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.
The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics an
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This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m
... Show MoreObjective: The study aimed to determine quality of life domains for adult patients with limbs loss and to identify
the association between quality of life domains and demographic characteristics and medical information.
Methodology: A descriptive study was carried out at Baghdad artificial limb center, Al-Salam medical
rehabilitation center, Al-Ghadeer medical rehabilitation center and the rheumatoid and medical rehabilitation
center for the period from September 2007 to April 2008. A purposive ''non- probability'' sample of (200)
patients with limbs loss. Questionnaire form was constructed for the purpose of the study. Data were collected
through the application of the questionnaire and interview technique. Data were a
This study deals with the role of compensation system in improving the quality of educational services (University of Halabja as a Model) also our problem was the following question ; What is the role of compensation system in its different dimensions in improving the quality of educational services? And what is the relationship and impact of using the dimensions of the compensation system to improve the quality of educational services? The hypothesis of the research included the correlation and the impacts between the compensation system and its combined variables in the quality of educational services. This was proved through a field study and the distribution of questionn
... Show MoreMonitoring the river’s water quality is important to predict the environmental risk. The Tigris River is Baghdad’s main source for living organisms, drinking water, and agro-industrial purposes. Three selected sites were carried out using different water quality parameters from July 2017 to April 2018 in the Tigris River in Baghdad. Fourteen water quality parameters: water temperatures, turbidity, electrical conductivity, pH, calcium, magnesium, chloride, sulfate, phosphate, dissolved oxygen (DO), alkalinity, total hardness, total dissolved substances TDS, and biological oxygen demand (BOD5). According to CCME WQI analysis, the water quality of Tigris River water was Fair for aqua
Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.
There has been a great deal of research into the considerable challenge of managing of traffic at road junctions; its application to vehicular ad hoc network (VANET) has proved to be of great interest in the developed world. Dynamic topology is one of the vital challenges facing VANET; as a result, routing of packets to their destination successfully and efficiently is a non-simplistic undertaking. This paper presents a MDORA, an efficient and uncomplicated algorithm enabling intelligent wireless vehicular communications. MDORA is a robust routing algorithm that facilitates reliable routing through communication between vehicles. As a position-based routing technique, the MDORA algorithm, vehicles' precise locations are used to establish th
... Show MoreBackground The Transportation Problem (TP) is a detailed model in operations study with applications in logistics, supply chain management, and resource allocation. The classical IBFS methods including North-West Corner, Least Cost and Vogel’s Approximation have competitive computational efficiency, but they are very sensitive to the structure of the problem and usually lead to a solution that is far from the global optimum. Classic enhancement strategies like the Generalized Distribution (MODI) and Stepping-Stone (SS) approaches have low computational complexity but may fall into a local optimum quickly, which makes them ineffective in large-scale or unbalanced problems. Methods We propose the first generic hybrid algorithm, calle
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