The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.
The investigation of natural convection in an annular space between two concentric cylinders partially filled with metal foam is introduced numerically. The metal foam is inserted with a new suggested design that includes the distribution of metal foam in the annular space, not only in the redial direction, but also with the angular direction. Temperatures of inner and outer cylinders are maintained at constant value in which inner cylinder temperature is higher than the outer one. Naiver Stokes equation with Boussinesq approximation is used for fluid regime while Brinkman-Forchheimer Darcy model used for metal foam. In addition, the local thermal equilibrium condition in the energy e
Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show MoreThe combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
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... Show Moreلمعرفة مدى تأثير تمرينات مهارية وفق تقنية تركيز للتفكير الجاني على الدقة الحركة وتعلم هجمة الإيقاف بالغطس للطلاب في سلاح الشيش استخدمت الباحثتان المنهج التجريبي على عينة من طلاب المرحلة الثالثة بكلية التربية البدنية وعلوم الرياضة –جامعة ديالى والتي بلغت (30) طالباً موزعين على مجموعتين التجريبية والضابطة وبعد إكمال اجراءات البحث وتطبيق الاختبارات القبلية وتنفيذ التمرينات والاختبار البعدي ومعالجة الب
... Show MoreThe research included preparation of new Schiff base (L) by two steps: preparation of precursor [bis(2-formyl-6-methoxyphenyl) succinate] (P) by reacting (3-methoxy salicyl aldehyde) with (succinoyl dichloride) as first step then react the prepared precursor (P) with (ethanethioamide) to have the new Schiff base [bis(2-((ethane thioyl imino) methyl)-6-methoxy phenyl) succinate] (L) as second step. Characterized compounds based on Mass spectra, 1 H, 13CNMR (for ligand (L)), FT-IR and UV spectrum, melting point, molar conduct, %C, %H, and %N, the percentage of the metal in complexes %M, magnetic susceptibility, while study corrosion inhibition (mild steel) in acid solution by weight loss. These measurements proved that by (Oxygen, Nitrogen, a
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