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    Economic Analysis and Economic Leakage Level in Water Loss Management and Paths for Future Evaluation: A Review
    (Univ Tehran, Coll Engineering, 2022) Firat, M.; Ates, A.; Yilmaz, S.; Ozdemir, O.
    Operational and investment costs increase due to aging of the network, increasing the failure rate, leakage and the water demand, new investments and energy consumption. Several methods and tools with different initial investment and operating costs are proposed for reducing water losses in the related literature. The aim of this study is to make detailed evaluations within the framework of economic components for effective and sustainable water loss management and provide a reference for further studies. The most important advantage is that there has not been a detailed assessment and discussion in this context within the framework of economic analysis and the economic leakage level. The methods and tools for reducing the water losses such as district metered areas, passive leakage control, active leakage control, pressure management, pipe management and network renewal methods, were evaluated economically and discussed. The most important issues in water loss management are the definition of the economic leakage level and the cost components that are the maintenance and break repair, methods applied to detect and control the leaks and automation systems for monitoring, control and data transfer. Moreover, the priority, suitability, applicability and economic impact of the methods should be considered to decide the methods for more efficient use of resources.
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    Optimal Fractional Order PID Controller Design for Fractional Order Systems by Stochastic Multi Parameter Divergence Optimization Method with Different Random Distribution Functions
    (Ieee, 2019) Ates, A.; Alagoz, B. B.; Chen, Y. Q.; Yeroglu, C.; HosseinNia, S. Hassan
    This paper modifies Stochastic Multi Parameter Divergence Optimization Method (SMDO) by using some types of random distribution functions in order to show effects of different random distribution functions on optimization performance. SMDO is a parameter wise random search algorithm in random walk class. A prominent feature of SMDO method lies in using random number with standard uniform distribution while diverging a parameter of solution point in backward and forward directions to reach an optimal solution. SMDO method benefits from the success of random backward and forward divergences. This study investigates effects of four types of random distribution functions on performance of SMDO algorithm for controller tuning problem. These distributions are Chi-Square Distribution (CSD), Rayleigh Distribution (RD), Log Normal Distribution (LND) and Uniform random (LTD) distribution. To illustrate effects of these random distribution functions, SMDO is employed to fractional order PID (FOPID) controller tuning problems for fractional order model (FOM) and results obtained for different distribution functions are demonstrated.