International Conference on Computer and Knowledge Engineering

Home / 11th International Conference on Computer and Knowledge Engineering

A novel hybrid DMHS-GMDH algorithm to predict COVID-19 pandemic time series

Authors :

Ahmad Taheri¹ Shahriar Ghashghaei² Amin Beheshti³ Keyvan RahimiZadeh⁴

1- Yasouj University 2- Tehran University of Medical Sciences 3- Macquarie University 4- Yasouj University, Macquarie University

Keywords :

COVID-19, pandemic, machine learning, harmony search, metaheuristic algorithm

Abstract :

In this paper, a novel hybrid method called DMHS-GMDH is presented to predict the time series of COVID-19 outbreaks. In this way, a new version of Harmony Search (HS) algorithm, named Double Memory HS (DMHS), is designed to optimize the structure of a Group Method of Data Handling (GMDH) type neural network. We conduct a series of experiments by applying proposed method on real COVID-19 dataset to forecast new cases and deaths of COVID-19. The statistical analysis indicates that the DMHS-GMDH algorithm on average provides better results than other competitors and the results demonstrate how our approach at least improves coefficient of determination and RMSE by 21% and 45%, respectively.

Papers List

List of archived papers

Improving Motor Imagery Classification in BCI Systems Using EMD and Multi-Layer CNNs

Reza Arghand - Ali Chaibakhsh - Moein Radman

Using Deep Learning for Classification of Lung Cancer on CT Images in Ardabil Province

Mohammad Ali Javadzadeh Barzaki - Jafar Abdollahi - Mohammad Negaresh - Maryam Salimi - Hadi Zolfeghari - Mohsen Mohammadi - Asma Salmani - Rona Jannati - Firouz Amani

Islamic Geometric algorithms: A survey

Elham Akbari - Azam Bastanfard

Histopathology Image-Based Cancer Classification Utilizing Transfer Learning Approach

Amir Meydani - Alireza Meidani - Ali Ramezani - Maryam Shabani - Mohammad Mehdi Kazeminasab - Shahriar Shahablavasani

Optimization Resource Allocation in NOMA-based Fog Computing with a Hybrid Algorithm

Zohreh Torki - S.Mojtaba Matinkhah

Early detection of Parkinson’s disease using Convolutional Neural Networks on SPECT images

Reyhaneh Dehghan - Marjan Naderan - Seyyed Enayatallah Alavi

Real-Time Gender Recognition with a Deep Neural Network

Samad Azimi Abriz - Majid Meghdadi

ROCT-Net: A new ensemble deep convolutional model with improved spatial resolution learning for detecting common diseases from retinal OCT images

Mohammad Rahimzadeh - Mahmoud Reza Mohammadi

An Interactive Approach for Query-based Multi-Document Scientific Text Summarization

Mohammadsadra Nejati - Azadeh Mohebi - Abbas Ahmadi

PowerLinear Activation Functions with application to the first layer of CNNs

Kamyar Nasiri - Kamaledin Ghiasi-Shirazi

Samin Hamayesh - Version 42.2.1