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BP神经网络 4

神经网络 4

BP算法 2

大坝 2

Doherty功率放大器；输出功率回退；输出阻抗；网络相位 1

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

A. CHITRA,S. HIMAVATHI

《能源前沿（英文）》 2015年第9卷第1期页码 22-30 doi: 10.1007/s11708-014-0339-1

摘要： Online estimation of rotor resistance is essential 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 consideration 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 implementation.

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

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A pre-compensation method of the systematic contouring error for repetitive command paths

D. L. ZHANG,Y. H. CHEN,Y. P. CHEN

《机械工程前沿（英文）》 2015年第10卷第4期页码 367-372 doi: 10.1007/s11465-015-0367-5

摘要：

For a repetitive command path, pre-compensating the contouring error by modifying the command path is practical. To obtain the pre-compensation value with better accuracy, this paper proposes the use of a back propagation neural network to extract the function of systematic contouring errors. Furthermore, by using the extracted function, the contouring error can be easily pre-compensated. The experiment results verify that the proposed compensation method can effectively reduce contouring errors.

关键词： contouring error pre-compensation motion control system back propagation (BP) neural network

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hexavalent chromium using a porous titanium flow-through electrode and intelligent prediction based on a backpropagation neural network

《环境科学与工程前沿（英文）》 2023年第17卷第8期 doi: 10.1007/s11783-023-1697-x

摘要：

● Titanium-based flow-through electrode achieved high Cr(VI) reduction efficiency.

关键词： Flow-through electrode Hexavalent chromium Heavy metals Neural network Artificial intelligence

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Day-ahead electricity price forecasting using back propagation neural networks and weighted least square

S. Surender REDDY,Chan-Mook JUNG,Ko Jun SEOG

《能源前沿（英文）》 2016年第10卷第1期页码 105-113 doi: 10.1007/s11708-016-0393-y

摘要： This paper proposes the day-ahead electricity price forecasting using the artificial neural networks (ANN) and weighted least square (WLS) technique in the restructured electricity markets. Price forecasting is very important for online trading, e-commerce and power system operation. Forecasting the hourly locational marginal prices (LMP) in the electricity markets is a very important basis for the decision making in order to maximize the profits/benefits. The novel approach proposed in this paper for forecasting the electricity prices uses WLS technique and compares the results with the results obtained by using ANNs. To perform this price forecasting, the market knowledge is utilized to optimize the selection of input data for the electricity price forecasting tool. In this paper, price forecasting for Pennsylvania-New Jersey-Maryland (PJM) interconnection is demonstrated using the ANNs and the proposed WLS technique. The data used for this price forecasting is obtained from the PJM website. The forecasting results obtained by both methods are compared, which shows the effectiveness of the proposed forecasting approach. From the simulation results, it can be observed that the accuracy of prediction has increased in both seasons using the proposed WLS technique. Another important advantage of the proposed WLS technique is that it is not an iterative method.

关键词： day-ahead electricity markets price forecasting load forecasting artificial neural networks load serving entities

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Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

《信息与电子工程前沿（英文）》 2015年第16卷第6期页码 474-485 doi: 10.1631/FITEE.1400295

摘要： Accurate blood pressure (BP) measurement is essential in epidemiological studies, screening programmes, and research studies as well as in clinical practice for the early detection and prevention of high BP-related risks such as coronary heart disease, stroke, and kidney failure. Posture of the participant plays a vital role in accurate measurement of BP. Guidelines on measurement of BP contain recommendations on the position of the back of the participants by advising that they should sit with supported back to avoid spuriously high readings. In this work, principal component analysis (PCA) is fused with forward stepwise regression (SWR), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and the least squares support vector machine (LS-SVM) model for the prediction of BP reactivity to an unsupported back in normotensive and hypertensive participants. PCA is used to remove multi-collinearity among anthropometric predictor variables and to select a subset of components, termed ‘principal components’ (PCs), from the original dataset. The selected PCs are fed into the proposed models for modeling and testing. The evaluation of the performance of the constructed models, using appropriate statistical indices, shows clearly that a PCA-based LS-SVM (PCA-LS-SVM) model is a promising approach for the prediction of BP reactivity in comparison to others. This assessment demonstrates the importance and advantages posed by hybrid models for the prediction of variables in biomedical research studies.

关键词： Blood pressure (BP) Principal component analysis (PCA) Forward stepwise regression Artificial neural network (ANN) Adaptive neuro-fuzzy inference system (ANFIS) Least squares support vector machine (LS-SVM)

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Discussion on back-to-back two-stage centrifugal compressor compact design techniques

Lei HUO, Huoxing LIU

《机械工程前沿（英文）》 2013年第8卷第4期页码 390-400 doi: 10.1007/s11465-013-0278-2

摘要：

Design a small flow back-to-back two-stage centrifugal compressor in the aviation turbocharger, the compressor is compact structure, small axial length, light weighted. Stationary parts have a great influence on their overall performance decline. Therefore, the stationary part of the back-to-back two-stage centrifugal compressor should pay full attention to the diffuser, bend, return vane and volute design. Volute also impact downstream return vane, making the flow in circumferential direction is not uniformed, and several blade angle of attack is drastically changed in downstream of the volute with the airflow can not be rotated to required angle. Loading of high-pressure rotor blades change due to non-uniformed of flow in circumferential direction, which makes individual blade load distribution changed, and affected blade passage load decreased to reduce the capability of work, the tip low speed range increases.

