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Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was checked by comparing it's results with the results of six forecasting models developed for the same data by Al-Suhili and khanbilvardi, 2014.The check of the performance of the new developed model was made for three forecasted series for each variable, using the Akaike test which indicates that the developed model is more successful, since it gave the minimum (AIC) values for (91.67 %) of the forecasted series. This indicates that the developed model had improved the forecasting performance. For the rest of cases (8.33%), other models gave the lowest AIC value, however it is slightly lower than that given by the developed model. Moreover the t-test for monthly means comparison between the models indicates that the developed model has the highest percent of succeed (100%).

 

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Publication Date
Wed May 01 2024
Journal Name
Diamond And Related Materials
A comparative study on the effects of multi-walled carbon nanotubes and graphene nanoplates incorporated for improved thermal conductivity and dielectric properties of polyvinyl chloride
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Publication Date
Sun Sep 15 2019
Journal Name
Al-academy
Role of the Internet in Spreading Rumors Social networking sites "Facebook" model For the duration of 1-7-2017 until 30-11-2017: يوسف محمد حسين
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This study is about the role of the Internet in spreading rumors, especially through social networking sites "Facebook" model as the effectiveness of social networks lies in the speed of transmission of events; these two characteristics are important to the public, making the Internet a strong contender for television and its relationship with the public. That's why we find that the Internet today has become a fertile environment for the growth and spread of rumors. The more limited the platforms and places of publication, the greater the responsibility in the search for the original source in   spreading this or that rumor, as the Internet is considered an easy means in the production, spreading  and re-spreading  of

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Data Mining, Modelling And Management
Association rules mining using cuckoo search algorithm
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Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
A Comparison Between the Theoretical Cross Section Based on the Partial Level Density Formulae Calculated by the Exciton Model with the Experimental Data for (_79^197)Au nucleus
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In this paper, the theoretical cross section in pre-equilibrium nuclear reaction has been studied for the reaction  at energy 22.4 MeV. Ericson’s formula of partial level density PLD and their corrections (William’s correction and spin correction) have been substituted  in the theoretical cross section and compared with the experimental data for  nucleus. It has been found that the theoretical cross section with one-component PLD from Ericson’s formula when  doesn’t agree with the experimental value and when . There is little agreement only at the high value of energy range with  the experimental cross section. The theoretical cross section that depends on the one-component William's formula and on-component corrected to spi

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
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Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p> ... Show More
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Publication Date
Thu Feb 29 2024
Journal Name
Iraqi Journal Of Science
Tigecycline is the Most Effective against Multi-Drug Resistant Klebsiella pneumoniae Recovered from Burn Wound Infections in Two Hospitals in Al-Kut City, Iraq
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     Klebsiella pneumoniae is among the most frequent microorganisms isolated from infections of burn wounds. This cross-sectional study aimed to investigate the distribution of multi-drug resistant (MDR) K. pneumoniae in two burn hospitals and the antibiotic resistance profile in different burn regions of the same patient. It was performed in two hospitals (Al-Zahraa and Al-Karama) in Al-Kut, Iraq, between January and May 2022. Totally, 100 burn swabs were collected from 40 patients of both genders suffering from burn wound infections, with ages ranging between 3 and 50 years. Klebsiella pneumoniae were isolated and identified using conventional methods followed by VITEK®2 system and confirmed via polymerase chain reaction targeting t

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Publication Date
Wed Apr 01 2020
Journal Name
Plant Archive
Genetic analysis of sorghum cultivars from USA using SSR markers
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Publication Date
Thu Jul 25 2019
Journal Name
Advances In Intelligent Systems And Computing
Solving Game Theory Problems Using Linear Programming and Genetic Algorithms
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Publication Date
Mon Mar 01 2010
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Proposed Algorithm for Steganography
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