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Comprehensive Study on Decoupling Networks for 7 Tesla MRI based on Reactive Load Parasitic-Element 基于无功负载寄生元件的7特斯拉MRI解耦网络综合研究
Q4 Engineering Pub Date : 2020-06-11 DOI: 10.29252/mjee.14.3.6
S. Salama, A. Abuelhaija, T. Baldawi, Samer Issa
This work presents and evaluates the integrating of decoupling networks in MRI systems at 7 Tesla magnetic field strength. The parasitic element is reactive loaded. Four different cases of reactive loads are considered: capacitive load, inductive load, open circuited, and short-circuited loads are considered. The idea behind this technique is to reduce or even eliminate the effect of mutual coupling between the RF coil elements in magnetic resonance imaging (MRI)system. Two rectangular loops are used to compose a planar phased array. This structure is designed and optimized in CST at the Larmor frequency of 298.3 MHz corresponding to the 7 Tesla MRI system.
这项工作介绍并评估了在7特斯拉磁场强度下MRI系统中去耦网络的集成。寄生元件为无功负载。考虑了四种不同的无功负载情况:电容负载、电感负载、开路负载和短路负载。该技术背后的思想是减少甚至消除磁共振成像(MRI)系统中RF线圈元件之间的相互耦合的影响。两个矩形环路用于组成一个平面相控阵。该结构是在CST中设计和优化的,拉莫尔频率为298.3MHz,对应于7特斯拉MRI系统。
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引用次数: 0
Correction of the Photovoltaic System Control by the Addition of a Voltage Regulator in the Electrical Conversion Chain 在电转换链中加入稳压器对光伏系统控制的修正
Q4 Engineering Pub Date : 2020-06-02 DOI: 10.29252/mjee.14.3.5
Ali Ghelam, M. Boudiaf, Y. Derouiche
The objective of this work is to meet the variations of the electrical energy needs by modifying the conventional topology of the conversion chain, at the same time to improve the operation of the photovoltaic system. This article focuses on improving the performance and efficiency of photovoltaic systems connected to the AC grid, through the use of advanced control algorithms (Sliding Mode control SMC and Fuzzy Logic Control FLC) for the control of DC/DC and DC/AC power conditioners. The control of the DC/DC converter allows the pursuit of the maximum power point MPPT of the photovoltaic generator with a view to a better utilization of the photovoltaic generator. The inverter control system is used to inject synchronized sinusoidal output current to the power grid and to improve the quality of energy injected into the grid. The original idea of this work based on the insertion of a DC/DC BOOST voltage regulator in the conversion chain (between the battery and the inverter) to adjust the voltage transfer of the DC bus. This technique allows the provision of AC voltage for the sufficiency of the energy required by the control according to the need of the load.
这项工作的目的是通过修改转换链的传统拓扑来满足电能需求的变化,同时改善光伏系统的运行。本文的重点是通过使用先进的控制算法(滑模控制SMC和模糊逻辑控制FLC)来控制DC/DC和DC/AC电源调节器,提高与交流电网连接的光伏系统的性能和效率。通过对DC/DC变换器的控制,可以追求光伏发电机的最大功率点MPPT,以便更好地利用光伏发电机。逆变器控制系统用于向电网注入同步正弦输出电流,以提高向电网注入能量的质量。这项工作的最初想法是基于在转换链(电池和逆变器之间)插入DC/DC BOOST稳压器来调整直流母线的电压转移。这种技术允许根据负载的需要提供交流电压,以满足控制所需的能量。
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引用次数: 1
Visual and Gyroscope Sensor for Head Movement Controller System on Meal-Assistance Application 视觉陀螺传感器在助餐头部运动控制系统中的应用
Q4 Engineering Pub Date : 2020-05-28 DOI: 10.29252/mjee.14.3.4
Riky Tri Yunardi, N. Dina, Eva Inaiyah Agustin, Aji Akbar Firdaus
Head movement utilizes gestures to aid people with disabilities so that they can have hands-free human-computer interaction. Currently, motion-based sensor is the most widely used approach to recognize of head gestures. Identification of head movement is important to control a robotic manipulator in an assisting device. However, the most effective methodologies to assess head angular movements are yet to be discovered. This paper combines two algorithms, the visual sensor and the gyro sensor, to identify head orientation movement with high precision. Head orientations were measured using data distribution and this was done with a meal-assistance robot manipulator used in a sitting position. Evaluation of the accuracy of the system shows that a visual sensor, a gyro sensor, and a combined sensor are 99.60%, 91.26%, and 99.85%, respectively. Therefore, we propose the application of position control of meal assistive robot based on user's head movement in a sitting position.
