Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colony algorithm or bees algorithm or a swarm of birds and other originally used algorithm for the purposes of technology pertaining to distinguish between images or signals and others can be illustrated to serve the Census and check successful at it. So the choice fell on the genetic algorithm which often applied in the biology science on the subject of the analysis of DNA and genetic engineering within the modern trends of Medical Science. Proposal genetic algorithm was developed, along with C4.5 algorithm. Having been in this research integrating the work of all these algorithms mechanism Generalized Additive model to estimate some nonparametric function. Simulation was used to demonstrate the classification optimization using misclassification error and prove estimation optimization by the root mean of squares error: RMSE. The simulation has to experiment samples sizes (200, 400, 600) and (1000) replications
BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
Genus Eucalyptus belongs to the family Myrtaceae that consists of more than 700 species, various hybrids and varieties. The majorly distributed species that are grown in Iraq are Eucalyptus alba, E. macarthurii, E. siderophloia and E. camaldulensis, E. tereticornis, E. vicina. Most Eucalyptus species are highly dependent on rainfall, and this is challenged by climatic changes owing to global warming making it difficult to effectively match the availability of mature trees and the market demand, especially for use as power transmission poles. With the widespread availability of other naturally occurring Eucalyptus species, it has become important to determine the genetic diversity and to analyze the phenotypic tra
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The objective review is to inspect the involvement of Interleukin-6 (IL-6) in rheumatoid arthritis (RA) and to highlight the role of IL-6 and its variants in the pathogenesis of RA and response to anti-IL-6 agents. Several genetic and environmental risk factors and infectious agents contributed to the development of RA. Interleukin-6 is engaged in self-targeted immunity by modifying the equilibrium between T regulatory (T-reg) and T helper-17 (Th-17) cells. The evidences reported that IL-6 parti
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Through recent years many researchers have developed methods to estimate the self-similarity and long memory parameter that is best known as the Hurst parameter. In this paper, we set a comparison between nine different methods. Most of them use the deviations slope to find an estimate for the Hurst parameter like Rescaled range (R/S), Aggregate Variance (AV), and Absolute moments (AM), and some depend on filtration technique like Discrete Variations (DV), Variance versus level using wavelets (VVL) and Second-order discrete derivative using wavelets (SODDW) were the comparison set by a simulation study to find the most efficient method through MASE. The results of simulation experiments were shown that the performance of the meth
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The research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests
... Show MoreSocieties developed throughout history with the development of life technology, that ideas presented by the contemporary art have been crystallized. The development included all the artistic fields such as the dramatic arts which depend on many effects and elements that led to the completion of the structure of the theater show. Scenography is considered one of the most important elements that the theatre show depends on such as the decoration, lighting, sound effects, costumes and accessories. The research addressed the following question: what are the characteristics and traits of scenography in the theatre show?
The research importance has become clear because it sheds lights on the characteristics of scenography in the Iraqi thea
In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using the simulation.
This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time t . The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integrated with the FD method t
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