National vaccination and local intervention impacts on covid-19 cases

T Toharudin, RS Pontoh, RE Caraka, S Zahroh… - Sustainability, 2021 - mdpi.com
COVID-19, as a global pandemic, has spread across Indonesia. Jakarta, as the capital of
Indonesia, is the province with the most positive cases. The government has issued various …

Hybrid vector autoregression feedforward neural network with genetic algorithm model for forecasting space-time pollution data

RE Caraka, RC Chen, H Yasin… - Indonesian Journal of …, 2021 - ejournal.kjpupi.id
The exposure rate to air pollution in most urban cities is really a major concern because it
results to a life-threatening consequence for human health and wellbeing. Furthermore, the …

Determination of the best weight matrix for the Generalized Space Time Autoregressive (GSTAR) model in the Covid-19 case on Java Island, Indonesia

N Imro'ah - Spatial Statistics, 2023 - Elsevier
One factor that goes into the construction of a space–time model, in this case, the
Generalized Space–Time Autoregressive (GSTAR) model, is the weight matrix, which acts …

Characteristics of the methanotroph used in coalbed methane emission reduction: Methane oxidation efficiency and coal wettability

Y Zhou, R Zhang, K Tian, S Zhao, H Shi, W Gong, Q Lei - Fuel, 2023 - Elsevier
In the process of coal mining, a large amount of methane is emitted into the atmosphere
every year, which enhances the greenhouse effect of the atmosphere. Microbial methane …

An improved equilibrium optimizer algorithm and its application in LSTM neural network

P Lan, K Xia, Y Pan, S Fan - Symmetry, 2021 - mdpi.com
An improved equilibrium optimizer (EO) algorithm is proposed in this paper to address
premature and slow convergence. Firstly, a highly stochastic chaotic mechanism is adopted …

Spatio-temporal forecasting: A survey of data-driven models using exogenous data

S Berkani, B Guermah, M Zakroum, M Ghogho - IEEE Access, 2023 - ieeexplore.ieee.org
Forecasting Spatio-Temporal processes has been attracting a great deal of interest within
the research community. In this context, there is an increasing trend of proposing and …

VAR and GSTAR-based feature selection in support vector regression for multivariate spatio-temporal forecasting

DD Prastyo, FS Nabila, Suhartono, MH Lee… - Soft Computing in Data …, 2019 - Springer
Multivariate time series modeling is quite challenging particularly in term of diagnostic
checking for assumptions required by the underlying model. For that reason, nonparametric …

[HTML][HTML] Generalised Space-Time Seasonal Autoregressive Integrated Moving Average Seemingly Unrelated Regression Modelling of Seasonal and Non-stationary …

S Ajobo, OO Alaba, A Zaenal - Scientific African, 2024 - Elsevier
ABSTRACT The Generalised Space-Time Seasonal Autoregressive Integrated Moving
Average (GSTSARIMA) model is known to efficiently handle non-stationary and seasonal …

Pemodelan Multivariate Kunjungan Wisatawan Mancanegara ke Indonesia Melalui Pintu Udara, Laut, dan Darat yang Melibatkan Dampak Wabah COVID-19

MR Susila - Barekeng: Jurnal Ilmu Matematika Dan Terapan, 2021 - ojs3.unpatti.ac.id
Salah satu penyumbang pertumbuhan perekonomian Indonesia adalah sektor pariwisata.
Menurut asalnya wisatawan dibagi menjadi dua yaitu wisatawan lokal dan mancanegara …

Evolving Hybrid Cascade Neural Network Genetic Algorithm Space–Time Forecasting

RE Caraka, H Yasin, RC Chen, NE Goldameir… - Symmetry, 2021 - mdpi.com
Design: At the heart of time series forecasting, if nonlinear and nonstationary data are
analyzed using traditional time series, the results will be biased. At the same time, if just …