Applications of deep learning in stock market prediction: recent progress
W Jiang - Expert Systems with Applications, 2021 - Elsevier
Stock market prediction has been a classical yet challenging problem, with the attention from
both economists and computer scientists. With the purpose of building an effective prediction …
both economists and computer scientists. With the purpose of building an effective prediction …
[HTML][HTML] Software defined satellite networks: A survey
W Jiang - Digital Communications and Networks, 2023 - Elsevier
In recent years, satellite networks have been proposed as an essential part of next-
generation mobile communication systems. Software defined networking techniques are …
generation mobile communication systems. Software defined networking techniques are …
Scientometric review and analysis of recent approaches to stock market forecasting: Two decades survey
TO Kehinde, FTS Chan, SH Chung - Expert Systems with Applications, 2023 - Elsevier
Abstract Stock Market Forecasting (SMF) has become a spotlighted area and is receiving
increasing attention due to the potential that investment returns can generate profound …
increasing attention due to the potential that investment returns can generate profound …
[HTML][HTML] Time series classification: Nearest neighbor versus deep learning models
W Jiang - SN Applied Sciences, 2020 - Springer
Time series classification has been an important and challenging research task. In different
domains, time series show different patterns, which makes it difficult to design a global …
domains, time series show different patterns, which makes it difficult to design a global …
Bangla-Meitei Mayek scripts handwritten character recognition using convolutional neural network
Recognition of handwritten characters in two Indic scripts Bangla and Meitei Mayek is one of
the challenging responsibilities due to intricate patterns and scarcity of standard datasets …
the challenging responsibilities due to intricate patterns and scarcity of standard datasets …
[HTML][HTML] Handwritten Arabic character recognition for children writing using convolutional neural network and stroke identification
Automatic Arabic handwritten recognition is one of the recently studied problems in the field
of Machine Learning. Unlike Latin languages, Arabic is a Semitic language that forms a …
of Machine Learning. Unlike Latin languages, Arabic is a Semitic language that forms a …
[HTML][HTML] A bibliometric analysis of off-line handwritten document analysis literature (1990–2020)
Providing computers with the ability to process handwriting is both important and
challenging, since many difficulties (eg, different writing styles, alphabets, languages, etc.) …
challenging, since many difficulties (eg, different writing styles, alphabets, languages, etc.) …
[HTML][HTML] Handwritten numeral recognition through superimposition onto printed form
Handwriting is, eventually, a variation of the printed forms where the characters are little
larger, smaller, angled and deformed than the printed forms. The small changes in …
larger, smaller, angled and deformed than the printed forms. The small changes in …
An evaluation of machine learning and deep learning models for drought prediction using weather data
Drought is a serious natural disaster that has a long duration and a wide range of influences.
To decrease drought-induced losses, drought prediction is the basis of corresponding …
To decrease drought-induced losses, drought prediction is the basis of corresponding …
Heart failure prediction with machine learning: a comparative study
J Wang - Journal of Physics: Conference Series, 2021 - iopscience.iop.org
Heart failure is a worldwide healthy problem affecting more than 550,000 people every year.
A better prediction for this disease is one of the key approaches of decreasing its impact …
A better prediction for this disease is one of the key approaches of decreasing its impact …