头部运动利用手势来帮助残疾人,使他们能够进行免提人机交互。目前,基于运动的传感器是识别头部手势最广泛使用的方法。头部运动的识别对于控制辅助设备中的机器人操作器非常重要。然而,评估头部角运动的最有效方法尚待发现。本文将视觉传感器和陀螺传感器两种算法相结合,以高精度识别头部定向运动。使用数据分布测量头部方向,并使用坐姿的助餐机器人进行测量。对系统精度的评估表明,视觉传感器、陀螺传感器和组合传感器的精度分别为99.60%、91.26%和99.85%。因此,我们提出了基于用户坐姿头部运动的助餐机器人位置控制的应用。
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引用次数: 3
Self-Adaptive Sampling Rate to Improve Network Lifetime using Watchdog Sensor and Context Recognition in Wireless Body Sensor Networks 基于看门狗传感器和上下文识别的自适应采样率提高无线身体传感器网络寿命
Q4 Engineering Pub Date : 2020-05-24 DOI: 10.29252/mjee.14.3.2
H. Mehdi, H. Zarrabi, A. K. Zadeh, A. Rahmani
Todays, Wireless Body Sensor Networks (WBSNs) are used as a useful way in health monitoring. One of the most important problems regarding wireless body sensor network (WBSNs) is network lifetime. This factor mainly relies on the energy consumption of sensors. In fact, during capturing vital sign data and also communicating them to the coordinator the biosensors consume energy. In this article, we are interested to propose an energy efficient adaptive sampling (AS) rate specification algorithm to set the amount of sensed data. According to the National Early Warning Score (NEWS), the sensors gather data and detect emergency data.  Two scenarios have been used; the first is utilizing context recognition to indicate the active and sleep sensors in different time slices and the second using watchdog sensors for checking patient situation in critical condition. Simulation results show the proposed method can save energy and increase network lifetime by up to 4 times more than the previous work. In addition, our methods allow on average 75% improvement in overhead data reduction while maintaining more than 90% data integrity.
如今,无线身体传感器网络(WBSN)被用作健康监测的一种有用方式。关于无线身体传感器网络(WBSN),最重要的问题之一是网络寿命。这个因素主要取决于传感器的能耗。事实上,在捕捉生命体征数据并将其传达给协调员的过程中,生物传感器消耗能量。在本文中,我们有兴趣提出一种节能自适应采样(AS)速率指定算法来设置感测数据量。根据国家预警评分(NEWS),传感器收集数据并检测紧急情况数据。使用了两种方案;第一种是利用上下文识别来指示不同时间片中的活动和睡眠传感器,第二种是利用看门狗传感器来检查危急情况下的患者情况。仿真结果表明,该方法可以节省能源,使网络寿命提高4倍。此外,我们的方法允许平均75%的开销数据减少改进,同时保持90%以上的数据完整性。
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引用次数: 5
VSI Based DSTATCOM for Compensating Nonlinear and Unbalanced Loads 基于VSI的DSTATCOM补偿非线性和不平衡负载
Q4 Engineering Pub Date : 2018-06-21 DOI: 10.14419/ijet.v7i3.3.14485
S. R.REDDY, P. V.PRASAD, G. N.SRINIVAS
This paper presents study of distribution static compensator (D-STATCOM) for compensation of neutral current, source&PCC current harmonic distortion,  PCC voltage regulation and compensation of unbalanced current waveform for the three phase four wire nonlinear and  unbalanced load medium voltage distribution system. The proposed control algorithm is developed based on synchronous reference frame theory with PI controller. The obtained reference current signal from control algorithm is compared in hysteresis band current controller for better switching of D-STATCOM. The performance of system without & with D-STATCOM is also analysed and compared. The proposed control method is implemented on 11/0.4kv medium voltage distribution system and it is provided effective compensation for reactive power and harmonic distortion mitigation. The simulation results are obtained using MATLAB/SIMULINK.  
