Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges
A Aldoseri, KN Al-Khalifa, AM Hamouda - Applied Sciences, 2023 - mdpi.com
The use of artificial intelligence (AI) is becoming more prevalent across industries such as
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
A review on nature-inspired algorithms for cancer disease prediction and classification
In the era of healthcare and its related research fields, the dimensionality problem of high-
dimensional data is a massive challenge as it is crucial to identify significant genes while …
dimensional data is a massive challenge as it is crucial to identify significant genes while …
Modified genetic algorithm with deep learning for fraud transactions of ethereum smart contract
Recently, the Ethereum smart contracts have seen a surge in interest from the scientific
community and new commercial uses. However, as online trade expands, other fraudulent …
community and new commercial uses. However, as online trade expands, other fraudulent …
Novel cuckoo search-based metaheuristic approach for deep learning prediction of depression
Depression is a common illness worldwide with doubtless severe implications. Due to the
absence of early identification and treatment for depression, millions of individuals …
absence of early identification and treatment for depression, millions of individuals …
CO‐WOA: novel optimization approach for deep learning classification of fish image
The most significant groupings of cold‐blooded creatures are the fish family. It is crucial to
recognize and categorize the most significant species of fish since various species of …
recognize and categorize the most significant species of fish since various species of …
Metaheuristics with deep learning model for cybersecurity and Android malware detection and classification
Since the development of information systems during the last decade, cybersecurity has
become a critical concern for many groups, organizations, and institutions. Malware …
become a critical concern for many groups, organizations, and institutions. Malware …
Evaluating the performance of metaheuristic based artificial neural networks for cryptocurrency forecasting
S Behera, SC Nayak, AVSP Kumar - Computational Economics, 2024 - Springer
The irregular movement of cryptocurrency market makes effective price forecasting a
challenging task. Price fluctuations in cryptocurrencies often appear to be arbitrary that has …
challenging task. Price fluctuations in cryptocurrencies often appear to be arbitrary that has …
Machine learning algorithms for crime prediction under Indian penal code
RM Aziz, P Sharma, A Hussain - Annals of data Science, 2024 - Springer
In this paper, the authors propose a data-driven approach to draw insightful knowledge from
the Indian crime data. The proposed approach can be helpful for police and other law …
the Indian crime data. The proposed approach can be helpful for police and other law …
Tracking phishing on Ethereum: Transaction network embedding approach for accounts representation learning
The transaction volume of Ethereum has been witnessing a year-on-year increase, which
has unfortunately been accompanied by significant losses due to phishing scams. To …
has unfortunately been accompanied by significant losses due to phishing scams. To …
Cybersecurity knowledge graphs construction and quality assessment
H Li, Z Shi, C Pan, D Zhao, N Sun - Complex & Intelligent Systems, 2024 - Springer
Cyber-attack activities are complex and ever-changing, posing severe challenges to
cybersecurity personnel. Introducing knowledge graphs into the field of cybersecurity helps …
cybersecurity personnel. Introducing knowledge graphs into the field of cybersecurity helps …