At Rolls-Royce, genetic algorithm has been applied to identify solutions to calibration problems. The inclusion of fuzzy logic to rank the solutions reduced ambiguity without requiring the large number of results and ...
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At Rolls-Royce, genetic algorithm has been applied to identify solutions to calibration problems. The inclusion of fuzzy logic to rank the solutions reduced ambiguity without requiring the large number of results and detailed physical understanding of the problem required in rigorous statistical approaches. Fuzzy logic also appeared to be an effective method of including engineering judgment in the form of qualitative rules.
Kauffman has proposed a theory of cell differentiation using random boolean nets as a model of genetic action. This scheme is used as the basis of a developmental representation in the context of geneticalgorithms. A...
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Kauffman has proposed a theory of cell differentiation using random boolean nets as a model of genetic action. This scheme is used as the basis of a developmental representation in the context of geneticalgorithms. A number of simple linear morphologies are evolved using this system.
This paper proposes a fitness function for geneticalgorithms used in control system design based on derived response shape. A technique is presented that allows control system performance to be specified as constrain...
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This paper proposes a fitness function for geneticalgorithms used in control system design based on derived response shape. A technique is presented that allows control system performance to be specified as constraints on the system response rather than an error function. A genetic algorithm is used to solve the resulting constrained optimization problem with the nonlinearity of the cost function. A design example of practical PID control of a lift system is given showing the flexibility of this type of control system specification and the performance achieved.
This paper develops a new approach to the design of robust fault detection systems via a genetic algorithm. To achieve robustness, a number of performance indices are introduced. Some performance indices are expressed...
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This paper develops a new approach to the design of robust fault detection systems via a genetic algorithm. To achieve robustness, a number of performance indices are introduced. Some performance indices are expressed in the frequency domain to account for the frequency distributions of incipient faults, noise and modelling uncertainty. All objectives are then reformulated into a set of inequality constraints on performance indices. A genetic algorithm is thus used to search an optimal solution to satisfy these inequality constraints. The approach developed is applied to a flight control system example and results show that incipient sensor faults can be detected reliably in the presence of modelling uncertainty.
This paper presents the application of geneticalgorithms to power system stabilizers. The stabilizers which are used in this study are of proportional-integral-derivative (PID) and lead/lag form. The aim is to invest...
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This paper presents the application of geneticalgorithms to power system stabilizers. The stabilizers which are used in this study are of proportional-integral-derivative (PID) and lead/lag form. The aim is to investigate the optimization of the parameters of the stabilizer using geneticalgorithms. The results show that the proposed GA can find suitable parameters for such stabilizers which are sufficiently close to global optimum values.
Most classical approaches to the determination of geodesics (such as the calculus of variations) are difficult to apply except for simple surfaces. geneticalgorithms are therefore used to provide a general methodolog...
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Most classical approaches to the determination of geodesics (such as the calculus of variations) are difficult to apply except for simple surfaces. geneticalgorithms are therefore used to provide a general methodology for the computation of geodesics.
geneticalgorithms provide a basis for automatic synthesis of analogue electronic networks. Passive linear networks have been generated to meet both frequency-domain and time-domain specifications. The networks genera...
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geneticalgorithms provide a basis for automatic synthesis of analogue electronic networks. Passive linear networks have been generated to meet both frequency-domain and time-domain specifications. The networks generated are both novel and effective. It should be possible to extend the technique to deal with active networks.
A procedure to optimize finite element models of engine structures for low noise using geneticalgorithms was investigated. Experiments were performed on a simple engine block model with 1800 degrees of freedom to stu...
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A procedure to optimize finite element models of engine structures for low noise using geneticalgorithms was investigated. Experiments were performed on a simple engine block model with 1800 degrees of freedom to study the effects of changing the control parameters. The procedure was then applied to the optimization of a concept level model with 13500 degrees of freedom. Optimization of this model yielded a reduction the predicted noise of 1.7 dB(A) for no mass increase and 2.3 dB(A) for an increase in mass of 5 per cent.
The Database Mining Research Group within the School of Information and Software engineering, at the University of Ulster, Jordanstown, has set two main objectives for its work. The first objective is to devise improv...
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The Database Mining Research Group within the School of Information and Software engineering, at the University of Ulster, Jordanstown, has set two main objectives for its work. The first objective is to devise improved data mining algorithms for mining classification and association rules. Some of the areas of improvement being investigated are: more efficient algorithms;wider algorithm scope;noisy data handling;incorporation of prior knowledge into algorithms;and measures of interestingness. The second objective is to evaluate the algorithms on real world data sets. The use of data mining techniques on data sets from the Northern Ireland Housing Executive (NIHE) is also investigated.
This paper describes the use of multiobjective geneticalgorithms (MOGAs) in the design of a multivariable control system for a gas turbine engine. It is shown how the MOGA confers an immediate advantage over conventi...
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This paper describes the use of multiobjective geneticalgorithms (MOGAs) in the design of a multivariable control system for a gas turbine engine. It is shown how the MOGA confers an immediate advantage over conventional multiobjective optimization methods by evolving a family of Pareto-optimal solutions allowing the control engineer to examine the trade-offs between the different design objectives. In addition, the paper demonstrates how the genetic algorithm can be used to search in both controller structure and parameter space thereby offering a potentially more general approach to optimization in controller design than traditional numerical methods.
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