Soft computing and fractal theory for industrial applications

O. Castillo, P. Melin
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Abstract

This tutorial will show how to use different Soil Computing (SC) techniques for the development of hybrid intelligent systems for industrial applications. SC techniques, at the moment, include Neural Networks, Fuzzy Logic, Genetic Algorithms and Chaos Theory. We also consider the use of Fractal Theory for pattern recognition and time series analysis. Each of these methodologies has its advantages and disadvantages and many problems have been solved, by using one of these methodologies. However, many real-world complex industrial problems require the integration of several of these methodologies to really achieve the efficiency and accuracy needed in practice. In this tutorial a brief introduction to SC methodologies will be given. Then, different methods for integrating the different SC methodologies in solving real-world problems will be described. At the end, the integration methodologies will he illustrated with real hybrid intelligent systems that have been developed for applications like: Food Processing Plants, Robotic Systems, Automated Quality Control, Financial and Economic Forecasting, and Manufacturing Systems, Those attending can expect to gain awareness of the role of SC methodologies and their integration in solving real world complex problems.
工业应用中的软计算和分形理论
本教程将展示如何使用不同的土壤计算(SC)技术开发用于工业应用的混合智能系统。目前,SC技术包括神经网络、模糊逻辑、遗传算法和混沌理论。我们也考虑使用分形理论的模式识别和时间序列分析。每种方法都有其优点和缺点,并且通过使用其中一种方法已经解决了许多问题。然而,许多现实世界中复杂的工业问题需要将其中几种方法集成在一起,才能真正实现实践中所需的效率和准确性。在本教程中,将简要介绍SC方法。然后,将描述整合不同SC方法来解决现实问题的不同方法。最后,他将用真正的混合智能系统来说明集成方法,这些系统已经被开发用于食品加工厂、机器人系统、自动化质量控制、金融和经济预测以及制造系统等应用。与会者可以期望了解SC方法的作用及其在解决现实世界复杂问题中的集成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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