本文研究了配电静态补偿器(D-STATCOM)在三相四线线非线性不平衡负载中压配电系统中对中性点电流、源及PCC电流谐波畸变的补偿、PCC电压的调节和不平衡电流波形的补偿。该控制算法基于同步参考系理论和PI控制器。将控制算法得到的参考电流信号在滞回带电流控制器中进行比较,以便更好地切换D-STATCOM。并对无D-STATCOM和有D-STATCOM的系统性能进行了分析和比较。该控制方法在11/0.4kv中压配电系统中得到了有效的无功补偿和谐波畸变缓解。利用MATLAB/SIMULINK进行了仿真。
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引用次数: 1
Artificial Neural Network Based Method to Mitigate Temporary Over-voltages 基于人工神经网络的暂态过电压缓解方法
Q4 Engineering Pub Date : 2011-05-18 DOI: 10.25103/JESTR.042.13
I. Sadeghkhani, A. Ketabi, R. Feuillet
Uncontrolled energization of large power transformers may result in magnetizing inrush current of high amplitude and switching over-voltages. The most effective method for the limitation of the switching over-voltages is controlled switching since the magnitudes of the produced transients are strongly dependent on the closing instants of the switch.‎ We introduce a harmonic index that it’s minimum value is corresponding to the best case switching time.‎ Also, this paper ‎presents an Artificial Neural Network (ANN)-based approach to ‎estimate the optimum switching instants for real time applications. In the proposed ANN, Levenberg–Marquardt ‎second order method is used to train the multilayer perceptron. ANN training is performed based on equivalent circuit parameters of the network. Thus, trained ANN is applicable to every studied system. To verify the effectiveness of the proposed index and accuracy of the ANN-based approach, two case studies are presented and demonstrated.
大型电力变压器上电不控制会产生高幅值的励磁涌流和开关过电压。限制开关过电压的最有效方法是控制开关,因为产生的瞬态的大小强烈依赖于开关的闭合瞬间。我们引入了一个谐波指标,其最小值对应于最佳情况下的切换时间。此外,本文提出了一种基于人工神经网络(ANN)的方法来估计实时应用的最佳切换时刻。在本文提出的人工神经网络中,采用Levenberg-Marquardt二阶方法训练多层感知器。基于网络的等效电路参数进行人工神经网络的训练。因此,训练后的人工神经网络适用于所研究的每个系统。为了验证所提出的指标的有效性和基于人工神经网络的方法的准确性,提出并演示了两个案例研究。
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引用次数: 4
Nitric Oxide Diffusion Attributes in Biological And Artificial Environments: A Computational Study 一氧化氮在生物和人工环境中的扩散特性:一个计算研究
Q4 Engineering Pub Date : 2011-03-10 DOI: 10.1234/MJEE.V5I1.403
C. P. S. Araujo, P. F. López, P. G. Báez
This paper presents a computational study on the dynamic of nitric oxide (NO) in both the biological and artificial environments, by means the analysis of important nitric oxide diffusion attributes, which are defined in this work. We apply the compartmental model of NO diffusion as a formal tool, using a computational neuroscience point of view. The main objective is the analyses of the emergence and dynamic of complex structures, essentially diffusion neighbourhood ( DNB), in environments with volume transmission (VT). The study is performed by the observation of the NO diffusion attributes, the NO directionality (NOD), the average influence (AI) and the center of DNB (CDNB). We present a study of the influences and dependences with respect to associated features to the NO synthesis-diffusion process, and to the different environments where it spreads (non-isotropy and non-homogeneity). The paper is structured into three sets of experiences which cover the aforementioned aspects: influence of the NO synthesis process, isolated and multiple processes, influence