Rice is the main food in Indonesia. drying by using traditional method directly under sun light can require a long time to complete. The aim of this study investigate appropriate kinetics modeling rice with applied fluidized bed dryer. A 2-cm thickness has been dried at various temperatures (50℃, 60℃, and 70℃) air velocity 10 m/s from hot dryer obtained pyrolysis process. selected based on agre...

Given that the traditional ARIMAX model has rarely been applied to any of climate change and environmental agents, which are most cognate agents with associated exogenous variables; neutralize for a better enhanced prediction system, distributional form error term is robust sufficient in capturing accommodating both external covariate(s) high frequency data required. This study therefore evalua...

The conventional criteria for predictive model selection do not indicate the absolute goodness of models. For example, the quantity of Akaike Information Criterion (AIC) has meanings only when we compare AIC of different models for a given amount of data. Thus, the existing criteria do not tell us whether the quantity and quality of data is satisfactory, and hence we cannot judge whether we sho...

We explore the viable $f(R)$ gravity models in FLRW backgrounds with a free spatial curvature parameter $\Omega_{K}$. In our numerical calculation, we concentrate on exponential model of $f(R) = R - \lambda R_{ch}(1-\exp{(-R/R_{ch}}))$, where $R_{ch}$ is characteristic scale, which independent $\Omega_K$, and $\lambda$ corresponds to parameter, while $R_{ch}\lambda=2\Lambda$ $\Lambda$ cosmologi...

The Akaike Information Criterion (AIC) is a powerful and highly principled method of model selection. When working with probabilistic models it is typical to fit them to the data by maximum likelihood, using Markov Chain Monte Carlo or Belief Propagation. The maximum likelihood value obtained in this way gives an indication of how good a fit the model is to the data. Unfortunately, models with ...

ABSTRACT In this work, we investigate the MOdified Gravity (MOG) theory for dynamics of Universe and compare results with Lambda cold dark matter (?CDM) cosmology. We study background cosmological properties MOG model structure formation at linear perturbation level. two models currently available data by using statistical Bayesian analyses. After obtaining updated constraints on free parameter...

Selection of estimators is an essential task in modeling. A general framework is that the estimators of a distribution are obtained by minimizing a function (the estimating function) and assessed using another function (the assessment function). A classical case is that both functions estimate an information risk (specifically cross-entropy); this corresponds to using maximum likelihood estimat...

Currently available methods for model selection used in phylogenetic analysis are based on an initial fixed-tree topology. Once a model is picked based on this topology, a rigorous search of the tree space is run under that model to find the maximum-likelihood estimate of the tree (topology and branch lengths) and the maximum-likelihood estimates of the model parameters. In this paper, we propo...

Abstract The one of the metaheuristic approaches that can be used was simulated annealing (SA) algorithm which inspired by metallurgical process. This shows advantages in finding global optimum given function will feature selection. In this study, we trying to combine neighborhood size and limited approach using data simulation comparing between two is Akaike Index Criterion (AIC) Bayesian (BIC...