output
20162024
most citedDeep learning for Stock Market Prediction

399 citations

17 papers

math.NT2024

The Beurling-Malliavin density, the Polya density and their connection

Rita Giuliano, Georges Grekos, Ladislav Misik

In this paper we present a new formulation of the Beurling-Malliavin density (Proposition 1). Then we consider the upper Polya density and show how its existence is connected with…

cs.LG2022★ 122 cited

Systematic review of deep learning and machine learning for building energy

Ardabili Sina, Leila Abdolalizadeh, Csaba Mako +2

The building energy (BE) management has an essential role in urban sustainability and smart cities. Recently, the novel data science and data-driven technologies have shown signifi…

cs.LG2022★ 1 cited

Integration of neural network and fuzzy logic decision making compared with bilayered neural network in the simulation of daily dew point temperature

Guodao Zhang, Shahab S. Band, Sina Ardabili +2

In this research, dew point temperature (DPT) is simulated using the data-driven approach. Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized as a data-driven technique to f…

econ.GN2021★ 18 cited

The Effect of Marketing Investment on Firm Value and Systematic Risk

Musaab Mousa, Saeed Nosratabadi, Judit Sagi +1

Analyzing the financial benefit of marketing is still a critical topic for both practitioners and researchers. Companies consider marketing costs as a type of investment and expect…

cs.CR2020★ 103 cited

Early detection of the advanced persistent threat attack using performance analysis of deep learning

Javad Hassannataj Joloudari, Mojtaba Haderbadi, Amir Mashmool +3

One of the most common and important destructive attacks on the victim system is Advanced Persistent Threat (APT)-attack. The APT attacker can achieve his hostile goals by obtainin…

cs.LG2020★ 268 cited

Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran

Mostafa Emadi, Ruhollah Taghizadeh-Mehrjardi, Ali Cherati +3

Estimation of the soil organic carbon content is of utmost importance in understanding the chemical, physical, and biological functions of the soil. This study proposes machine lea…