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Complementary data-intelligence model for river flow simulation

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Publication Date
Wed Jun 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Mechanical Engineering
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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Some Estimation methods for the two models SPSEM and SPSAR for spatially dependent data

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In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

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Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
The extent of including logical intelligence in the Book of chemistry for the fifth Grade of science

The aim of the current research to determine the extent of logical intelligence in the book of chemistry for the fifth grade of science and to achieve the goal the researcher has prepared a special criterion in the areas of logical intelligence main and sub-to be included in the book after reviewing the previous literature and studies in this regard may be the final form after presentation to experts and arbitrators in the field of Educational and psychological sciences, curricula and teaching methods from (3) main areas and (21) sub-fields, then the researcher analyzed the book Bibih and applied branches and adopted the idea of ​​both explicit and implicit as a unit of registration and repet

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Publication Date
Wed Nov 20 2024
Journal Name
Journal Of Administration And Economics
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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
An Artificial Intelligence-based Proactive Network Forensic Framework

     is at an all-time high in the modern period, and the majority of the population uses the Internet for all types of communication. It is great to be able to improvise like this. As a result of this trend, hackers have become increasingly focused on attacking the system/network in numerous ways. When a hacker commits a digital crime, it is examined in a reactive manner, which aids in the identification of the perpetrators. However, in the modern period, it is not expected to wait for an attack to occur. The user anticipates being able to predict a cyberattack before it causes damage to the system. This can be accomplished with the assistance of the proactive forensic framework presented in this study. The proposed system combines

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Engineering
Intelligence in Construction between Contemporary and Traditional Architecture

The authentic traditional architecture proved that it is very convenient to the environmental and social regulations where it appeared and lasted for hundred of years.

This traditional architecture got the intelligence in providing thermal comfort for their occupants by the intelligent usage of the building materials and the intelligent planning and designs which took in consideration the climatic condition and the aerodynamics of the whole city as one ecological system starting from the cold breeze passing through its narrow streets till it enters the dwelling units and glides out through the wind catchers.

This architecture had been neglected and replaced by modern imported architecture which had collap

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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Publication Date
Mon Jan 01 2024
Journal Name
Pathology - Research And Practice
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