关键词： back-to-back two-stage centrifugal compressor design Internal flow

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基于GA－BP网络的人工湿地污水净化效果研究

黄娟,王世和,雒维国,钱卫一,鄢璐

《中国工程科学》 2007年第9卷第2期页码 79-83

摘要：基于大量可靠的试验数据，首次采用遗传神经网络方法模拟湿地除污系统，详细论述了网络拓扑结构优化和训练数据预处理等关键问题，建立了可靠的GA－BP模型，并采用该模型仿真湿地系统正交试验，依据正交试验结果对影响因素进行分级

关键词：人工湿地污水净化 GA-BP网络正交试验

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Choosing configurations of transmission line tower grounding by back flashover probability value

Dmitry KUKLIN

《能源前沿（英文）》 2016年第10卷第2期页码 213-226 doi: 10.1007/s11708-016-0398-6

摘要： There is a considerable number of works devoted to electrical characteristics of grounding. These characteristics are important in general. However, in application to grounding of transmission line towers they are not enough to determine what grounding construction is preferable in some particular case, because these characteristics are calculated or measured apart from the grounded object, and only limited number of current (or voltage) source waveforms is used. This paper indicates reasons in favor of the fact that to choose the optimum design of grounding, the calculation model should include the tower as it is. The probability of back flashover, which provides both qualitative and quantitative estimate of the grounding structure efficiency, can be taken as the criterion for the grounding design. The insulation flashover probability is calculated on the basis of engineering method, which evaluates breakdown strength of insulation for nonstandard waveshapes, and probability data on lightning currents. Different approaches are examined for identifying the back flashover probability, as not only amplitudes but also other parameters can be taken into account. Finite-difference time-domain method is used for calculations of transients. It is found that lightning current waveform can greatly influence calculated back flashover probability value.

关键词： grounding transmission line tower back flashover probability FDTD method

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基于正交实验的BP神经网络预测研究

蔡安辉,刘永刚,孙国雄

《中国工程科学》 2003年第5卷第7期页码 67-71

摘要：

用不同的L₉（3⁴）正交实验方案结果作为训练学习样本集，对BP神经网络预测应用过程的策略进行了探讨，结果表明：完备的正交实验样本集是基本训练学习单元，在完备的正交实验样本集上添加或减少样本数量同一实验的条件下，完备的信息量大的正交实验样本集，能以很高的精度预测完备的信息量小的正交实验样本集；提出了一条新的实验设计思路——通过实验得出一个完备的正交实验样本集，通过计算机用BP

关键词： BP神经网络正交实验策略实验设计思路样本集

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一种改进BP算法在机械手逆运动学中的应用

吴爱国,郝润生

《中国工程科学》 2005年第7卷第7期页码 34-38

摘要：

通过对传统BP算法的分析，提出了一种改进激励函数的学习方法，并且在神经网络的每一层采用不同的学习速率，以提高训练速度；采用所提出的改进BP算法，训练多层前向神经网络，建立机械手逆运动学模型，仿真结果表明了该算法的有效性；与传统BP算法相比，大大提高了机械手逆运动学的精度。

关键词：神经网络 BP算法激励函数机械手逆运动学

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DFIG sliding mode control fed by back-to-back PWM converter with DC-link voltage control for variable

Youcef BEKAKRA,Djilani BEN ATTOUS

《能源前沿（英文）》 2014年第8卷第3期页码 345-354 doi: 10.1007/s11708-014-0330-x

摘要： This paper proposes an indirect power control of doubly fed induction generator (DFIG) with the rotor connected to the electric grid through a back-to-back pulse width modulation (PWM) converter for variable speed wind power generation. Appropriate state space model of the DFIG is deduced. An original control strategy based on a variable structure control theory, also called sliding mode control, is applied to achieve the control of the active and reactive power exchanged between the stator of the DFIG and the grid. A proportional-integral-(PI) controller is used to keep the DC-link voltage constant for a back-to-back PWM converter. Simulations are conducted for validation of the digital controller operation using Matlab/Simulink software.

关键词： doubly fed induction generator (DFIG) wind turbine back-to-back pulse width modulation (PWM) DC-link voltage sliding mode control

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基于BP神经网络的工程图形数据远程安全快速传输法

秦威,秦书玉

《中国工程科学》 2007年第9卷第1期页码 49-52

摘要：根据图形的几何元素相关性的特征，建立参数结构，采用人工神经网络BP算法同时进行数据编码压缩和数据加密，实现复杂工程图形数据的远程高效安全传输。实例表明，此方法可用于实际工程。

关键词：神经网络 BP算法相关性加密快速传输图形数据

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Optimization of turbine cold-end system based on BP neural network and genetic algorithm

Chang CHEN,Danmei XIE,Yangheng XIONG,Hengliang ZHANG

《能源前沿（英文）》 2014年第8卷第4期页码 459-463 doi: 10.1007/s11708-014-0335-5

摘要： The operation condition of the cold-end system of a steam turbine has a direct impact on the economy and security of the unit as it is an indispensible auxiliary system of the thermal power unit. Many factors influence the cold-end operation of a steam turbine; therefore, the operation mode needs to be optimized. The optimization analysis of a 1000 MW ultra-supercritical (USC) unit, the turbine cold-end system, was performed utilizing the back propagation (BP) neural network method with genetic algorithm (GA) optimization analysis. The optimized condenser pressure under different conditions was obtained, and it turned out that the optimized parameters were of significance to the performance and economic operation of the system.

关键词： optimization turbine cold-end system BP neural network genetic algorithm