Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Letteri, Ivan"'
Autor:
Dyoub, Abeer, Letteri, Ivan
In this study, we investigated the application of bio-inspired optimization algorithms, including Genetic Algorithm, Particle Swarm Optimization, and Whale Optimization Algorithm, for feature selection in chronic disease prediction. The primary goal
Externí odkaz:
http://arxiv.org/abs/2401.05380
Tax incentives and fiscal bonuses have had a significant impact on the Italian economy over the past decade. In particular, the "Superbonus 110" tax relief in 2020, offering a generous 110% deduction for expenses related to energy efficiency improvem
Externí odkaz:
http://arxiv.org/abs/2311.01584
Autor:
Letteri, Ivan
Volatility-based trading strategies have attracted a lot of attention in financial markets due to their ability to capture opportunities for profit from market dynamics. In this article, we propose a new volatility-based trading strategy that combine
Externí odkaz:
http://arxiv.org/abs/2307.13422
In general, traders test their trading strategies by applying them on the historical market data (backtesting), and then apply to the future trades the strategy that achieved the maximum profit on such past data. In this paper, we propose a new tradi
Externí odkaz:
http://arxiv.org/abs/2210.11532
Stock market forecasting is a lucrative field of interest with promising profits but not without its difficulties and for some people could be even causes of failure. Financial markets by their nature are complex, non-linear and chaotic, which implie
Externí odkaz:
http://arxiv.org/abs/2201.12286
Publikováno v:
EPTCS 345, 2021, pp. 182-188
Dialogue Systems are tools designed for various practical purposes concerning human-machine interaction. These systems should be built on ethical foundations because their behavior may heavily influence a user (think especially about children). The p
Externí odkaz:
http://arxiv.org/abs/2109.08294
Despite the enormous amount of data, particular events of interest can still be quite rare. Classification of rare events is a common problem in many domains, such as fraudulent transactions, malware traffic analysis and network intrusion detection.
Externí odkaz:
http://arxiv.org/abs/2012.15231
Machine learning is rapidly becoming one of the most important technology for malware traffic detection, since the continuous evolution of malware requires a constant adaptation and the ability to generalize. However, network traffic datasets are usu
Externí odkaz:
http://arxiv.org/abs/2009.11347
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