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31.
Saeed Masoudnia Reza Ebrahimpour Seyed Ali Asghar Abbaszadeh Arani 《Neural Processing Letters》2012,36(1):31-47
Combining accurate neural networks (NN) in the ensemble with negative error correlation greatly improves the generalization ability. Mixture of experts (ME) is a popular combining method which employs special error function for the simultaneous training of NN experts to produce negatively correlated NN experts. Although ME can produce negatively correlated experts, it does not include a control parameter like negative correlation learning (NCL) method to adjust this parameter explicitly. In this study, an approach is proposed to introduce this advantage of NCL into the training algorithm of ME, i.e., mixture of negatively correlated experts (MNCE). In this proposed method, the capability of a control parameter for NCL is incorporated in the error function of ME, which enables its training algorithm to establish better balance in bias-variance-covariance trade-off and thus improves the generalization ability. The proposed hybrid ensemble method, MNCE, is compared with their constituent methods, ME and NCL, in solving several benchmark problems. The experimental results show that our proposed ensemble method significantly improves the performance over the original ensemble methods. 相似文献
32.
In this paper, a direct self‐structured adaptive fuzzy control is introduced for the class of nonlinear systems with unknown dynamic models. Control is accomplished by an adaptive fuzzy system with a fixed number of rules and adaptive membership functions. The reference signal and state errors are used to tune the membership functions and update them instantaneously. The Lyapunov synthesis method is also used to guarantee the stability of the closed loop system. The proposed control scheme is applied to an inverted pendulum and a magnetic levitation system, and its effectiveness is shown via simulation. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society 相似文献
33.
In this article, we consider the project critical path problem in an environment with hybrid uncertainty. In this environment, the duration of activities are considered as random fuzzy variables that have probability and fuzzy natures, simultaneously. To obtain a robust critical path with this kind of uncertainty a chance constraints programming model is used. This model is converted to a deterministic model in two stages. In the first stage, the uncertain model is converted to a model with interval parameters by alpha-cut method and distribution function concepts. In the second stage, the interval model is converted to a deterministic model by robust optimization and min-max regret criterion and ultimately a genetic algorithm with a proposed exact algorithm are applied to solve the final model. Finally, some numerical examples are given to show the efficiency of the solution procedure. 相似文献
34.
In this study, Adaptive Neuro-Fuzzy Inference System (ANFIS) has been used to model local scouring depth and pattern scouring around concave and convex arch shaped circular bed sills. The experimental part of this research study includes seven sets of laboratory test cases which were performed in an experimental flume under different flow conditions. A data set consists of 2754 data points of scouring depth were collected to use in the ANFIS model. The ratio of arch diameter, D, to flume width, W, is used as a non dimensional variables in all test cases. The results from ANFIS model were compared with the results of ANN model obtained by Homayoon et al. [24] and previously presented models. The results indicated that for D/W equal to 1 and 1.2, the ANFIS models produced a good performance for convex and concave bed sills. As a result, the ANFIS models can be used as an alternative to ANN for estimation of scour depth and scour pattern around a concave bed sill installed with a bridge pier. 相似文献
35.
Ho-Chan Kim Hardian Reza Dharmayanda Taesam Kang Agus Budiyono Gigun Lee Widyawardana Adiprawita 《International Journal of Control, Automation and Systems》2012,10(1):88-101
Rigorous control synthesis for an unmanned aerial vehicle necessitates the availability of a good, reasonable model for such
a vehicle. The work reported in this paper focuses on the modeling of a rotary unmanned aerial vehicle (RUAV) and the development
of a robust controller that can handle parameter uncertainties and disturbances. The parameters of the plant model are obtained
through the use of the prediction error method with real flight data. The response of the identified linear model shows a
good match with the measured flight data. The H
∞ control scheme is applied to obtain a robustly stable controller using the identified model. The proposed controller is analyzed
using frequency-domain analysis and time-domain simulations. The performance of the proposed H
∞ controller is better than that of the conventional proportional derivative controller in that the proposed controller has
a shorter settling time and less overshoot. Furthermore, the degradation of the proposed controller performance is negligible
and stability is maintained when the input gains to the plant are doubled, which demonstrates the good performance and robustness
of the controller. 相似文献
36.
Open Forum
Cheep! Cheep! 相似文献37.
Azizli Mohammad Javad Barghamadi Mohammad Rezaeeparto Katayoon Mokhtary Masoud Parham Somayeh Darabi Mehdi Joker 《Iranian Polymer Journal》2021,30(10):1001-1018
Iranian Polymer Journal - Effects of graphene oxide (GO) on various properties of rubber hybrid nanocomposites based on PVMQ/XNBR-g-GMA/XNBR (phenyl-vinyl-methyl-polysiloxane/carboxylated nitrile... 相似文献
38.
Esmat Koohsaryan Mansoor Anbia Mohammad Sepehrian Mohammad Maghsoodlu 《Journal of surfactants and detergents》2021,24(1):85-97
This study reports the preparation of hierarchical NaP zeolite with the aim of obtaining a non-phosphate detergent builder as an alternative for environmental remediation from eutrophication phenomenon. Hierarchically structured NaP zeolite was easily synthesized hydrothermally and under different syntheses conditions. Samples were characterized using several standard techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, and N2 adsorption–desorption analysis. Three powder detergents were prepared by mixing main components such as linear alkylbenzene sulfonate, sodium sulfate, sodium silicate, and sodium carbonate as well as different amounts of as-synthesized zeolite and sodium tripolyphosphate in the detergent formulation as potential detergency builders. Some different detergency tests as pH value, water insolubility, foam height, moisture content, alcohol insolubility, and surface tension measurement were carried out for all synthetic detergent samples and two commercial ones. The results demonstrated that the high cleaning performance of the powders was obtained as using eco-friendly zeolite builders in comparison with phosphate-based commercial and synthetic detergent samples. 相似文献
39.
This paper aims to provide a systematic and comprehensive survey of state-of-the-art machine learning techniques and their potential applications in IoT-integrated power systems. 相似文献
40.
Mohammadi Hossein Mohammadi Mohammad Amiri Iraj Sadegh Hosseinghadiry Mahdiar 《SILICON》2021,13(3):747-755
Silicon - In this paper, a new structure: triple work function metal gate SOI MESFET, intended for integration into the deep-submicron CMOS technology, is proposed. The gate of the device consists... 相似文献