Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin’s method), The nonparametric model is estimated by using kernel smoothing (Nadaraya Watson), K-Nearest Neighbor smoothing and Median smoothing. The Flower Pollination algorithms were employed and structured in building the ecological model and estimating the semi-parametric regression function with measurement errors in the explanatory and dependent variables, then compare the models to choose the best model used in the environmental scope measurement errors, where the comparison between the models is done using the mean square error (MSE).
The virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr
The utilization of carbon dioxide (CO₂) to enhance wellbore injectivity presents a cost-effective and sustainable strategy for mitigating greenhouse gas emissions while improving reservoir performance. This study introduces an environmentally friendly method employing a water-soluble chitosan salt (CS) that generates a carbonated-rich acid solution upon contact with dry CO₂ at 25 °C and 508 psi. CS solutions (100–2000 ppm) were prepared and evaluated for CO₂ uptake, acid generation, and rheological behavior. Results show that 1000 ppm achieves an optimal CO2 uptake (2612 mg/l), with moderate viscosity increase (from 1.52 to 3.37 cp), while higher concentrations exhibit a sharp rise due to polymer-like network formation. Core floodi
... Show MoreA fracture is a damage to bone tissue that causes damage to the tissue surrounding the bone and may penetrate the skin. Subjects and methods: the present study included (80) fractured Iraqi patients (and 40) patients with DM2 and (40) without DM2 and compared them with (40) healthy control. Patients and control are matched in age. This study showed a significant increase in retinol-binding protein 4 (RBP4) and a considerable decrease in Vit .A GPT and GOT in fracture patients with and without DM2. In addition, there was a significant negative correlation between RBP4 with (GPT and GOT) in fracture patients with DM2 and a significant positive correlation between RBP4 with (GPT and GOT) in fracture patients without DM2.
... Show MoreBackground: Recent research indicates that persistent inflammatory responses may contribute to the rise of diabetic nephropathy (DN) and diabetic cardiovascular disease (DCVD) in type 2 diabetes mellitus patients (DM2). Numerous molecules associated with inflammation and angiogenesis have been implicated in the development and progression of DN and DCVD, respectively. Methods: The subjects were separated into five groups: healthy controls (n= 25), type 2 diabetes mellitus patients (n= 30), type 2 diabetes mellitus patients with nephropathy DN (n= 30), and type 2 diabetes mellitus patients with cardiovascular disease DCVD (n= 30). The blood levels of irisin, IL-8, HbA1C, urea, and creatinine were determined. Results: In current study there w
... Show MoreThe study using Nonparametric methods for roubust to estimate a location and scatter it is depending minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .
It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu
... Show MoreIn this research the activity of radon gas in air in Baghad governorate,Iraq, using “alpha-emitters track registration (CR-39) track detector were measured. This measurement was done for selected areas from Baghdad Governorate, The results obtained shows that the highest average concentrations for Rn-222 is (179.077 Bq/m^3) which was recorded within Al-Shaaib city and less average concentrations was (15.79 Bq/m^3) in the nearby residential area of Baghdad International Airport and the overall average concentrations is (86.508 Bq/m^3) for these regions. Then the radon concentration was measured annual effective dose calculated from radon concentration and found in range from 0.4031 mSv/y to 4.5179 mSv /y with an average value of 2.1824 m
... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
... Show MoreEstimation of the tail index parameter of a one - parameter Pareto model has wide important by the researchers because it has awide application in the econometrics science and reliability theorem.
Here we introduce anew estimator of "generalized median" type and compare it with the methods of Moments and Maximum likelihood by using the criteria, mean square error.
The estimator of generalized median type performing best over all.
In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf
... Show MoreHydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined. There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements. The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more accurate t
... Show More