BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

The relationships between the related parties constitute a normal feature of trading and business processes. Entities may perform parts of their activities through subsidiary entities, joint ventures and associate entities. In these cases, the entity has the ability to influence the financial and operating policies of the investee through control, joint control or significant influence,  So could affect established knowledge of transactions and balances outstanding, including commitments, and relationships with related to the evaluation of its operations by users of financial statements, including the risks and opportunities facing the entity assess the parties. So research has gained importance of the importance of the availability

Swimming has now become the focus of attention of specialists, which has led to the search for the best methods and various methods of training, which rely heavily on scientific research and studies, through the use of proper planning and a comprehensive scientific and practical vision in the preparation and training process for this game. Some studies have proven that  The use of training methods has a positive role in the athletic training of the swimmer, provided that these methods are used in the correct way according to the scientific principles of training and with the loads and stresses that serve the specialized activity, i.e. the swimming distance. The study aimed at the follow 1- Preparing exercises using elastic ro

Cognitive-behavioral therapy is one of the most important relatively recent; treatment programs that attempt to modify behavior and control psychological disorders by modifying the individual's thinking style and awareness of himself and his environment, and cognitive reconstruction by replacing negative thoughts with positive ones. The current study aimed to know the effectiveness of a cognitive behavioral treatment program in reducing nervous fatigue among mothers of children with cerebral palsy. The sample on which the nervous fatigue scale was applied consisted of (30) mothers whose son suffers from cerebral palsy, and the results indicated that (24) mothers suffer from nervous fatigue. This sample was divided

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This research seeks to try to address one of the important issues in society that prevents the state from achieving its social, economic, political and financial goals, represented by the low tax proceeds, through which it can achieve those goals. What is reflected on the tax proceeds, knowing that the General Tax Authority does not take into account the issue of analyzing the opportunity cost of corporate capital as one of the profit indicators when setting the annual controls, which leads to a decrease in the tax proceeds, and therefore the research objective will be to shed light on the importance of adopting the concept of analysis The opportunity cost by the General Tax Authority to achieve a tax proceeds commensurate with t

Abstract: Lymphoproliferative Disorders (LPDs) are a group of neoplasms affecting various cells within lymphoid system. Each type has different treatment a..70619

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo