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 absolute mean square error were also used to measure the accuracy of the estimation for methods used. The important result obtained in this paper is that the optimal neural network was the Backpropagation (BP) and Recurrent neural networks (RNN) to solve time series, whether linear, semilinear, or non-linear. Besides, the result proved that the inefficiency and inaccuracy (failure) of RBF in solving nonlinear time series. However, RBF shows good efficiency in the case of linear or semi-linear time series only. It overcomes the problem of local minimum. The results showed improvements in the modern methods for time series forecasting.
Regression analysis models are adopted by using SPSS program to predict the 28-day compressive strength as dependent variable and the accelerated compressive strength as independent variable. Three accelerated curing method was adopted, warm water (35ºC) and autogenous according to ASTM C C684-99 and the British method (55ºC) according to BS1881: Part 112:1983. The experimental concrete mix design was according to ACI 211.1. Twenty eight concrete mixes with slump rang (25-50) mm and (75-100)mm for rounded and crushed coarse aggregate with cement content (585, 512, 455, 410, 372 and 341)Kg/m3.
The experimental results showed that the acc
... Show MoreThe gravity method is a measurement of relatively noticeable variations in the Earth’s gravitational field caused by lateral variations in rock's density. In the current research, a new technique is applied on the previous Bouguer map of gravity surveys (conducted from 1940–1950) of the last century, by selecting certain areas in the South-Western desert of Iraqi-territory within the provinces' administrative boundary of Najaf and Anbar. Depending on the theory of gravity inversion where gravity values could be reflected to density-contrast variations with the depths; so, gravity data inversion can be utilized to calculate the models of density and velocity from four selected depth-slices 9.63 Km, 1.1 Km, 0.682 Km and 0.407 Km.
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Communication attribution is a condition of the validity of the hadeeth and that each narrator heard from his Sheik.There are some of the narrators who said to hear who told him and his contemporary, and this narrator is also innocent of the stigma of fraud, but this hearing has no truth.
This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
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This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine
... Show MoreThe compliance is considered
This study aimed to deduce the net atrioventricular compliance which is affected the trans mitral blood flow.
This study focuses on study group of 25 patients (15 males
In this research, the problem of ambiguity of the data for the project of establishing the typical reform complex in Basrah Governorate was eliminated. The blurry of the data represented by the time and cost of the activities was eliminated by using the Ranking function and converting them into normal numbers. Scheduling and managing the Project in the Critical Pathway (CPM) method to find the project completion time in normal conditions in the presence of non-traditional relationships between the activities and the existence of the lead and lag periods. The MS Project was used to find the critical path. The results showed that the project completion time (1309.5) dinars and the total cost has reached (33113017769) dinars and the
... Show MoreDiesel engine oil was subjected to thermal oxidization (TO) for six periods of time (0 h, 24 h, 48 h, 72 h, 96 h, and 120 h) and was subsequently characterized by terahertz time domain spectroscopy (THz-TDS). The THz refractive index generally increased with oxidation time. The measurement method illustrated the potential of THz-TDS when a fixed setup with a single cuvette is used. A future miniaturized setup installed in an engine would be an example of a fixed setup. For the refractive index, there were highly significant differences among the oxidation times across most of the 0.3–1.7 THz range.