To realize or implement the large dimensional image data, it may be taking a longer search time to detect the desired target. Recently, for the large amount of data and information in engineering or biomedical applications, various techniques including soft-computing techniques such as neural networks, fuzzy logic, or genetic algorithms, and multivariate analysis techniques like factor analysis...

Understanding data is one of most important problems. Popular crisp logic rules are easy to understand and compare, however for some datasets the number of extracted rules is very large, what affect reduction of generalization and makes the system less transparent. Another solution are fuzzy logic rules, which are much more flexible, however they don’t support symbolic and nominal attributes. A...

due to the fact that the error surface of adaptive infinite impulse response (iir) systems is generally nonlinear and multimodal, the conventional derivative based techniques fail when used in adaptive identification of such systems. in this case, global optimization techniques are required in order to avoid the local minima. harmony search (hs), a musical inspired metaheuristic, is a recently ...

This study proposed a model-based robust fault detection (RFD) method using soft computing techniques. Robust detection of the possible realistic incipient faults of an industrial gas turbine engine in steady-state conditions is mainly centered. For residual generation a bank of Multi-Layer perceptron (MLP) models, is used, Moreover, in fault detection phase, a passive approach based on Modelli...

It is known that control signals from a fuzzy logic controller are determined by a response behavior of a controlled object rather than its analytical models. That implies that the fuzzy controller could yield a similar control result for a set of plants with a similar dynamic behavior. This idea leads to modeling of a plant with unknown structure by defining several types of dynamic behavior, ...

This paper presents a comparative analysis of the performance of fuzzy approaches on the task of predicting customer review ratings using a computational intelligence framework based on a genetic algorithm for data dimensionality reduction. The performance of the Fuzzy C-Means (FCM), a neurofuzzy approach combining FCM and the Adaptive Neuro Fuzzy Inference System (ANFIS), and the Simplified Fu...