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Chinese Physics B 2011年第6期20卷 546-551页

作者：伍雪冬王耀南刘维亭朱志宇 School of electronics and Information Jiangsu University of Science and Technology college of electrical and Information Engineering Hunan University

On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering （EKF） and the unscented Kalman filtering （UKF）, which were shortened as GEKF and CUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network （RBFNN） prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent.

关键词： prediction of time series with missing data random interruption failures in the observation neural network approximation

Grey Wolf Optimizer to Real Power Dispatch with Non-Linear Constraints

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Computer Modeling in Engineering & Sciences 2018年第4期115卷 25-45页

作者： G.R.Venkatakrishnan R.Rengaraj S.Salivahanan Assistant Professor Department of Electrical and Electronics EngineeringSSN College of EngineeringChennai-603110India Associate Professor Department of Electrical and Electronics EngineeringSSN College of EngineeringChennai-603110India Professor Department of Electronics and Communication EngineeringSSN College of EngineeringChennai-603110India

A new and efficient Grey Wolf Optimization(GWO)algorithm is implemented to solve real power economic dispatch(RPED)problems in this *** nonlinear RPED problem is one the most important and fundamental optimization problem which reduces the total cost in generating real power without violating the *** methods can solve the ELD problem with good solution quality with assumptions assigned to fuel cost curves without which these methods lead to suboptimal or infeasible *** behavior of grey wolves which is mimicked in the GWO algorithm are leadership hierarchy and hunting *** leadership hierarchy is simulated using four types of grey *** addition,searching,encircling and attacking of prey are the social behaviors implemented in the hunting *** GWO algorithm has been applied to solve convex RPED problems considering the all possible *** results obtained from GWO algorithm are compared with other state-ofthe-art algorithms available in the recent *** is found that the GWO algorithm is able to provide better solution quality in terms of cost,convergence and robustness for the considered ELD problems.

关键词： Grey wolf optimization(GWO) constraints power generation dispatch evolutionary computation computational complexity algorithms

A novel evolving scale-free model with tunable attractiveness

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Chinese Physics B 2010年第7期19卷 35-39页

作者：刘绚刘天琪王昊李兴源 School of electrical Engineering and Automation Sichuan University college of electronics and Information Engineering Sichuan University

In this paper, a new evolving model with tunable attractiveness is presented. Based on the Barabasi-Albert （BA） model, we introduce the attractiveness of node which can change with node degree. Using the mean-field theory, we obtain the analytical expression of power-law degree distribution with the exponent γ∈ （3, ∞）. The new model is more homogeneous and has a lower clustering coefficient and bigger average path length than the BA model.

关键词： scale-free tunable attractiveness degree distribution clustering coefficient

Nonlinear correction of photoelectric displacement sensor based on least square support vector machine

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Journal of Central South University 2011年第5期18卷 1614-1618页

作者：郭杰荣何怡刚刘长青 college of Physics and electronics Hunan University of Arts and Science college of electrical and Information Engineering Hunan University

A model of correcting the nonlinear error of photoelectric displacement sensor was established based on the least square support vector *** parameters of the correcting nonlinear model,such as penalty factor and kernel parameter,were optimized by chaos genetic *** the nonlinear correction of photoelectric displacement sensor based on least square support vector machine was *** application results reveal that error of photoelectric displacement sensor is less than 1.5%,which is rather satisfactory for nonlinear correction of photoelectric displacement sensor.

关键词： least square support vector machine position photoelectric displacement sensor nonlinear correct

Performance Enhancement of PV Based Boost Cascaded Fifteen Level Inverter for AC Loads

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Computer Systems Science & Engineering 2022年第7期42卷 165-181页

作者： M.P.Viswanathan B.Anand Department of electrical and electronics Engineering Hindusthan College of Engineering and TechnologyCoimbatore641032India

In this research work,single-stageﬁfteen levels cascaded DC-interface converter(CDDCLC)is proposed for sun arranged photovoltaic technology(PV)*** proposed geography is joined with help DC chopper and H-associate inverter to upgrade the power converter to accomplish the diminished harmonic proﬁ*** assessment with the customary inverter structures,the proposed system is used with diminished voltage stress,decreased switch count and DC source *** proposed research work with cascaded DC link conver-ter design requires three DC sources for combiningﬁfteen-level AC *** investigation structure switching technique is phase opposition and disposition pulse width modulation technique(POPD)which results in improved quality of obtained output AC power with 6.73%THD and also determinedly recommended for power converters used in UPS and drive applications since it is extremely affordable.A simulation and prototype model ofﬁfteen-level CDDCLC system is deployed and its performance is analyzed for various operating conditions.

关键词： Cascaded DClinkconverter(CDDCLC) modified phaseopposition and disposition(MPOPDPWM) photovoltaic(PV) DCinterfaceboostconverter

Computer-Assisted Real-Time Rice Variety Learning Using Deep Learning Network

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Rice science 2022年第5期29卷 489-498页

作者： Pandia Rajan JEYARAJ Siva Prakash ASOKAN Edward Rajan SAMUEL NADAR Department of electrical and electronics Engineering Mepco Schlenk Engineering CollegeSivakasi 626005India

Due to the inconsistency of rice variety,agricultural industry faces an important challenge of rice grading and classification by the traditional grading *** existing grading system is manual,which introduces stress and strain to humans due to visual *** rice grading system development has been proposed as a promising research area in computer *** this study,an accurate deep learning-based non-contact and cost-effective rice grading system was developed by rice appearance and *** proposed system provided real-time processing by using a NI-myRIO with a high-resolution camera and user *** firstly trained the network by a rice public dataset to extract rice discriminative ***,by using transfer learning,the pre-trained network was used to locate the region by extracting a feature *** proposed deep learning model was tested using two public standard datasets and a prototype real-time scanning *** AlexNet architecture,we obtained an average accuracy of 98.2%with 97.6%sensitivity and 96.4%*** validate the real-time performance of proposed rice grading classification system,various performance indices were calculated and compared with the existing *** simulation and real-time experiment evaluations confirmed the robustness and reliability of the proposed rice grading system.

