Introduction: prediction the per capita health expenditures can be useful and effective in determining the best policies for financing and managing of health expenditures. Accordingly, the main objective of this study was to predict the per capita health expenditures tr More
Introduction: prediction the per capita health expenditures can be useful and effective in determining the best policies for financing and managing of health expenditures. Accordingly, the main objective of this study was to predict the per capita health expenditures trend in Iran. Methods: In this paper, we specified a health expenditure model relying on theoretical basics in order to obtain desirable forecasts. On the basis of three forms of linear, exponential and quadratic equations and using theoretical foundations in the field of per capita health expenditure function, we used genetic algorithm (GA) and particle swarm optimization (PSO) algorithm to simulate Iranians per capita health expenditure during 1979-2015. Then we selected the superior model in terms of prediction power criteria and forecast per capita health expenditure until 2041. Also, the statistical analyzes were performed using the MATLAB software version R2016b. Results: The predicted results indicate that per capita health expenditures in Iran will increase with a positive slope by 2041. The amount of this expenditure will be from $ 1081 (based on 2011 constant prices) in 2015 to $ 2628 in 2041 (about 2.5 times). Conclusion: With regard to the projected amount of per capita health expenditures up to 2041 horizon, policy makers in the health sector should take the necessary measures to finance the expenditures of this sector.
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One of the key issues in the optimal operation of DFIG-based wind turbines is the optimization of relatively large control parameters that exist in these systems. However, the main problem is the high number of control parameters and the nonlinearity of the model of the More
One of the key issues in the optimal operation of DFIG-based wind turbines is the optimization of relatively large control parameters that exist in these systems. However, the main problem is the high number of control parameters and the nonlinearity of the model of these systems, which makes solving the optimization problem very time-consuming and divergent in some cases. In this article, in order to optimize the control parameters, a method based on particle swarm optimization (PSO) is proposed. In this method, after linearization of the system model, the eigenvalues of the system are extracted as a function of the control parameters. By examining the sensitivity of eigenvalues to control parameters, more sensitive parameters are identified and optimized based on the PSO method. The performance of the proposed method has been investigated through simulation in the MATLAB software environment.
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When a turbine–generator set connect to a long transmission line, may results side effects such as Sub-Synchronous Resonances (SSR). The capabilities of the Distributed Static Series Compensator (DSSC) as a member of the family of D-FACTS can be used to reduce the More
When a turbine–generator set connect to a long transmission line, may results side effects such as Sub-Synchronous Resonances (SSR). The capabilities of the Distributed Static Series Compensator (DSSC) as a member of the family of D-FACTS can be used to reduce these SSR. To achieve this desired goal, the fuzzy controller, Particle Swarm Optimization (PSO) and artificial neural network is used to control of the DSSC. Particle swarm optimization is designed Based on the Conventional Damping Controller (CDC) and fuzzy logic is designed based on damping controller (FLBDC) and damping control based on artificial neural network trained using the fast pace of changes has been designed. Stability of the system is analysed by simulations in the time domain with performance index (PI). All simulations are done using Matlab / Simulink software. Case studies show that proposed algorithms can reduce SSR in the system.All simulations are done using Matlab / Simulink software. Case studies show that proposed algorithms can reduce SSR in the system.
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Elastic analysis of structures creates basic shearing forces and stresses that are significantly larger than the actual responses of the structures. By entering the inelastic domain, the structure can absorb and resist a large amount of earthquake energy. On the other h More
Elastic analysis of structures creates basic shearing forces and stresses that are significantly larger than the actual responses of the structures. By entering the inelastic domain, the structure can absorb and resist a large amount of earthquake energy. On the other hand, nonlinear analysis of structures requires time-consuming and voluminous computational operations, so in most of the codes, a simple and appropriate method called equivalent static method is presented to achieve a reasonable answer to the nonlinear behavior of the structure (without performing a nonlinear analysis). Therefore, due to the importance of ductility in the absorption of seismic energy, the computational forces caused by the earthquake are reduced by introducing the coefficient of structural behavior, R. In this paper, an extensive database consisting of 12,960 eccentrically braced frame (EBF) structures with varying story numbers of 3, 6, 9, 12, 15 and 20, three types of column stiffness and three degrees of bracing slenderness was designed and analyzed under 20 near-faults pulse-like earthquakes. To generate the estimated relation R, 6769 data were interpreted using particle swarm algorithm. The results of a correlation of 0.86 in the test data presented the accuracy of the proposed relation.
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این مطالعه یک مدل کنترل موجودی را برای تعیین چرخه بهینه بازپرسازی اقلام منسوخ شدنی ارائه میکند، که در آن تقاضای مشتری به صورت یک تابع کاهشی از زمان در حالت منسوخ شدن ناگهانی در نظر گرفته شده است. علاوه بر این، برای تشویق خریدار به خرید بیشتر، فروشنده می تواند به خریدار More
این مطالعه یک مدل کنترل موجودی را برای تعیین چرخه بهینه بازپرسازی اقلام منسوخ شدنی ارائه میکند، که در آن تقاضای مشتری به صورت یک تابع کاهشی از زمان در حالت منسوخ شدن ناگهانی در نظر گرفته شده است. علاوه بر این، برای تشویق خریدار به خرید بیشتر، فروشنده می تواند به خریدار اجازه دهد هزینه را با تاخیر پرداخت کند. بر این اساس، مقاله حاضر بر بررسی یک مدل کنترل موجودی برای اقلام منسوخ شدنی با در نظر گرفتن سیاست اعتبار تجاری و تقاضای وابسته به زمان و حالت منسوخ شدن ناگهانی تمرکز دارد. با توجه به غیر خطی بودن مدل پیشنهادی، از تقریب سری تیلور برای حل آن استفاده شد. علاوه بر این، برای جلوگیری از تأثیر تقریب سری تیلور بر راهحل بهینه، از یک الگوریتم فراابتکاری بهینهسازی ازدحام ذرات کارآمد برای یافتن راهحل نزدیک به بهینه استفاده شد که نشاندهنده پاسخهای بهتر است. سپس مثالهای عددی در مورد مطالعاتی صنعت عمده فروشی تلفن همراه برای نشان دادن اعتبار مدل پیشنهادی در نظر گرفته و حل شد. در نهایت، یک تحلیل حساسیت در زمینه اثرات پارامترهای اصلی بر سود کل و زمان چرخه بازپرسازی انجام شد. نتایج عددی حاکی از آن است که گنجاندن ریسک منسوخ شدگی در مدل موجودی کالا برای اقلام منسوخ شدنی در افزایش سود و در عین حال کاهش هزینه های این اقلام تاثیر بسزایی دارد.
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The household energy management system (HEMS) can optimally schedule home appliances for transferring loads from peak to off-peak times. Consumers of smart houses have HEM, renewable energy sources and storage systems to reduce the bill. In this article, a new HEM model More
The household energy management system (HEMS) can optimally schedule home appliances for transferring loads from peak to off-peak times. Consumers of smart houses have HEM, renewable energy sources and storage systems to reduce the bill. In this article, a new HEM model based on the time of usage pricing planning with renewable energy systems is proposed to use the energy more efficiently. The new meta-heuristic whale optimization algorithm (WOA) and the common meta-heuristic of particle swarm optimization (PSO) are used to achieve that. To improve the performance, a mapping chaos theory (CWOA) is proposed. Also, an independent solar energy source is used as a support of the microgrid to achieve a better performance. It is concluded that the energy saving achieved by the proposed algorithm is able to decrease the electricity bill by about 40-50% rather than the WOA and PSO methods. The proposed system is simulated in MATLAB environment.
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