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.
Background: Salivary biomarkers, a non-invasive alternative method to serum and tissue based biomarkers and it is consider as an effective modality for early diagnosis. Salivary microRNA 21, a nucleotide biomarker, was reported to increase in patients with oral squamous cell carcinoma. This study was conducted to measure the fold change of microRNA 21 in stimulated saliva and to study its association with smoking and occurrence of oral squamous cell carcinoma. Materials and methods: A 20 patients with oral squamous cell carcinoma who used to be smokers was included in addition to 40 control subjects (20 smokers and 20 non- smokers health looking subjects). Stimulated saliva was collected under standardized condition. Salivary microRNA 21 wa
... Show MoreThis article aims to determine the time-dependent heat coefficient together with the temperature solution for a type of semi-linear time-fractional inverse source problem by applying a method based on the finite difference scheme and Tikhonov regularization. An unconditionally stable implicit finite difference scheme is used as a direct (forward) solver. While by the MATLAB routine lsqnonlin from the optimization toolbox, the inverse problem is reformulated as nonlinear least square minimization and solved efficiently. Since the problem is generally incorrect or ill-posed that means any error inclusion in the input data will produce a large error in the output data. Therefore, the Tikhonov regularization technique is applie
... Show MoreThe city has normal natural state, and the man has a usual movement, change and search for the new .Also, the city has a usual change and transform in its time, place and quality (sizes)structures. The city has a solid memory diving into the past and the future and reflects The real present, and this memory has a timing layers change into real materialistic place making the city has accumulated overlapping circles which is hard to break u , and it broadcasts the lockup timing density ,in which there is no visual record precisely, it is just like((the social record)) that evaluates the un visual relationships between the components and parts of the city (community and form) in a visual quiet exhibition and transform change inside.
... Show MoreLive the present companies in a competitive business environment going on and try to achieve excellence in their industry through the marketing of their products and achieve greater market share as possible to ensure its continued existence, and perhaps the concept of time production, which confirms, in essence, on the need to reduce inventory to a minimum in the production process as well as the concept of the marketing information system which asserts, in essence, to document all the events that are related to the marketing of the product provided by the production process, together constitute the subject deserves research and investigation as they have raised well-known in the fields of production management and marketing management.
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MorePower switches require snubbing networks for driving single – phase industrial heaters. Designing these networks, for controlling the maximum allowable rate of rise of anode current (di/dt) and excessive anode – cathode voltage rise (dv/dt) of power switching devices as thyristors and Triacs, is usually achieved using conventional methods like Time Constant Method (TCM), resonance Method (RM), and Runge-Kutta Method (RKM). In this paper an alternative design methodology using Fuzzy Logic Method (FLM) is proposed for designing the snubber network to control the voltage and current changes. Results of FLM, with fewer rules requirements, show the close similarity with those of conventional design methods in such a network of a Triac drivin
... Show MoreThe software-defined network (SDN) is a new technology that separates the control plane from data plane for the network devices. One of the most significant issues in the video surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the video from the cameras. In this paper, two methods are proposed to solve this problem. The first method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).
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