关键词： deep learning algorithm rice defect classification computer vision agriculture automated visual grading system

Design,simulation of different configurations and life-cycle cost analysis of solar photovoltaic-water-pumping system for agriculture applications:use cases and implementation issues

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Clean Energy 2022年第2期6卷 335-352页

作者： L.Ashok Kumar C.N.Lakshmiprasad G.Ramaraj G.Sivasurya Department of electrical and electronics Engineering PSG College of TechnologyCoimbatoreIndia

Water is an essential resource for agriculture and the majority of land is irrigated through borewells or *** power requirement for an irrigation pump motor is fed by the on-grid power supply but the availability of electricity in rural areas is still *** rising concerns about global warming and the rise in carbon footprints,it is necessary to choose clean and green energy,thereby attaining self-sustainable *** receives yearly a mean solar irradiation of 6.5 kWh/m^(2)***,a solar photovoltaic-water-pumping system(SPV-WPS)is a suitable alternative to grid energy;thereby,the farmers would generate electricity through the solar photovoltaic system and become self-sufficient in their energy *** this paper,two different agricultural fields in Tamil Nadu,India that deploy flood irrigation and drip irrigation are taken as a case *** paper discusses the concerns on the use of grid power and their carbon footprint,design and simulation of 4-and 5.5-kW SPV-WPSs using PVsyst 7.1.1,and the advantages of using SPV-WPSs and life-cycle cost analysis on different use *** Government of India has introduced a special scheme to promote the installation of SPV-WPSs by offering attractive incentives through PM-Kisan Urja Suraksha evam Utthaan Mahabhiyan(KUSUM)*** results of the case study show that with the use of SPV-WPSs,either with or without subsidy,the farmer could gain a minimum of 250%on the investment with a project lifetime of 25 years.

关键词： solar water pump PVsyst PM-KUSUM subsidy life-cycle cost sustainable development goal

Identification and Guaranteed Performance Control of Hammerstein Systems over Wireless Channels

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International Journal of Automation and computing 2016年第2期13卷 125-132页

作者： Wei-Hua Deng Kang Li Jing Deng college of electrical Engineering Shanghai University of Electric Power School of electronics Electrical Engineering and Computer ScienceQueen's University

The problems of identification and stabilization of a class of Hammerstein systems over a wireless network are investigated in this paper. A new approach for the proof of iterative identification is presented first. Then a guaranteed performance controller is designed to stabilize the system. The effectiveness of the proposed approach is demonstrated by numerical examples.

关键词： Identification guaranteed performance control model-based approach wireless network stochastic delay.

A modified neural learning algorithm for online resistance estimation in vector controlled induction drives rotor motor

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Frontiers in Energy 2015年第1期9卷 22-30页

作者： A. CHITRA S. HIMAVATHI School of electrical Engineering Vellore Institute of TechnologyUniversity Katpadi Vellore 632014 India Department of electrical and electronics Engineering PondicherryEngineering College Pudhucherry 605014 India

Online estimation of rotor resistance is essen- tial for high performance vector controlled drives. In this paper, a novel modified neural algorithm has been identified for the online estimation of rotor resistance. Neural based estimators are now receiving active con- sideration as they have a number of advantages over conventional techniques. The training algorithm of the neural network determines its learning speed, stability, weight convergence, accuracy of estimation, speed of tracking and ease of implementation. In this paper, the neural estimator has been studied with conventional and proposed learning algorithms. The sensitivity of the rotor resistance change has been tested for a wide range of variation from -50% to ＋50% on the stability of the drive system with and without estimator. It is quiet appealing to settle with optimal estimation time and error for the viable realization. The study is conducted extensively for estimation and tracking. The proposed learning algorithm is found to exhibit good estimation and tracking capabilities. Besides, it reduces computational complexity and, hence, more feasible for practical digital implementa- tion.

关键词： neural networks back propagation (BP) rotorresistance estimators vector control induction motor

Attractor comparison analysis for characterizing vertical upward oil gas water three-phase flow

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Chinese Physics B 2014年第3期23卷 361-368页

作者：赵俊英金宁德高忠科杜萌王振亚 School of electrical Engineering and Automation Tianjin University Electronic Engineering Department Tianjin Vocational College of Electronics & Information

We investigate the dynamic characteristics of oil-gas-water three-phase flow in terms of chaotic attractor comparison. In particular, we extract a statistic to characterize the dynamical difference in attractor probability distribution. We first take time series from Logistic chaotic system with different parameters as examples to demonstrate the effectiveness of the method. Then we use this method to investigate the experimental signals from oil-gas-water three-phase flow. The results indicate that the extracted statistic is very sensitive to the change of flow parameters and can gain a quantitatively insight into the dynamic characteristics of different flow patterns.

关键词： oil-gas-water three-phase flow fluid dynamics attractor comparison