of distance to the element where NO is synthesized, and influence of features of the diffusion environment. The developments have been performed in mono bi-and three-dimensional environments, with endothelial cell features. The study contributes the needed formalism to management the dynamic of NO in artificial an biological environments also to quantify the information representation capacity that a type of NO diffusion-based signaling presents and their implications in many other underlying neural mechanisms, such as neural recruitment, synchronization of computations between neurons and in the brain activity in general. 一氧化氮擴散屬性生物和人工環境:計算研究 卡門拉巴斯蘇亞雷斯阿勞霍,巴勃羅·費爾南德斯·洛佩斯,帕特里西奧·加西亞·貝茲 摘要 本文對一氧化氮(NO)的生物和人造環境的動態的計算研究,由裝置的重要的一氧化氮擴散屬性,這是在此工作中定義的分析。 我們不應用擴散的房室模型作為一個正式的工具,使用視圖計算神經科學點。 其主要目的是在出現的分析和動態複雜的結構,基本上是擴散附近(DNB)與體積傳輸(VT)環境。 該研究是由NO擴散屬性,NO的方向性(NOD)的觀察進行的,平均影響(AI)和DNB(CDNB)的中心。 我們目前的影響和依賴關係的研究,相對於相關功能的NO合成擴散過程,並在那裡它傳播(非各向同性和非均勻性)在不同的環境。 本文的結構分為三組經驗涵蓋上述幾個方面:NO合成過程中的影響力,孤立和多進程,到NO合成元素距離的影響,擴散環境的特徵的影響。 的發展已經在單雙向和三維環境中被執行時,與內皮細胞的特徵。 該研究有助於所需的形式主義管理NO的動態人工的生物環境也量化信息的表示能力,一個類型沒有基於擴散信號禮物和許多其他潛在的神經機制影響,如神經招聘,同步 的神經元之間,並且在一般的大腦活動的計算。
本文通过分析一氧化氮在生物和人工环境中的重要扩散属性,对一氧化氮在生物和人工环境中的动态进行了计算研究。我们使用计算神经科学的观点,将NO扩散的室室模型作为正式工具。主要目的是分析复杂结构的出现和动态,主要是扩散邻域(DNB),在具有体积传输(VT)的环境中。通过观察NO扩散属性、NO方向性(NOD)、平均影响(AI)和DNB中心(CDNB)进行研究。我们提出了一项关于NO合成-扩散过程相关特征的影响和依赖性的研究,以及它传播的不同环境(非各向同性和非同质性)。本文分为三组经验,涵盖了上述三个方面:NO合成过程的影响、孤立和多过程的影响、与NO合成元素距离的影响、扩散环境特征的影响。这些进展已经在单双三维环境中进行,具有内皮细胞的特征。该研究为人工和生物环境中一氧化氮的动态管理提供了必要的形式,也量化了一种基于一氧化氮扩散的信号所呈现的信息表示能力,以及它们在许多其他潜在神经机制中的含义,如神经募集、神经元之间计算的同步和一般的大脑活动。一氧化氮擴散屬性生物和人工環境:計算研究卡門拉巴斯蘇亞雷斯阿勞霍,巴勃羅·費爾南德斯·洛佩斯,帕特里西奧·加西亞·貝茲摘要本文對一氧化氮(NO)的生物和人造環境的動態的計算研究,由裝置的重要的一氧化氮擴散屬性,這是在此工作中定義的分析。我們不應用擴散的房室模型作為一個正式的工具,使用視圖計算神經科學點。 。該研究是由没有擴散屬性,没有的方向性(点头)的觀察進行的,平均影響(AI)和DNB (CDNB)的中心。我們目前的影響和依賴關係的研究,相對於相關功能的没有合成擴散過程,並在那裡它傳播(非各向同性和非均勻性)在不同的環境。本文的結構分為三組經驗涵蓋上述幾個方面:没有合成過程中的影響力,孤立和多進程,到没有合成元素距離的影響,擴散環境的特徵的影響。的發展已經在單雙向和三維環境中被執行時,與內皮細胞的特徵。 該研究有助於所需的形式主義管理没有的動態人工的生物環境也量化信息的表示能力,一個類型沒有基於擴散信號禮物和許多其他潛在的神經機制影響,如神經招聘,同步的神經元之間,並且在一般的大腦活動的計算。
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引用次数: 1
Cyclostationary Beacon for Assisting Spectrum Sensing in Opportunistic Spectrum Access 机会频谱接入中辅助频谱感知的循环平稳信标
Q4 Engineering Pub Date : 2011-01-28 DOI: 10.1234/MJEE.V5I1.374
Hanwen Cao, Q. Cai, J. P. Miranda, T. Kaiser
Cognitive radio is a promising solution to the problem of spectrum scarcity by means of allowing secondary radio networks access the spectrum opportunistically. One of the most important issues in cognitive radio is how to detect existing over-the-air signals reliably. Not a few literatures have reported that signals could be detected via their inherent or embedded properties. However, this approach may not be reliable and flexible enough for all kinds of signals with different modulation types. In this paper, we propose a type of multitone beacon signal carrying cyclostationary signatures, which is able to enhance the reliability and efficiency of signal detection at low cost of spectrum overhead. This beacon not only can indicate the presence or absence of user signal but also can reveal some other information helpful to opportunistic spectrum access through the information bits carried on its cyclostationary signatures. It could be applied to device/network identification, indication of spectrum allocation and spectrum rendezvous, both for primary and secondary users. Based on our previous work reported in [1], the generation and detection algorithm of the beacon signal are extended with improved spectral efficiency. Performance is discussed with both computer simulation and testbed validation.
