In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.

Aim: This abstract aims to highlight the critical nature of climate change as a pressing challenge facing humanity in the 21st century. It underscores the severe consequences it poses to essential facets of human existence, including water and energy resources, agricultural production, and the broader environmental systems. Method: The abstract primarily utilizes a descriptive approach to emphasize the impact of climate change on the Middle East, particularly the Arab region. It relies on a review of existing knowledge and data related to climate change and its effects on ecosystems and drought patterns. Results: The abstract outlines the direct and indirect repercussions of climate change on human life and the environment. It draws atten

The study's primary purpose is to explore an appropriate way of monitoring and assessing water depths using the satellite remote sensing technique of the Al Habbaniyah Lake in Iraq. This research studied the experience-conditions (thresholds) of different bands for multi-temporal satellite image data with different satellite image sensors (Landsat 5-TM, and EO1-ALI) for the same region, to recognize regions of water depths. The threshold values are taken that to separate the Al Habbaniyah Lake to the required depths (shallow, deep, and very deep), as a supervised method. A three-dimension feature space plot had used to represent these regions. The relationship of the mean values of the three separated water regions with all TM and A

The monetary policy is a vital method used in implementing monetary stability through: the management of income and adjustment of the price (monetary targets) in order to promote stability and growth of real output (non-cash goals); the tool of interest rate and direct investment guides or movement towards the desired destination; and supervisory instruments of monetary policy in both quantitative and qualitative. The latter is very important as a standard compass to investigate the purposes of the movement monetary policy in the economy. The public and businesses were given monetary policy signals by those tools. In fiscal policy, there are specific techniques to follow to do the spending and collection of revenue. This is done in order to

Background. The use of modern aids and technology has contributed greatly to football development, the goalkeeper is the most important position in the team, and the use of devices gave objective readings about the goalkeeper's ability in terms of skill and physical aspects. Objectives. The research aimed to prepare exercises using an electronic device to measure the knee bending angle because of its great importance in developing the skill of catching and dimensions of the high ball for football goalkeepers. Methods. The researchers used the experimental method, and the sample consisted of (4) male goalkeepers under 15 years of age, one of the research procedures was to determine the biomechanical variables affecting the development of the

In this research we prepared shiff bases unilateral claw( benzyl imine aniline ) and Bilateral claw ( benzayal-2-imine phenol ) in high purity reach to 98% , which it's prepared from aromatic amine with aldehydes, it's solid,thermosetting, not dissolved in water in general. Diagnosed prepared article by using infra red spectroscopy (IR) which shows azomethen grop at 1640cm-1 At this diagnosis we suggest tetra headral mechanism in this Circumstances For a reaction.

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Election study included four sites for the waters in area of Youssifiyah south of Baghdad (river water, tank water, liquefactions water, and water filtrate and seethed and purifier by alum and chloride), the samples were collected during the month of June in 2007. Temperature, electrical conductivity and acidity are measured. Also , the concentration of chloride , sulphate , carbonate , nitrate , sodium , calcium , magnesium , hard total and total dissolved substances are determined , as well as heavy metals assess environmental risk (such as Cu, Pb, Zn, Fe). It was also a study of bacterial totals included both total Bacteria (TB) and Total Coliform Bacteria (TC) and Fecal Coliform (FC) and Fecal Streptococci (FS). The stu