23,921 research outputs found
An artificial immune systems based predictive modelling approach for the multi-objective elicitation of Mamdani fuzzy rules: a special application to modelling alloys
In this paper, a systematic multi-objective Mamdani fuzzy modeling approach is proposed, which can be viewed as an extended version of the previously proposed Singleton fuzzy modeling paradigm. A set of new back-error propagation (BEP) updating formulas are derived so that they can replace the old set developed in the singleton version. With the substitution, the extension to the multi-objective Mamdani Fuzzy Rule-Based Systems (FRBS) is almost endemic. Due to the carefully chosen output membership functions, the inference and the defuzzification methods, a closed form integral can be deducted for the defuzzification method, which ensures the efficiency of the developed Mamdani FRBS. Some important factors, such as the variable length coding scheme and the rule alignment, are also discussed. Experimental results for a real data set from the steel industry suggest that the proposed approach is capable of eliciting not only accurate but also transparent FRBS with good generalization ability
An immune algorithm based fuzzy predictive modeling mechanism using variable length coding and multi-objective optimization allied to engineering materials processing
In this paper, a systematic multi-objective fuzzy
modeling approach is proposed, which can be regarded
as a three-stage modeling procedure. In the first stage, an
evolutionary based clustering algorithm is developed to
extract an initial fuzzy rule base from the data. Based on
this model, a back-propagation algorithm with momentum
terms is used to refine the initial fuzzy model. The refined
model is then used to seed the initial population of an
immune inspired multi-objective optimization algorithm
in the third stage to obtain a set of fuzzy models with
improved transparency. To tackle the problem of
simultaneously optimizing the structure and parameters, a
variable length coding scheme is adopted to improve the
efficiency of the search. The proposed modeling approach
is applied to a real data set from the steel industry.
Results show that the proposed approach is capable of
eliciting not only accurate but also transparent fuzzy
models
Determining a Robust, Pareto Optimal Geometry for a Welded Joint
Multi-criteria optimization problems are known to give rise to a set of Pareto optimal solutions where one solution cannot be regarded as being superior to another. It is often stated that the selection of a particular solution from this set should be based on additional criteria. In this paper a methodology has been proposed that allows a robust design to be selected from the Pareto optimal set. This methodology has been used to determine a robust geometry for a welded joint. It has been shown that the robust geometry is dependent on the variability of the geometric parameters
The 1/5-th Rule with Rollbacks: On Self-Adjustment of the Population Size in the GA
Self-adjustment of parameters can significantly improve the performance of
evolutionary algorithms. A notable example is the
genetic algorithm, where the adaptation of the population size helps to achieve
the linear runtime on the OneMax problem. However, on problems which interfere
with the assumptions behind the self-adjustment procedure, its usage can lead
to performance degradation compared to static parameter choices. In particular,
the one fifth rule, which guides the adaptation in the example above, is able
to raise the population size too fast on problems which are too far away from
the perfect fitness-distance correlation.
We propose a modification of the one fifth rule in order to have less
negative impact on the performance in scenarios when the original rule reduces
the performance. Our modification, while still having a good performance on
OneMax, both theoretically and in practice, also shows better results on linear
functions with random weights and on random satisfiable MAX-SAT instances.Comment: 17 pages, 2 figures, 1 table. An extended two-page abstract of this
work will appear in proceedings of the Genetic and Evolutionary Computation
Conference, GECCO'1
- …