evolutionary neural fuzzy systems
Credit rating using fuzzy algorithms
... used: neural networks (NNs) [5], [19], [20], [11] fuzzy systems[2], [11], evolutionary algorithms [6], artificial immune systems [8], [22], hybrid systems [20], and support ...
10
Hybrid soft computing systems for electromyographic signals analysis: a review
... artificial neural networks (ANN), evolutionary computing (EC), fuzzy logic (FL), and swarm intelligence (SI) have been the most widely-used in the past few years ...
19
Implementation of Evolutionary Computing Techniques for Cancer Diagnosis Using Digital Signal Processor
... on systems that use knowledge based techniques to support human decision- making, learning and ...Such systems are capable of cooperating with human user and so the quality of support given and the manner ...
7
Evolving Intelligent Systems, eIS
... learning neural networks methods in direction of on-line applications with a structure that can grow and ...intelligent systems’ can also be treated in the framework of the knowledge and data ...
13
Adaptive and intelligent navigation of autonomous planetary rovers – a survey
... of evolutionary and swarm algorithms for solving the problem of path planning due to their suitability for handling large, complex ...minima. Evolutionary and swarm algorithms have also been combined with ...
8
Vol 9, No 1 (2014)
... Evolutionary computing has facilitated numerous real life applications. Genetic Algorithms are one of the pioneer method that works on principle of natural genetics to provide search and optimization facility. ...
13
International Journal of Computer Science and Mobile Computing
... like Fuzzy Sets (FSs), Artificial Neural Networks (ANNs), evolutionary computation, Rough Sets (RSs), and Support Vector Machines (SVMs), biologically inspired algorithm like ant colony system, swarm ...
6
An Adaptive Neural Network Fuzzy Inference Controller Using Predictive Evolutionary Tuning
... nonlinear systems continues to be a challenging problem, particularly when the system is uncertain or the environment ...a neural network to learn about the unknown plant and fuzzy inference to ...
6
Survey on Various Types of Noise and Methods for Noise Removal
... Intelligent systems are capable to provide efficient and powerful decision making in real ...intelligent systems which are not available in traditional information ...expert systems, natural language ...
6
Computational Web Intelligence Intelligent Technology for Web Applications Y Q Zhang pdf
... His research interests include hybrid intelligent systems, neural networks, fuzzy logic, evolutionary computation, kernel machines, granular computing, computational Web intelligence, in[r] ...
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Intelligent System for Efficiency Enhancing Program of Thermal Power Plant: A Case Study
... intelligent systems. It is based on fuzzy logic, artificial neural networks and probabilistic reasoning including genetic ...intelligent systems,aimed at a formalization of the remarkable ...
6
Microwave neural networks and fuzzy classifiers for ES systems
... Above all, the present approach explores the fact that frequently the missions destined F^RSuch ES systems are not as demanding as, for instance, the expected Soviet threat in the “cold war” period. In opposition ...
241
A Comparison and Analysis of Soft Computing Techniques for Content based Image Retrieval System
... image. Fuzzy logic has been extensively used at various stages of image retrieval such as region groupings within the images as a feature extraction technique, for measuring the similarity between the target image ...
6
Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... the Fuzzy Adaptive Learning Control/Decision Network (FALCON)-Based Fault Detector (FFD), and the Adaptive-Network-Based Fuzzy Inference System (ANFIS)-Based Fault Detector ...
11
A Hybrid Intelligent Decision Making System for Navigation with Optimized Performance
... the Fuzzy Facts deal with imprecise ...utilize fuzzy logic for authentic world quandaries we require to first define the control objectives and criteria and the possible failure ...results. Fuzzy ...
5
Study of Existing Work on Soft Computing Methodologies and Fusion of Neural Network and Fuzzy Logic for Estimation and Approximation
... Artificial Neural Networks (ANNS) were first introduced by McCulloch and Pitt [9], in 1940s based on the observation that human brain consist of numerous interconnected neurons encapsulating the most rare thing in ...
15
A Neuro-Fuzzy System For Diagnosis of Soya-Beans Diseases
... of fuzzy logic and neural network in solving large number of problems such as prediction and classification rate in crop disease modeling in the developing ...
12
Modelling Metal cutting Parameters Using Intelligent Techniques
... The initial step in ANN-based data processing system is determining the inputs of the neural network. The input layer of both ANNs has three neurons: (1) Cutting speed, (2) Feed rate and (3) Depth of cut. The ANN ...
11
Computational Intelligence in Manufacturing Handbook Jun Wang pdf
... feedforward neural network trained with the BP algorithm to model bead geometry with recorded arc welding ...The neural network was a fairly accurate static model of the welding process and could be ...
560
State of the art of machine learning models in energy systems: A systematic review
... energy systems has resulted in a massive amount of data ...energy systems are essential for predictive modeling of production, consumption, and demand analysis due to their accuracy, efficacy and speed ...
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