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.
Prodigiosin is a ‘natural red pigment produced by Serratia marcescens which exhibits immunosuppressive and anticancer properties in addition to antimicrobial activities. This work presents an attempt to maximize the production of prodigiosin by two different strategies: one factor at time (OFAT) and statistical optimization. The result of OFAT revealed that sucrose and peptone were the best carbon and nitrogen sources for pigment production with concentration of prodigiosin of about 135 mg/ L. This value was increased to 331.6mg/ L with an optimized ratio of C/N (60:40) and reached 356.8 with pH 6 and 2% inoculum size at end of classical optimization. Statistical experimental design based on Response surface methodology was co
... Show MoreThe research dealt with the study of the element of time in the cinematic language and the role it plays in creating the aesthetic meanings in the documentary film by means of the various structural constructions with which time is constructed. The research included the introduction and the problem of research, which was represented by the following question: (Did the documentary film adopt the values of time formats in the fiction film or it created for itself special linguistic formulations and models which achieve the aesthetic concept?). It also included the importance of research, the need for it and its goal in addition to clarifying the limits of research.The theoretical framework included three sections the first of which is the
... Show MorePeriodontal disease is typically treated with mechanical debridement of the tooth surface. It may, however, be insufficient to eradicate pathogenic microorganisms on its own. Because of the microbial etiology of periodontitis, systemic or local antibiotic therapy is used as an adjunct treatment. The present study aimed to determine the effects of curcumin gel on Porphyromonas gingivalis. Eleven patients with stage II and III periodontitis were registered in the study. A double-blinded split-mouth design followed. Periodontal pockets were distributed into 2 groups; the test group received scaling and root planing along with curcumin gel, while the control group received scaling and root planing along with a placebo gel. Plaque index,
... Show MoreThe research aims to determine the strength of the relationship between time management and work pressure and administrative leadership, where he was taken a sample of (47) of the administrative leadership at the Higher Institute of security and administrative development in the Ministry of Interior was used questionnaire as a key tool in collecting data and information and analyzed the answers to the sample surveyed by using Statistical program (spss) in the arithmetic mean of the calculation and test (t) and the correlation coefficient, the research found the most important results: the existence of significant moral positive relationship between both time management and work pressure and administrative leadership, the leadership of th
... Show MoreThe main aim of this research study is to point out the vital importance of high-quality exterior audits to limit discretionary accounting, as it could distort a company’s commercial results. The research introduces a well-founded hypothesis on the preventive powers of high-quality audits, as it can act as a strong exterior control. The research focuses on testing the complex relationship between earnings management and investors’ behavior within the public-listed companies from the food industry. The research gathers credible annual comprehensive data from thirty-five publicly-listed firms from the United States. It encompasses the twenty years prior to 2024, as it includes the twenty years prior to 2024. Additionally, the gathered dat
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreIn this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame