Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The research aims to find approximate solutions for two dimensions Fredholm linear integral equation. Using the two-variables of the Bernstein polynomials we find a solution to the approximate linear integral equation of the type two dimensions. Two examples have been discussed in detail.

   In this paper we obtain some statistical approximation results for a general class of maxproduct operators including the paused linear positive operators.

The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM. 

In contemporary cities, the expansion of the use of vehicles has led to the deterioration of the urban environment. To counter this, many concepts and strategies emerged that attempted to regulate mobility in cities and limit its effects. The concept of a "complete street" is one of the modern trends concerned with diversifying means of transportation and reducing the disadvantages of mechanical transportation methods This paper discusses the role that complete streets can play in developing the urban environment in the Alyarmok District of Baghdad, which suffers from traffic congestion and its associated problems.In this study, 104 people were surveyed in the Alyarmok region, and the linear regression method was used to analyze their op

The removal of chlorpyrifos pesticide from aqueous solutions was achieved by adsorption using low cost agricultural residue as adsorbent surface; barley husks. Several variables that affect the adsorption were studied including contact time, adsorbent weight, pH, ionic strength, particle size and temperature. The absorbance of the solution before and after adsorption was measured by using UV-Visible spectrophotometer. The equilibrium data was suitable with Langmuir model of adsorption and the linear regression coefficient R2 = 0.9785 at 37.5°C was used to knowledge the best fitting isotherm model. The general shape of the adsorption isotherm of chlorpyrifos on barley husks consistent with (H3-type) on the Giles classification. Several

     In this paper, we studied the travelling wave solving for some models of Burger's equations. We used sine-cosine method to solution nonlinear equation and we used direct solution after getting travelling wave equation.

This paper presents the application of a framework of fast and efficient compressive sampling based on the concept of random sampling of sparse Audio signal. It provides four important features. (i) It is universal with a variety of sparse signals. (ii) The number of measurements required for exact reconstruction is nearly optimal and much less then the sampling frequency and below the Nyquist frequency. (iii) It has very low complexity and fast computation. (iv) It is developed on the provable mathematical model from which we are able to quantify trade-offs among streaming capability, computation/memory requirement and quality of reconstruction of the audio signal. Compressed sensing CS is an attractive compression scheme due to its uni

    In this paper, we formulate and study a new property, namely indeterminacy (neutrosophic) of the hollow module. We mean indeterminacy hollow module is neutrosophic hollow module B (shortly Ne(B)) such that it is not possible to specify the conditions for satisfying it.  Some concepts have been studied and introduced, for instance, the indeterminacy local module, indeterminacy divisible module, indeterminacy indecomposable module and indeterminacy hollow-lifting module. Also, we investigate that if Ne(B) is an indeterminacy divisible module with no indeterminacy zero divisors, then any indeterminacy submodule Ne(K) of Ne(B) is an indeterminacy hollow module. Further, we study the relationship between the indeterminacy of hollow an

Molecularly imprinted polymers (MIPs) are an effective method for separating enantiomeric compounds. The main objective of this research is to synthesize D-arabinitol MIPs, which can selectively separate D-arabinitol and its potential application to differentiate it from its enantiomer compound through a non-covalent approach. A macroporous polymer was synthesized using D-arabinitol as a template, acrylamide as a functional monomer, ethylene glycol dimethacrylate (EGDMA) being a cross-linker, dimethylsulfoxide (DMSO) being a porogen, as well as benzoyl peroxide being an initiator. After polymer synthesis, D-arabinitol was removed by a mixture of methanol and acetic acid (4:1, v/v). Fourier-Transform Infrared spectroscopy (FT-IR) and Scan