cities and social network analysis. The …

A good prediction of landslide displacement is an essential component for implementing an
early warning system. In the Three Gorges Reservoir Area (TGRA), many landslides deform …

Recurrent neurons (and in particular LSTM cells) demonstrated to be efficient when used as
basic blocks to build sequence to sequence architectures, which represent the state-of-the …

For the consideration of environmental aspects of the personal transportation, electric
vehicle (EV) and plug-in hybrid electric vehicle (PHEV) has the prospective solution …

Event sequence, asynchronously generated with random timestamp, is ubiquitous among
applications. The precise and arbitrary timestamp can carry important clues about the …

Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …

Machine learning methods trained on raw numerical time series data exhibit fundamental
limitations such as a high sensitivity to the hyper parameters and even to the initialization of …

Server workload in the form of cloud-end clusters is a key factor in server maintenance and
task scheduling. How to balance and optimize hardware resources and computation …