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.

List of archived papers

Improving ADHD Detection with Cost-Sensitive LightGBM

Behnam Yousefimehr - Mehdi Ghatee - Ali Heydari

Effect of Tissue Excitation in Breast Cancer Detection from Ultrasound RF Time Series: Phantom studies

Elaheh Norouzi Ghehi - Ali Fallah - Saeid Rashidi - Maryam Mehdizadeh Dastjerdi

Virus-Antiviral Prediction Using Machine and Deep Learning Methods

Shayan Majidifar - Fatemeh Nasiri - Mohsen Hooshmand

FAST: FPGA Acceleration of Neural Networks Training

Alireza Borhani - Mohammad Hossein Goharinejad - Hamid Reza Zarandi

Deep Learning-Based Malaysian Sign Language (MSL) Recognition: Exploring the Impact of Color Spaces

Ervin Gubin Moung - Precilla Fiona Suwek - Maisarah Mohd Sufian - Valentino Liaw - Ali Farzamnia - Wei Leong Khong

Analysis of Insect-plant Interactions Affected by Mining operations, A Graph Mining Approach

Mohammad Heydari - Ali Bayat - Amir Albadvi

Prediction of rTMS Treatment Response in Depression Using a Frequency-Based EEG Biomarker

Ali Asadi Zeidabadi - Saeid Rashidi

Reversible Data Insertion in Encryption Domain Based on Reduced Quad Difference Expansion

Alireza Ghaemi - Mohammad Zare Ehteshami - Amirhossein Ghaemi

Damage Detection After the Earthquake Using Sentinel-1 and 2 Images and Machine Learning Algorithms (Case Study: Sarpol-e Zahab Earthquake)

Niloofar Alizadeh - Behnam Asghari Beirami - Mehdi Mokhtarzade

A Deep CNN Model Based Ensemble Approach for Semantic and Instance Segmentation of Indoor Environment

Sajad Rezaei - Jafar Tanha - Zahra Jafari - SeyedEhsan Roshan - Mohammad-Amin Memar Kochebagh

more

Samin Hamayesh - Version 43.7.0