Fuzzy Systems and Soft Computing in Nuclear Engineering

Ruan, Da

doi:10.1007/978-3-7908-1866-6

Cited by 8 publications

References 65 publications

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Optimizing Nuclear Reactor Operation Using Soft Computing Techniques

Entzinger

Ruan

Fuzzy Applications in Industrial Engineering

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Summary. The strict safety regulations for nuclear reactor control make it difficult to implement new control techniques such as fuzzy logic control (FLC). FLC however, can provide very desirable advantages over classical control, like robustness, adaptation and the capability to include human experience into the controller. Simple fuzzy logic controllers have been implemented for a few nuclear research reactors, among which the Massachusetts Institute of Technology (MIT) research reactor [1] in 1988 and the first Belgian reactor (BR1) [2] in 1998, though only on a temporal basis.The work presented here is a continuation of earlier research on adaptive fuzzy logic controllers for nuclear reactors at the SCK • CEN [2, 3, 4] and [5] (pp 65-82). A series of simulated experiments has been carried out using adaptive FLC, genetic algorithms (GAs) and neural networks (NNs) to find out which strategies are most promising for further research and future application in nuclear reactor control.Hopefully this contribution will lead to more research on advanced FLC in this domain and finally to an optimised and intrinsically safe control strategy.

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Optimizing Nuclear Reactor Operation Using Soft Computing Techniques

Entzinger

Ruan

Fuzzy Applications in Industrial Engineering

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Demand Forecasting Method Using Artificial Neural Networks

Viloria

Matos

Gaitan

et al. 2019

Communications in Computer and Information Science

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Based on a forecast, the decision maker can determine the capacity required to meet a certain forecast demand, as well as carry out in advance the balance of capacities in order to avoid underusing or bottlenecks. This article proposes a procedure for forecasting demand through Artificial Neural Networks. In order to carry out the validation, the procedure proposed was applied in a Soda Trading and Distribution Company where three types of products were selected.

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A fuzzy decision support system for the economic calculus in radioactive waste management

Kunsch

Fortemps

2002

Information Sciences

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Fuzzy Systems and Soft Computing in Nuclear Engineering

Cited by 8 publications

References 65 publications

Optimizing Nuclear Reactor Operation Using Soft Computing Techniques

Optimizing Nuclear Reactor Operation Using Soft Computing Techniques

Demand Forecasting Method Using Artificial Neural Networks

A fuzzy decision support system for the economic calculus in radioactive waste management

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