A multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is of two variables, three sites, the variables are the monthly rainfall and evaporation; the sites are Sulaimania, Dokan, and Darbandikhan.. The model form is similar to the first order auto regressive model, but in matrices form. A matrix for the different relative correlations mentioned above and another for their relative residuals were derived and used as the model parameters. A mathematical filter was used for both matrices to obtain the elements. The application of this model indicates i

Physically based modeling approach has been widely developed in recent years for the simulation of dam failure process due to the lack of field data. This paper provides and describes a physically-based model depending on dimensional analysis and hydraulic simulation methods for estimating the maximum water level and the wave propagation time from breaching of field test dams. The field physical model has been constructed in Dabbah city to represent the collapse of the Roseires dam in Sudan. Five cases of a dam failure were studied to simulate water flood conditions by changing initial water height in the reservoir (0.8, 1.0, 1.2, 1.4 and 1.5 m respectively).The physical model working under five cases, case 5 had the greatest influence of t

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

The result of a developed mathematical model for predicting the design
parameters of the fiber Raman amplifier (FRA) are demonstrated. The amplification
parameters are tested at different pump power with different fiber length. Recently,
the FRA employed in optical communication system to increase the repeater distance
as will as the capacity of the communication systems. The output results show, that
high Raman gain can be achieved by high pumping power, long effective area that
need to be small for high Raman gain. High-stimulated Raman gain coefficient is
recommended for high Raman amplifier gain, the low attenuation of the pump and the
transmitted signal in the fiber lead to high Raman gain.

The Zubair reservoir in the Abu-Amood field is considered a shaly sand reservoir in the south of Iraq. The geological model is created for identifying the facies, distributing the petrophysical properties and estimating the volume of hydrocarbon in place. When the data processing by Interactive Petrophysics (IP) software is completed and estimated the permeability reservoir by using the hydraulic unit method then, three main steps are applied to build the geological model, begins with creating a structural, facies and property models. five zones the reservoirs were divided (three reservoir units and two cap rocks) depending on the variation of petrophysical properties (porosity and permeability) that results from IP software interpr

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

Lacing reinforcement plays a critical role in the design and performance of reinforced concrete (RC) slabs by distributing the applied loads more evenly across the slab, ensuring that no specific area of the slab is overloaded. In this study, nine slabs, divided into three groups according to the investigated parameters, were meticulously designed and evaluated to study the interplay between the lacing reinforcement and other key parameters. Each slab was crafted for simple support and was subjected to both static and repeated two-point load tests. The lacing reinforcement had an angle of 45° with various tension and lacing steel. The repeated-tested specimens with lacing reinforcement experienced smaller ductility than those of s