认知无线电是一种很有前途的解决频谱短缺问题的方法,它允许二次无线电网络机会性地访问频谱。认知无线电中最重要的问题之一是如何可靠地检测现有的无线信号。不少文献报道了信号可以通过其固有或嵌入的特性来检测。然而,对于不同调制类型的各种信号,这种方法可能不够可靠和灵活。本文提出了一种带有循环平稳特征的多音信标信号,以较低的频谱开销成本提高了信号检测的可靠性和效率。信标不仅可以指示用户信号的存在或不存在,而且还可以通过其循环平稳特征上携带的信息位揭示一些有助于机会频谱接入的其他信息。它可应用于设备/网络识别、频谱分配指示和频谱交会,适用于主要用户和次要用户。我们在[1]的基础上,扩展了信标信号的生成和检测算法,提高了频谱效率。通过计算机仿真和试验台验证对性能进行了讨论。
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引用次数: 1
Spectrum Sensor Hardware Implementation Based on Cyclostationary Feature Detector 基于周期平稳特征检测器的频谱传感器硬件实现
Q4 Engineering Pub Date : 2011-01-28 DOI: 10.1234/MJEE.V5I1.355
V. Turunen, M. Kosunen, Sami Kallioinen, A. Parssinen, J. Ryynanen
Cognitive radios utilize spectrum sensors to provide  information about the surrounding radio environment. This enables cognitive radios to communicate at the same frequency bands with existing (primary) radio systems, and thereby improve the utilization of spectral resources. Furthermore, the spectrum sensor must be able to guarantee that the cognitive radio devices do not interfere with the primary system transmissions. This paper describes a hardware implementation of a spectrum sensor based on cyclostationary feature detector, which has an improved detection performance achieved by decimation of the cyclic spectrum. Decimation also provides a simple way to control detection time and, therefore, allows trading the detection time to better probability of detection and vice versa. Implementation complexity in terms of power consumption and silicon area for a 65 nm CMOS process is evaluated. Measured detection performance is presented and detection of a 802.11g WLAN signal through air interface is demonstrated. Cognitive radios utilize spectrum sensors to provide information about the surrounding radio environment. This enables cognitive radios to communicate at the same frequency bands with existing (primary) radio systems, and thereby improve the utilization of spectral resources. Furthermore, the spectrum sensor must be able to guarantee that the cognitive radio devices do not interfere with the primary system transmissions. This paper describes a hardware implementation of a spectrum sensor based on cyclostationary feature detector, which has an improved detection performance achieved by decimation of the cyclic spectrum. Decimation also provides a simple way to control detection time and, therefore, allows trading the detection time to better probability of detection and vice versa. Implementation complexity in terms of power consumption and silicon area for a 65 nm CMOS process is evaluated. Measured detection performance is presented and detection of a 802.11g WLAN signal through air interface is demonstrated.
