This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spent to achieve the best classification accuracy.
The instant global trend towards developing tight reservoir is great; however, development can be very challenging due to stress and geomechanical properties effect in horizontal well placement and hydraulic fracturing design. Many parameters are known to be important to determine the suitable layer for locating horizontal well such as petrophysical and geomechanical properties. In the present study, permeability sensitivity to stress is also considered in the best layer selection for well placement. The permeability sensitivity to the stress of the layers was investigated using measurements of 27 core sample at different confining stress values. 1-D mechanical earth model (MEM) was built and converted to a 3-D full-field geomechanical mode
... Show MoreSurvival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete
... Show MoreDifferent ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
Treatises concerning analyzing the interior spaces multiplied and their directions varied, that some of them analyzed the interior space on the basis of the intellectual and philosophical affiliation or the historical period and others in the light of the concept and mechanisms of the shape. The researcher has not been able to find a research that dealt with analyzing the space within the systems of shape generation, thus it is possible to determine the research problem with the following question: to what extent is it possible to analyze the interior space based on systems of shape generation? As far as the importance of the research is concerned, it sheds light on five of the systems of the shape generation which are: Syntax, shape gra
... Show MoreThe current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1st, 2nd and 3rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition
... Show MoreBig data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an
... Show MoreIn this research, Haar wavelets method has been utilized to approximate a numerical solution for Linear state space systems. The solution technique is used Haar wavelet functions and Haar wavelet operational matrix with the operation to transform the state space system into a system of linear algebraic equations which can be resolved by MATLAB over an interval from 0 to . The exactness of the state variables can be enhanced by increasing the Haar wavelet resolution. The method has been applied for different examples and the simulation results have been illustrated in graphics and compared with the exact solution.
The spectral response of the Si solar cell does not coincidence with the sun irradiance spectrum, so the efficiency of the Si solar cell is not high. To improve the Si solar cell one try to make use of most region of the sun spectrum by using dyes which absorb un useful wavelengths and radiate at useful region of spectrum (by stock shift). Fluorescence's dye is used as luminescent concentrator to increase the efficiency of the solar cell. The results show that the performance efficiency and out power for crystalline silicon solar cells are improved.