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Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably improved prediction of dispersed phase hold up. The developed correlation also
shows better prediction over a wide range of operation parameters in RDC columns.

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
...Show More Authors

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Scopus (10)
Scopus
Publication Date
Thu Sep 01 2022
Journal Name
Computers And Electrical Engineering
Automatic illness prediction system through speech
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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
Modifying Hebbian Network for Text Cipher
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The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. This work modernize the feedforward neural network, so the secret message will be encrypted by unsupervised neural network method to get the cipher text that can be decrypted using the same network to get the original text. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding lengths. In this work, the key is the final weights

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Publication Date
Sat Apr 02 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of Artificial Intelligence in achieving Ambidextrous Performance A case study in a sample of private banks
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The research aims to shed light on the role of artificial intelligence in achieving Ambidexterity performance, as banks work to take advantage of modern technologies, artificial intelligence is an innovation that is expected to have a long-term impact, as well as banks can improve the quality of their services and analyze data to ensure that customers' future needs are understood. . The Bank of Baghdad and the Middle East Bank were chosen as a community for the study because they had a role in the economic development of the country as well as their active role in the banking market. A sample of department managers was highlighted in collecting data and extracting results based on the checklist, which is the main tool for the stu

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Publication Date
Fri Aug 01 2014
Journal Name
Int. J. Mod. Eng. Res
Exact solutions for MHD flow of a viscoelastic fluid with the fractional Burgers’ model in an annular pipe
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This paper presents an analytical study for the magnetohydrodynamic (MHD) flow of a generalized Burgers’ fluid in an annular pipe. Closed from solutions for velocity is obtained by using finite Hankel transform and discrete Laplace transform of the sequential fractional derivatives. Finally, the figures are plotted to show the effects of different parameters on the velocity profile.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
On Training Of Feed Forward Neural Networks
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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.

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Publication Date
Mon Feb 19 2018
Journal Name
Al-academy
The Mechanisms of build up the dramatic construction in the films of the world of nature - National Geographic's films as a model-
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The subject of  research entitled "The Mechanisms of build up the dramatic construction in the films of the world of nature - National Geographic's films as a model" emerges from the importance of the subject of the dramatic construction and its departure from its classic style due to the evolution of the visual  presentation and its instruments and the specificity and emergence of a form of television production represented by the films of the world of nature which began to occupy an important space in the map of television and television channels specialized in this subject, which drove the researcher to study the mechanisms of producing the dramatic construction in this kind of film s. This research came in three  chapt

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Publication Date
Thu Dec 15 2022
Journal Name
Al-academy
The art of adornment and make-up in the ancient civilizations of Mesopotamia and the old country of Yemen as a model
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This research sheds light on those discrepancies in the use of ornaments, adornment and perfumes, as well as the art of cosmetics, in two important civilizations, namely, the Mesopotamian civilization as the earlier civilization, and the civilization of Yemen, which represents the first Arab civilization. Through the foregoing, our research includes two topics, the first topic included the history of the use of decorations, ornaments and perfumes in the civilization of Mesopotamia, while the second topic included the study of ornaments, adornment and cosmetic art in the ancient civilization of Yemen. And then the research came out with a number of conclusions that the researcher considers very important to highlight the differences and f

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Publication Date
Thu Dec 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Shear Wave velocity for carbonate rocks
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In many oil fields only the BHC logs (borehole compensated sonic tool) are available to provide interval transit time (Δtp), the reciprocal of compressional wave velocity VP.

   To calculate the rock elastic or inelastic properties, to detect gas-bearing formations, the shear wave velocity VS is needed. Also VS is useful in fluid identification and matrix mineral identification.

   Because of the lack of wells with shear wave velocity data, so many empirical models have been developed to predict the shear wave velocity from compressional wave velocity. Some are mathematical models others used the multiple regression method and neural network technique.

   In this study a number of em

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