By Patricia Melin, Oscar Castillo, Janusz Kacprzyk
This publication offers fresh advances at the layout of clever platforms in accordance with fuzzy good judgment, neural networks and nature-inspired optimization and their software in parts corresponding to, clever keep watch over and robotics, trend popularity, time sequence prediction and optimization of complicated difficulties. The e-book is geared up in 8 major components, which include a gaggle of papers round the same topic. the 1st half includes papers with the most topic of theoretical facets of fuzzy good judgment, which primarily comprises papers that suggest new recommendations and algorithms in keeping with fuzzy platforms. the second one half includes papers with the most subject matter of neural networks conception, that are primarily papers facing new suggestions and algorithms in neural networks. The 3rd half comprises papers describing functions of neural networks in different parts, comparable to time sequence prediction and trend reputation. The fourth half comprises papers describing new nature-inspired optimization algorithms. The 5th half provides different purposes of nature-inspired optimization algorithms. The 6th half comprises papers describing new optimization algorithms. The 7th half includes papers describing purposes of fuzzy common sense in varied parts, equivalent to time sequence prediction and development reputation. eventually, the 8th half includes papers that current improvements to meta-heuristics in accordance with fuzzy common sense suggestions.
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Additional info for Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization
In addition, MexDer (the Mexican Derivatives Exchange) is also part of MSE Group and is the leading marketplace for trading benchmark Mexican derivatives products. The MSE time series we are using 800 pair data (Fig. 4) that correspond from period of 11/09/2005 to 01/15/09  of the IPC (which stands for “Indice de Precios y Cotizaciones”) is the broadest indicator of the MSE overall performance. 6 0 100 200 300 400 500 600 700 800 Days (time) Fig. 4 Mexican stock exchange time series 3 General Architecture of the Proposed Method The proposed method combines the ensemble of ANFIS models and the use of interval type-2 fuzzy systems as response integrators (Fig.
Melin Fig. 5 Results and Comparison Table 1 shows the results of 30 experiments that were made with the genetic optimization of interval type-2 fuzzy integrators in ensembles of ANFIS models for the time series prediction. This Table shows the comparison result (best, mean and standard deviation “STD”) of the prediction error for the optimization of the interval type-2 fuzzy integrators (used two and three MFs for each integrator). 000596 (STD). 000392 (STD). 097165. Table 2 shows the results of 30 experiments that were made with the genetic optimization of interval type-2 and type-1 fuzzy integrators in ensembles of ANFIS models for the time series prediction.
8) because the performance is better and minimized the prediction error of the Dow Jones time series. Fig. 2 Design the Representation of the Chromosome of Genetic Algorithms for Optimizer the MFs in the Fuzzy Integrators The GAs are used to optimize the parameters values of the MFs in each interval type-2 fuzzy integrators. The representation of GAs is of Real-Values and the chromosome size will depend of the MFs that are used in each design of the interval type-2 fuzzy inference system integrators.