In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction accuracy criterion and matching curve-fitting in this work demonstrated that if the residuals of the revised model are white noise, the forecasts are unbiased. Future work investigating robust hybrid model forecasting using fuzzy neural networks would be very interesting.
The ground state densities of unstable neutron-rich 8He and 17B exotic nuclei are studied via the framework of the two-frequency shell model (TFSM) and the binary cluster model (BCM). In TFSM, the single particle harmonic oscillator wave functions are used with two different oscillator size parameters βc and βv where the former is for the core (inner) orbits and the latter is for the valence (halo) orbits. In BCM, the internal densities of the clusters are described by single particle Gaussian wave functions. Shell model calculations for the two valence neutrons in 8He and 17B are performed via the computer code OXBASH. The long tail performance is clearly noticed in the calculated neutron and matter density distributions of these nucl
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We produced a study in Estimation for Reliability of the Exponential distribution based on the Bayesian approach. These estimates are derived using Bayesian approaches. In the Bayesian approach, the parameter of the Exponential distribution is assumed to be random variable .we derived bayes estimators of reliability under four types when the prior distribution for the scale parameter of the Exponential distribution is: Inverse Chi-squar
... Show MoreA theoretical model is developed to determine time evolution of temperature at the surface of an opaque target placed in air for cases characterized by the formation of laser supported absorption waves (LSAW) plasmas. The model takes into account the power temporal variation throughout an incident laser pulse, (i.e. pulse shape, or simply: pulse profile).
Three proposed profiles are employed and results are compared with the square pulse approximation of a constant power.
Abstract
Objective of this research focused on testing the impact of internal corporate governance instruments in the management of working capital and the reflection of each of them on the Firm performance. For this purpose, four main hypotheses was formulated, the first, pointed out its results to a significant effect for each of corporate major shareholders ownership and Board of Directors size on the net working capital and their association with a positive relation. The second, explained a significant effect of net working capital on the economic value added, and their link inverse relationship, while the third, explored a significant effect for each of the corporate major shareholders ownershi
... Show MoreIn this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro
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