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Finding an accurate early forecasting model from small dataset: A case of 2019-nCoV novel coronavirus outbreak
(International Journal of Interactive Multimedia and Artificial Intelligence, 2020-03)
Epidemic is a rapid and wide spread of infectious disease threatening many lives and economy damages. It is important to fore-tell the epidemic lifetime so to decide on timely and remedic actions. These measures include ...
Composite Monte Carlo decision making under high uncertainty of novel coronavirus epidemic using hybridized deep learning and fuzzy rule induction
(Applied Soft Computing Journal, 2020-08)
In the advent of the novel coronavirus epidemic since December 2019, governments and authorities have been struggling to make critical decisions under high uncertainty at their best efforts. In computer science, this ...
A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak
(Applied intelligence, 2021)
Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 ...
Alzheimer's Patient Analysis Using Image and Gene Expression Data and Explainable-AI to Present Associated Genes
(Institute of Electrical and Electronics Engineers Inc., 2021)
There are more than 10 million new cases of Alzheimer's patients worldwide each year, which means there is a new case every 3.2 s. Alzheimer's disease (AD) is a progressive neurodegenerative disease and various machine ...
Social IoT Approach to Cyber Defense of a Deep-Learning-Based Recognition System in front of Media Clones Generated by Model Inversion Attack
(IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023)
Model inversion attack (MIA) is a cyber threat with an increasing alert even for deep-learning-based recognition systems (DLRSs). By targeting a DLRS under a scenario of attacker access to the model structure and parameters, ...
DisastDrone: A Disaster Aware Consumer Internet of Drone Things System in Ultra-Low Latent 6G Network
(IEEE Transactions on Consumer Electronics, 2023)
Internet of Things application in disaster responses and management is a predominant research domain. The introduction of the consumer drones, flying ad-hoc networks, low latency 5G, and beyond 5G produce significant ...
The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID19 Pandemic
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they ...
Analysis of the COVID19 Pandemic Behaviour Based on the Compartmental SEAIRD and Adaptive SVEAIRD Epidemiologic Models
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
A significant number of people infected by COVID19 do not get sick immediately but become carriers of the disease. These patients might have a certain incubation period. However, the classical compartmental model, SEIR, ...
The Comparison of Different Linear and Nonlinear Models Using Preliminary Data to Efficiently Analyze the COVID-19 Outbreak
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
The COVID-19 pandemic spread generated an urgent need for computational systems to model its behavior and support governments and healthcare teams to make proper decisions. There are not many cases of global pandemics in ...
Probabilistic Forecasting Model for the COVID-19 Pandemic Based on the Composite Monte Carlo Model Integrated with Deep Learning and Fuzzy System
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
There are several techniques to support simulation of time series behavior. In this chapter, the approach will be based on the Composite Monte Carlo (CMC) simulation method. This method is able to model future outcomes of ...