A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and pH).The objective function adopted in the optimization model is in a form the sum of difference in each of the 5 water quality parameters, resulting from the
mixing equation of the waters of the rivers, from the accepted limits of these parameters , weighted by a penalty factor assigned for each water quality parameter according to its importance. The adopted acceptable limits are 1500,1000, 6,4 and 7, while the penalty factors are 1,0.8,0.8,0.8,and 0.2 for EC,TDS,BOD,DO,and pH respectively. The constraints adopted on the decision variables which the monthly flows of the three rivers are those that provide the monthly demands downstream each river, and not exceed a maximum monthly flow
limits. The maximum flow limits adopted are for three flow cases, wet, average and dry years. For each flow case three scenarios for the monthly water quality parameters were adopted , the average values(scenario 1),the 10% increase in EC,TDS, and BOD (Scenario
2),and the 20% increase in these three water quality parameters (Scenario 3). Hence nine cases are adopted and for each an optimum monthly flows are found for each river. The genetic optimization model adopt a variable number of population of 100 to 1000 in a step of
100,0.8 and 0.2 cross over and mutation rates, and three iterations to reach the stable optimum solutions. The results indicates that the flow analysis shows a significant decrease in the flow values of the three rives after year 2000,hence, the flow values for the period of (1994-1999), are excluded and the only used values are those for (2000-2011). The estimated monthly demands exhibits low variation. The observed optimum monthly flow values decrease in general as the case flow changed from wet to normal and dry cases. The change in Scenarios from S1 to S2 and S3 , do not necessarily increase all the required optimum monthly flow values. The obtained minimum objective functions do not exhibits a certain trend with the change in the flow cases and/or the change in the scenarios.
This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB ) to find the optimal solution
In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior
Coronary artery disease (CAD) is the leading cause of death worldwide. Certain genetic polymorphisms play an important role in this multifactorial disease, being linked with increased risk of early onset CAD.
To assess six genetic polymorphisms and clinical risk factors in relation to early onset nondiabetic Iraqi Arab CAD patients compared to controls.
This case–contro
The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r
... Show MoreThis research aims to analyse the problem of organizations in general and universities in particular, in dealing with �quality subjects� in a world where these organizations face the risks of becoming side lined and possibly vanished without looking for solutions that allow them to move in an open arena where change becomes the key to those solutions. Change here must be strategic and planning must adopts a way for organizations to develop mechanisms to manage change itself. Management leaders play a central role in achieving the principle required to chart new trends for universities in dealing with quality as a strategy that allows excellence and competition in light of the success of the processes of change. Change through reengineer
... Show MoreTwo field experiments were carried out for cultivating yellow maize crop Zea mays L. during the autumn planting season 2019 in two sites with soils of different textures. The first site is a loamy texture in one of the fields of the Medhatia Agriculture Division, Babylon Governorate. The second was silty loam by an alluvial mixture in one of the fields of Al-Nouriah Research Station, Ministry of Agriculture located in Al-Nouriah sub-district, Al-Qadisiyah governorate. It was found through the results that the uniformity, efficiency, and adequacy of the irrigation efficiency of the sprinkler irrigation method is better than that of the sprinkler irrigation method, and it ranged between (88.6-88.7) for uniformity and (84-86)% of the irrigatio
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