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bees algorithm (ba)

در نشریات گروه برق
تکرار جستجوی کلیدواژه bees algorithm (ba) در نشریات گروه فنی و مهندسی
تکرار جستجوی کلیدواژه bees algorithm (ba) در مقالات مجلات علمی
  • Shoorangiz Shams Shamsabad Farahani*, MohammadMahdi Arefi, AmirHossein Zaeri

    Electroencephalography (EEG) is a major clinical tool to diagnose, monitor and manage neurological disorders which is mostly affected by artifacts. Given the importance and the need for an automated method to remove artifacts, in this paper some intelligent automated methods are proposed which are composed of three main parts as extraction of effective input, filtering and filter optimization. Wavelet transform is utilized to extract the effective input, and the wavelet approximation coefficients are used as an effective input signal. In addition, Radial Basis Function Neural Network (RBFNN) has been used for filtering. The appropriate number of RBFs has been selected using extensive simulations, and the optimal value of spread parameter has been achieved by Bees algorithm (BA). Finally, the proposed artifact removal schemes have been evaluated on some real contaminated EEG signals in Mashad Ghaem hospital database. The results show that the proposed artifact removal schemes are able to effectively remove artifacts from EEG signals with little underlying brain signal distortion.

    Keywords: Artifacts, Bees Algorithm (BA), Electroencephalography, Optimization, Radial Basis Function NeuralNetwork (RBFNN), Wavelet Transform (WT)
  • افشین لشکرآرا *، هاجر باقری طولابی
    در این مقاله، کنترلر غیرخطی جدید برای DSTATCOM در یک ریزشبکه شامل واحدهای تولید پراکنده (DG) واحد پیشنهاد شده است. روش کنترلی پیشنهادی بر اساس نظریه خطی سازی فیدبک (FLT)، طراحی و از کنترلرهای PID نیز برای تنظیم و ردیابی جریان و ولتاژ مرجع استفاده شده است. همچنین ترکیبی از سیستم های فازی و الگوریتم زنبورها (BA) به منظور بهینه سازی پارامترهای کنترل کننده های PID پیشنهاد شده است. نتایج به دست آمده نشان می دهد ویژگی های پاسخ پله ولتاژ DSTATCOM کنترلر پیشنهادی شامل زمان خیز، زمان نشست، حداکثر اضافه جهش و خطای حالت پایدار به شکل چشمگیری بهبود یافته است. همچنین روش ترکیبی پیشنهادی برای تنظیم کنترلر طراحی شده به تنظیم بهتر ولتاژ DC خازن موجود درDSTATCOM منجر شده است و نیز عملکرد بهتری در مقایسه با کنترلر کلاسیک PID و یا کنترلر تنظیم شده با الگوریتم ژنتیک (GA) و بهینه سازی ازدحام ذرات (PSO) در هر دو حالت وقوع خطا و پس از برطرف سازی خطا دارد.
    کلید واژگان: الگوریتم زنبورها (BA)، نظریه خطی سازی فیدبک (FLT)، سیستم توزیع، منطق فازی
    Afshin Lashkrara *, Hajar Bagheri Tolabi
    This paper presents a nonlinear controller for a Distribution Static Compensator (DSTATCOM) of microgrids incorporating the Distributed Generation (DG) units. The nonlinear control has been designed based on partial feedback linearization theory and Proportional-Integral-Derivative (PID) controllers try to adjust the voltage and trace the outputs. This paper has proposed a combination of a fuzzy system and Bees Algorithm (BA) to optimize the parameters of the PID controllers. The results confirm that the characteristics of the response of the proposed controller (i.e. settling and rise times, the maximum overshoot and the steady-state error of the voltage step response of the DSTATCOM) is significantly improved by finding a high-quality solution. The proposed hybrid tuning method for the Partial Feedback Linearizing (PFL) controller concluded a better DC voltage regulation for the capacitor within the DSTATCOM. Furthermore, in the event of fault the proposed controller tuned by the fuzzy-BA method has shown a better performance in comparison with the conventional controller or controllers tuned by Genetic Algorithm (GA) or Particle Swarm Optimization (PSO) methods on both fault duration and after clearing times.
    Keywords: Distribution System, DSATACOM, Bees Algorithm (BA), Fuzzy Sets, Partial Feedback Linearizing (PFL)
  • R. Ilka, Y. Alinejad, Beromi, H. Yaghobi
    Among all types of electrical motors, permanent magnet synchronous motors (PMSMs) are reliable and efficient motors in industrial applications. Because of their superiority over other kinds of motors, they are replacing conventional electric motors. On the other hand, high-phase PMSMs are good candidates to be used in certain industrial and military projects such as electric vehicles, spacecrafts, naval systems and etc. In these cases, the motor has to be designed with minimum volume and high torque and efficiency. Design optimization can improve their features noticeably, thus reduce volume and enhance performance of motors. In this paper, a new method for optimum design of a five-phase surface-mounted permanent magnet synchronous motor is presented to achieve minimum permanent magnets (PMs) volume with an increased torque and efficiency. Design optimization is performed in search for optimum dimensions of the motor and its permanent magnets using Bees Algorithm (BA). The design optimization results in a motor with great improvement regarding the original motor which is compared with two well-known evolutionary algorithms i.e. GA and PSO. Finally, finite element method simulation is utilized to validate the accuracy of the design.
    Keywords: Permanent Magnets (PMs), Bees Algorithm (BA), Design Optimization, Finite Element Method (FEM)
  • A. Moradi*, A. Mirzakhani Nafchi, A. Ghanbarzadeh
    this paper wants to apply a multi-objective optimization method for optimizing truss design problem. This method is named as Multi-Objectives Bees Algorithm (MOBA). In the first problem, objective functions are minimizing stress in the two members and minimizing volume of truss, and on each of other three problems, the objectives which should be optimized are value of total weight of structure and also total displacement of nodes with considering limits on cross section of elements. The bees algorithm is developed based on principle of multi-objective problems. A clustering algorithm is applied for multi-objective bees algorithm in order to manage the size of the Pareto-optimal set. The results are good evidence for robustness and effectiveness of multi-objective bees algorithm in solving multi-objective optimal truss design.
    Keywords: Bees Algorithm (BA), Multi, Objective, Optimization, Pareto, Truss Design
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