Predicting Human Position Using Improved Numerical Association Analysis for Bioelectric Potential Data

Tahyudin, Imam; Berlilana,; Nambo, Hidetaka

doi:10.1007/978-3-030-12388-8_46

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…The aim is to prevent the premature search for optimal values because they are trapped in optimal local values. This method uses the concept of PSO, but a modification process is carried out on the velocity equation by including the Cauchy distribution [28], [30]. The velocity function can be seen from function (12) as follows.…”

Section: Parcdmentioning

confidence: 99%

“…Meanwhile, the PARCD method can also estimate a person's position with a non-linear data set with an accuracy of about 75% [28]; hence, In this paper, we proposed a combined SARIMA time series model and PARCD evolutionary algorithm (SARIMA-PARCD) that aims to solve for linear and nonlinear problems. The proposed model accuracy is compared to the other baseline models, SARIMA, LSTM, and SARIMA-LSTM.…”

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confidence: 99%

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The mortality modeling of covid-19 patients using a combined time series model and evolutionary algorithm

Tahyudin

Wahyudi

Maulana

et al. 2022

Int. J. Adv. Intell. Informatics

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COVID-19 pandemics for as long as two years ago since 2019 gives many insights into various aspects, including scientific development. One of them is the fundamental research of computer science. This research aimed to construct the best model of COVID-19 patients’ mortality and obtain less prediction errors. We performed the combination methods of time series, SARIMA, and Evolutionary algorithm, PARCD, to predict male patients who died because of COVID-19 in the USA, containing 1.008 data. So, this research proposed that SARIMA-PARCD has a powerful combination for addressing the complex problem in a dataset. The prediction error of SARIMA-PARCD was compared with other methods, i.e., SARIMA, LSTM, and the combination of SARIMA-LSTM. The result showed that the SARIMA-PARCD has the smallest MSE value of 0.0049. Therefore, the proposed method is competitive to implement in other cases with similar characteristics. This combination is robust for solving linear and non-linear problems.

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Section: Parcdmentioning

confidence: 99%

mentioning

confidence: 99%

The mortality modeling of covid-19 patients using a combined time series model and evolutionary algorithm

Tahyudin

Wahyudi

Maulana

et al. 2022

Int. J. Adv. Intell. Informatics

Self Cite

View full text Add to dashboard Cite

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“…This operator helps in avoiding the PSO algorithm trapping in local optima. The PARCD was also applied practically for predicting human positions [33]. In the years since the introduction of the PARCD algorithm, an improved version was released by the same authors [32].…”

Section: Particle Swarm Optimization Narm Variantsmentioning

confidence: 99%

A brief overview of swarm intelligence-based algorithms for numerical association rule mining

Fister¹

2020

Preprint

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Numerical Association Rule Mining is a popular variant of Association Rule Mining, where numerical attributes are handled without discretization. This means that the algorithms for dealing with this problem can operate directly, not only with categorical, but also with numerical attributes. Until recently, a big portion of these algorithms were based on a stochastic nature-inspired population-based paradigm. As a result, evolutionary and swarm intelligence-based algorithms showed big efficiency for dealing with the problem. In line with this, the main mission of this chapter is to make a historical overview of swarm intelligence-based algorithms for Numerical Association Rule Mining, as well as to present the main features of these algorithms for the observed problem. A taxonomy of the algorithms was proposed on the basis of the applied features found in this overview. Challenges, waiting in the future, finish this paper.

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A Brief Overview of Swarm Intelligence-Based Algorithms for Numerical Association Rule Mining

Fister

2021

Springer Tracts in Nature-Inspired Computing

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Predicting Human Position Using Improved Numerical Association Analysis for Bioelectric Potential Data

Cited by 4 publications

References 8 publications

The mortality modeling of covid-19 patients using a combined time series model and evolutionary algorithm

The mortality modeling of covid-19 patients using a combined time series model and evolutionary algorithm

A brief overview of swarm intelligence-based algorithms for numerical association rule mining

A Brief Overview of Swarm Intelligence-Based Algorithms for Numerical Association Rule Mining

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