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An efficient artificial fish swarm algorithm with harmony search for scheduling in flexible job-shop problem
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Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best solution. When it is the better one, it replaces with the artificial fish swarm solution from which this solution was improvised. Meanwhile the best improvised solutions are carried over to the Harmony Memory. The objective is to minimize a total completion time (makespan) and to make the proposed approach as a portion of the expert and the intelligent scheduling system for remanufacturing decision support. Harmony search algorithm has demonstrated to be efficient, simple and strong optimization algorithm. The ability of exploration in any optimization algorithm is one of the key points. The obtained optimization results show that the proposed algorithm provides better exploitation ability and enjoys fast convergence to the optimum solution. As well, comparisons with the original artificial fish swarm algorithm demonstrate improved efficiency.

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Treatability influence of municipal sewage effluent on surface water quality assessment based on Nemerow pollution index using an artificial neural network
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Abstract<p>Assessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem</p> ... Show More
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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Building a mathematical model of the transportation problem under the dynamics of demand restrictions with practical application
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Abstract\

In this research we built a mathematical model of the transportation problem  for data of General Company for Grain Under the environment of variable demand ,and situations of incapableness to determining the supply required quantities as a result of economic and commercial reasons, also restrict flow of grain amounts was specified to a known level by the decision makers to ensure that the stock of reserves for emergency situations that face the company from decrease, or non-arrival of the amount of grain to silos , also it took the capabilities of the tanker into consideration and the grain have been restricted to avoid shortages and lack of processing capability, Function has been adopted

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Three-Dimensional Finite Element Simulation of the Buried Pipe Problem in Geogrid Reinforced Soil
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Buried pipeline systems are commonly used to transport water, sewage, natural oil/gas and other materials. The beneficial of using geogrid reinforcement is to increase the bearing capacity of the soil and decrease the load transfer to the underground structures.

This paper deals with simulation of the buried pipe problem numerically by finite elements method using the newest version of PLAXIS-3D software. Rajkumar and Ilamaruthi's study, 2008 has been selected to be reanalyzed as 3D problem because it is containing all the properties needed by the program such as the modulus of elasticity, Poisson's ratio, angle of internal friction. It was found that the results

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Publication Date
Sat Dec 31 2022
Journal Name
Mathematical Modelling Of Engineering Problems
Experimental and Numerical Study of Open Channel Flow with T-Section Artificial Bed Roughness
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Experimental and numerical studies have been conducted on the effects of bed roughness elements such as cubic and T-section elements that are regularly half-channel arrayed on one side of the river on turbulent flow characteristics and bed erosion downstream of the roughness elements. The experimental study has been done for two types of bed roughness elements (cubic and T-section shape) to study the effect of these elements on the velocity profile downstream the elements with respect to different water flow discharges and water depths. A comparison between the cubic and T-section artificial bed roughness showed that the velocity profile downstream the T-section increased in smooth side from the river and decrease in the rough side

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Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Mon Jan 01 2024
Journal Name
Studies In Systems, Decision And Control
The Effect of Using an Accounting Information System Based on Artificial Intelligence in Detecting Earnings Management to Enhance the Sustainability of Economic Units
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This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

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Publication Date
Sat May 23 2026
Journal Name
Advances In Life Science And Technology
The Effect of Preservatives and Freezing on Museum Saved Fish Samples
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Two means used for saving fish samples, namely Freezing and Preservatives represented by Alcohol and Formalin. The Freezing was used in saving samples collected newly, in addition to use Alcohol and Formalin with different concentrations 70% of Alcohol and 10% of Formalin. The concentrations of some heavy metal elements were examined, such as Potassium, Phosphorus, Calcium, Manganese, Magnesium, Zinc, Iron, Copper and Boron in samples saved in Formalin and Alcohol and frozen at different durations. The concentration of some elements has been changed during the saving duration. The study was performed on the concentration of heavy elements in the Liza abu muscles of saved and frozen fish.

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach
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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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Publication Date
Tue Dec 01 2009
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
RECORD OF TWO SPECIES OF THE MONOGENETIC TREMATODES GENUS DACTYLOGYRUS FOR THE FIRST TIME IN IRAQ ON GILLS OF THE CYPRINID FISH ALBURNUS CAERULEUS
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For the first time in Iraq, two species of monogenetic tretamtodes of the genus Dactylogyrus were recorded from gills of Alburnus caeruleus from Tigris river at Al-Zaafaraniya, south of Baghdad during June 1995. The first species, Dactylogyrus sphyrna is characterized by having the seventh pair of marginal hooklets almost twice as large as other marginal hooklets, powerful inner and outer processes of median hooks especially the inner one which is expanded terminally, one connecting bar and long spirally twisted copulatory organ. The second species, Daclytogyrus phoxini differs from the first one by having marginal hooklets of the same size, inner and outer processes of median hooks are not powerful, two connecting bars

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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