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.
Laurylamine hydrochloride CH3(CH2)11 NH3 – Cl has been chosen from cationic surfactants to produce secondary oil using lab. model shown in fig. (1). The relationship between interfacial tension and (temperature, salinity and solution concentration) have been studied as shown in fig. (2, 3, 4) respectively. The optimum values of these three variables are taken (those values that give the lowest interfacial tension). Saturation, permeability and porosity are measured in the lab. The primary oil recovery was displaced by water injection until no more oil can be obtained, then laurylamine chloride is injected as a secondary oil recovery. The total oil recovery is 96.6% or 88.8% of the residual oil has been recovered by this technique as shown
... Show MoreThis research aims at to identify the extent to which creative thinking skills Impact the change &development of Administrative Leadership styles In Administrative Leadership of the Medical City Department. Identify the nature of the relationship between them, determine the prevailing leadership style, &measure the level of creative thinking skills they have. In order to achieve the objectives of the research, the descriptive analytical method was adopted.
The research tool consisted of a questionnaire consisting of (61) paragraphs, in addition to the interview & observation. The research sample consisted of (170) administrative leaders in the upper &middle organizational levels. The
... Show MoreWith the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.
The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat
... Show MoreEnergy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit
... Show MoreThis study investigated the treatment of dairy wastewater using the electrocoagulation method with iron filings as electrodes. The study dealt with real samples collected from local factory for dairy products in Baghdad. The Response Surface Methodology (RSM) was used to optimize five experimental variables at six levels for each variable, for estimating chemical oxygen demand (COD) removal efficiency. These variables were the distance between electrodes, detention time, dosage of NaCl as electrolyte, initial COD concentration, and current density. RSM was investigated the direct and complex interaction effects between parameters to estimate the optimum values. The respective optimum value was 1 cm for the distance between electrodes, (6
... Show MoreIn this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and
... Show MoreJeder Lernende, der in der Fremdsprache Deutsch kommunizieren möchte, wird sich auch mit der deutschen Aussprache beschäftigen (müssen). Wer eine gute Aussprache hat, wird nicht nur oft und zu Recht bewundert, er hat es auch leichter, die deutsche Sprache zu verstehen, und er wird gut verstanden. Aussprachefehler beeinträchtigen die Kommunikation, sie führen zur Unverständlichkeit von Namen, Wörtern und Äußerungen oder Mißverständnissen, sie bewirken Ermüdung und Konzentrationsverluste und beeinträchtigen die Sprachverarbeitung durch Assoziationen und Emotionen, die beim Hörer entstehen können.’’[1]
Diese vorliegende Forschung befasst sich mit der Wic
... Show MoreThe research dealt with the effect of the tax examiner's efficiency in detecting tax evasion, as the research problem dealt with tax evasion, especially in Iraq, for many reasons and factors, including those related to tax administration represented in administrative corruption and the complexity of procedures in the tax accounting process and failure to achieve justice in the tax treatment, including the taxpayer himself, as he tries to evade for reasons Related to the level of tax awareness, loss of confidence in the tax administration, and reasons related to the state's inability to manage the services file well and its ability to achieve the set goals, This reflected negatively on the emergence of some of the consequences of
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