Tutorial HIMA-T Hybrid intelligent systems with Soft Computing techniques

2009 ◽  
Author(s):  
Oscar Castillo ◽  
Patricia Melin
Keyword(s):  
Soft Computing ◽  
Intelligent Systems ◽  
Hybrid Intelligent Systems ◽  
Soft Computing Techniques

Hybrid Intelligent Systems for Medical Diagnosis

2010 ◽  
pp. 187-202 ◽  
Author(s):  
Rahul Kala ◽  
Anupam Shukla ◽  
Ritu Tiwari
Keyword(s):  
Medical Diagnosis ◽  
Intelligent Systems ◽  
Fuzzy Inference ◽  
Back Propagation ◽  
Medical Engineering ◽  
Back Propagation Algorithm ◽  
Hybrid Intelligent Systems ◽  
Neuro Fuzzy ◽  
Soft Computing Techniques ◽  
Inference Systems

In this chapter authors describe the application of various soft computing techniques in the field of medical diagnosis. They also explained new approaches being applied to the field of Bio-Medical Engineering as well as many new models being proposed, like Hybrid Systems and standard Back Propagation Algorithm for this purpose. These are Adaptive Neuro Fuzzy Inference Systems, Ensembles and Evolutionary Artificial Neural Networks.

scholarly journals Fuzzy logic research work in Mexico motivated by Lotfi Zadeh

2021 ◽  
Vol 27 (2) ◽  
pp. 1-10
Author(s):  
Oscar Castillo ◽  
◽  
Patricia Melin ◽  
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Systems ◽  
Intelligent Systems ◽  
High Performance ◽  
Research Work ◽  
Short Review ◽  
Swarm Algorithms ◽  
Soft Computing Techniques

We provide in this article a short review of the research work that has been done in Mexico on developing new methods and theory for designing intelligent systems utilizing type-2 fuzzy systems in combination with soft computing techniques. Soft Computing (SC) is an area formed by intelligent paradigms, like fuzzy systems, neural networks, and bio-inspired and swarm algorithms, which may be utilized to build high performance hybrid systems. The combination of type-2 fuzzy systems with SC enables the constructing of efficient intelligent systems for solving complex problems in a wide diversity of areas, such as control, pattern recognition, medical diagnosis and others. We also recall some of the main moments and memories of encounters and meetings with the father of fuzzy logic (Prof. L. Zadeh), which were very positive and motivated us to continue his work and legacy.

scholarly journals Weather Predictions using Support Vector Machine and Rough Set

2019 ◽  
Vol 9 (2) ◽  
pp. 5513-5516
Keyword(s):  
Soft Computing ◽  
Rough Set ◽  
Intelligent Systems ◽  
Promising Result ◽  
Weather Prediction ◽  
Support Vector ◽  
Climate Modelling ◽  
Specific Domain ◽  
Computing Technique ◽  
Soft Computing Techniques

Climate modelling and weather prediction, the application of science and technology to predict the state of the atmosphere for a given location is a challenging task for the researchers in this modern age.Now-a-days the soft computing techniques have been evolved which can be used for the prediction of weather with more accuracy and less errors. But, Soft computing technique is a new approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments. Hence, this paper tries to analyze soft computing techniques i.e Rough Set and SVM for weather prediction of Delhi and reveals that Rough set exhibits promising result that SVM.

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