The Application of the Fuzzy Neural Network Control in Elevator Intelligent Scheduling Simulation

Yin-e, Zhang; Ye, Yun; Zhong, Jian

doi:10.1109/isise.2010.129

Cited by 6 publications

(2 citation statements)

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“…As shown in Figure 4, firstly it needs to set safety coefficient of finance by the combination with the financial management process of electric power enterprise, so in this system, the number of neurons of hidden layer is set as that can be adjusted according to the demanded [11]. On this basis, it makes the BP neural network of single hidden layer be able to approximately be close to any nonlinear mapping which has more hidden layer's changes, so as to carry out the correction of error and training values, and to test the correction coefficient.…”

Section: Advanced Engineering Solutionsmentioning

confidence: 99%

Computer Simulation Technology of Electric Power Safety Based on Fuzzy Neural Network

Zheng

2014

AMM

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As the basis industry of the national economy electric power enterprise is shouldering significant social responsibility in the process of operation, also needs to face the operational risk generated by enterprise competition under the conditions of market economy. How to scientifically and efficiently manage the financial risks of power enterprises is one of the hot issues that are urgent needed to resolve in the current field. In this paper, on the basis of previous studies, firstly has combined with the structure characteristics of the fuzzy neural network model. Then it builds prediction analysis model of financial risks according to the fuzzy neural network structure. And it sets the selection of the number of neuron for the hidden layer based on the financial risks' characteristics of electric power enterprise. At last, it combines with 12 financial indicators data of electric power enterprise finance to make further computer simulation, so as to verify the scientificity of the model. And the results show that the model has strong reliability and a strong practical value.

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Section: Advanced Engineering Solutionsmentioning

confidence: 99%

Computer Simulation Technology of Electric Power Safety Based on Fuzzy Neural Network

Zheng

2014

AMM

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“…The fuzzy logic algorithm has been implemented in the optimization. A fuzzy BP neutral network for multiple elevator operation is introduced to further improve the performance of lift system [52]. However, the input data such as the average waiting time, power consumption, and floor traffic, etc.…”

Section: Control Strategy Of Hybrid Microgridmentioning

confidence: 99%

Coordination control of hybrid AC/DC building microgrid

Zhu¹

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Advantages such as environmental friendliness and flexibility have made microgrid an attractive option for in modern power systems. Microgrid is a localized grouping of distributed generators, storages and loads. Microgrid integrates with sustainable energy sources could reduce carbon emission. A microgrid can serve specific purposes, such as to enhance reliability, diversification of energy sources, and cost reduction. Therefore, microgrid has been introduced into building distributed networks as it makes both power generation and consumption more efficient. In Introduction Chapter 1 1 Chapter 1 Introduction Buildings are considered to be among the largest energy consumption unites in modern cities. With the increase of building energy consumption, the drawbacks of conventional building power distributed network topology arise progressively. The theme of this thesis is to design a novel building hybrid microgrid and its coordination control. Each subsystem in this novel building hybrid microgrid is designed to improve the whole system efficiency and meet specific requirements. The objectives and structure of this thesis are introduced in this chapter. 1.2.4 Simplify the hybrid energy storage controller Based on the building microgrid configuration, hybrid building energy storage system (HBES) has different operating modes. Energy storage converters are able to work in either voltage regulation mode or power exchange mode. The proposed adaptive area droop control is introduced to HBES which could automatically alter the energy storage operating mode by changing the droop coefficient. The energy storage converter does not need multiple controllers to achieve different objectives. This also means that the energy storage converter is simplified. 1.2.5 Extend the DC output voltage range A highly efficient single-phase PFC converter features sinusoidal input current, three-level output characteristic and flexible output DC voltage. Its attractiveness is that the embedded bidirectional DC/DC buck converter only needs to process partial input power rather than full scale of input power, and therefore energy conversion efficiency can be largely improved compared with the conventional two stage solution. Also, the PFC stage exhibits three-levels of output voltage, and the An added benefit of this converter is that, the fluctuating 100Hz or 120Hz harmonic power in the single-phase system can be diverted into the dc-link capacitor through proper control design, and the terminal voltage and/or the charging current of battery pack will be fairly constant, which may expand its working lifetime. Its operation principle and control strategies are discussed in detail in this paper, and both simulations and experimental results are provided for validation. Chapter 7 concludes the research findings presented in this thesis and suggests some prospective research topics for future investigation.

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Elevator Control Chip Design

Yue

2021

2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI)

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The Application of the Fuzzy Neural Network Control in Elevator Intelligent Scheduling Simulation

Cited by 6 publications

References 0 publications

Computer Simulation Technology of Electric Power Safety Based on Fuzzy Neural Network

Computer Simulation Technology of Electric Power Safety Based on Fuzzy Neural Network

Coordination control of hybrid AC/DC building microgrid

Elevator Control Chip Design

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