Introduction to Fuzzy Systems, Neural Networks, and Genetic Algorithms
نویسنده
چکیده
Soft Computing technologies are the main topics of this book. This chapter provides the basic knowledge of fuzzy systems (FSs), neural networks (NNs), and genetic algorithms (GAs). Readers who have already studied these technologies may skip the appropriate sections. To understand the functions of FSs, NNs, and GAs, one needs to imagine a multi-dimensional input–output space or searching space. Figure 1 is an example of such a space.
منابع مشابه
INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES
The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...
متن کاملPrediction of Gain in LD-CELP Using Hybrid Genetic/PSO-Neural Models
In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...
متن کاملPrediction of Gain in LD-CELP Using Hybrid Genetic/PSO-Neural Models
In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...
متن کاملComparison of Genetic and Hill Climbing Algorithms to Improve an Artificial Neural Networks Model for Water Consumption Prediction
No unique method has been so far specified for determining the number of neurons in hidden layers of Multi-Layer Perceptron (MLP) neural networks used for prediction. The present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. The data used in the present research for prediction are consumption data of water...
متن کاملCompensatory Genetic Fuzzy Neural Networks and Their Applications
compensatory genetic fuzzy neural networks and their applications neural networks fuzzy logic and genetic algorithms by rajasekaran and g a v pai ebook free download nonlinear workbook chaos fractals cellular automata neural networks genetic algorithms gene expression programming wavelets fuzzy logic with c java and symbolicc programs applications of neural networks in environment energy and he...
متن کامل