Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries

S Singh, KS Parmar, SJS Makkhan, J Kaur… - Chaos, Solitons & …, 2020 - Elsevier
Discussions about the recently identified deadly coronavirus disease (COVID-19) which
originated in Wuhan, China in December 2019 are common around the globe now. This is …

Daily PM2. 5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm

W Sun, J Sun - Journal of environmental management, 2017 - Elsevier
Increased attention has been paid to PM 2.5 pollution in China. Due to its detrimental effects
on environment and health, it is important to establish a PM 2.5 concentration forecasting …

Fast stochastic configuration network based on an improved sparrow search algorithm for fire flame recognition

H Wu, A Zhang, Y Han, J Nan, K Li - Knowledge-Based Systems, 2022 - Elsevier
Flame image recognition is of great significance in the fire detection and prevention. In this
paper, in order to improve the accuracy of fire recognition, a fast stochastic configuration …

Electric load forecasting based on a least squares support vector machine with fuzzy time series and global harmony search algorithm

YH Chen, WC Hong, W Shen, NN Huang - Energies, 2016 - mdpi.com
This paper proposes a new electric load forecasting model by hybridizing the fuzzy time
series (FTS) and global harmony search algorithm (GHSA) with least squares support vector …

Ensemble probabilistic prediction approach for modeling uncertainty in crude oil price

J Wang, T Niu, P Du, W Yang - Applied Soft Computing, 2020 - Elsevier
The quantification of the uncertainty in crude oil price is of significance to improve the related
financial decision-making. However, studies in this field have remained limited because the …

Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors

H Balogun, H Alaka, CN Egwim - Applied Computing and Informatics, 2021 - emerald.com
Purpose This paper seeks to assess the performance levels of BA-GS-LSSVM compared to
popular standalone algorithms used to build NO2 prediction models. The purpose of this …

A cooperative stochastic configuration network based on differential evolutionary sparrow search algorithm for prediction

W Fang, B Shen, A Pan, L Zou… - Systems Science & Control …, 2024 - Taylor & Francis
Stochastic configuration network (SCN) is a powerful prediction model whose performance
is significantly influenced by the configuration of the network parameters. To improve the …

Forecasting East and West Coast Gasoline Prices with Tree-Based Machine Learning Algorithms

E Sofianos, E Zaganidis, T Papadimitriou, P Gogas - Energies, 2024 - mdpi.com
This study aims to forecast New York and Los Angeles gasoline spot prices on a daily
frequency. The dataset includes gasoline prices and a big set of 128 other relevant variables …

Balancing exploration and exploitation by using sequential execution cooperation between artificial bee colony and migrating birds optimization algorithms

H Makas, N YUMUŞAK - Turkish Journal of Electrical …, 2016 - journals.tubitak.gov.tr
The artificial bee colony (ABC) algorithm is a metaheuristic search method inspired by bees'
foraging behaviour. With its global search ability in scout bee phase, it can easily escape …

A hybrid least squares support vector machine with bat and cuckoo search algorithms for time series forecasting

AJ Mohammed, KI Ghathwan… - Journal of Information …, 2020 - e-journal.uum.edu.my
Least Squares Support Vector Machine (LSSVM) has been known to be one of the effective
forecasting models. However, its operation relies on two important parameters …