认知无线电利用频谱传感器提供有关周围无线电环境的信息。这使得认知无线电能够与现有(主要)无线电系统在同一频带上通信,从而提高频谱资源的利用率。此外,频谱传感器必须能够保证认知无线电设备不会干扰主系统传输。本文介绍了一种基于循环平稳特征检测器的频谱传感器的硬件实现,通过对循环频谱进行抽取,提高了检测性能。抽取还提供了一种控制检测时间的简单方法,因此,可以用检测时间来换取更好的检测概率,反之亦然。在功耗和硅面积方面对65纳米CMOS工艺的实现复杂性进行了评估。给出了实测的检测性能,并演示了通过空中接口检测802.11g WLAN信号。认知无线电利用频谱传感器提供有关周围无线电环境的信息。这使得认知无线电能够与现有(主要)无线电系统在同一频带上通信,从而提高频谱资源的利用率。此外,频谱传感器必须能够保证认知无线电设备不会干扰主系统传输。本文介绍了一种基于循环平稳特征检测器的频谱传感器的硬件实现,通过对循环频谱进行抽取,提高了检测性能。抽取还提供了一种控制检测时间的简单方法,因此,可以用检测时间来换取更好的检测概率,反之亦然。在功耗和硅面积方面对65纳米CMOS工艺的实现复杂性进行了评估。给出了实测的检测性能,并演示了通过空中接口检测802.11g WLAN信号。
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引用次数: 7
A Comparative Study of Space Search Algorithm and Particle Swarm Optimization in the Design of ANFIS-based Fuzzy Models 空间搜索算法与粒子群算法在基于anfiss的模糊模型设计中的比较研究
Q4 Engineering Pub Date : 2011-01-28 DOI: 10.1234/MJEE.V5I1.366
Wei Huang, L. Ding, Sung-Kwun Oh
In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of ANFIS-based fuzzy models based on SSA and information granulation (IG). In comparison with “conventional” evolutionary algorithms (such as PSO), SSA leads not only to better search performance to find global optimization but is also more computationally effective. In the hybrid optimization of ANFIS-based fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of ANFIS-based fuzzy models comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using three representative numerical examples such as Non-linear function, gas furnace, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some “conventional” fuzzy models already encountered in the literature.
在本研究中,我们提出了一种空间搜索算法(SSA),然后引入了一种基于SSA和信息粒化(IG)的基于anfiss的模糊模型混合优化。与“传统的”进化算法(如PSO)相比,SSA不仅具有更好的搜索性能来找到全局优化,而且计算效率更高。在基于anfiss的模糊推理系统的混合优化中,利用SSA对模糊模型进行参数优化,实现模糊模型的结构优化。借助c均值聚类实现的IG有助于确定模糊模型隶属函数顶点参数的初始值。基于anfiss的模糊模型的整体混合辨识以两种优化机制的形式出现:结构辨识(如要使用的输入变量的数量、输入变量的特定子集、隶属函数的数量和多项式类型)和参数辨识(即隶属函数的顶点)。结构识别采用SSA和C-Means方法,参数估计采用SSA和标准最小二乘法。通过非线性函数、煤气炉和Mackey-Glass时间序列三个具有代表性的数值算例对所提模型的性能进行了评价。通过对SSA和PSO的比较研究表明,SSA在模型质量和计算时间方面都提高了性能。所提出的模型还与文献中已经遇到的一些“传统”模糊模型的质量进行了对比。
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引用次数: 7
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Majlesi Journal of Electrical Engineering
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