neural/fuzzy systems
The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models
... Hybrid neural networks – based systems, are based on an architecture which integrates the neural networks and the fuzzy logic based system in the form of parallel ...the neural networks ...
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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 ...
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Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
... a fuzzy if–then rule base so that a desired input/output mapping is ...a fuzzy rule base has received more attention ...optimizing fuzzy reason- ing via NN structures [15]–[21]. Parameters in ...
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Optimized Scheduling of Generating Unit for Economic Load Dispatch using Neuro Fuzzy Expert Systems
... Neuro Fuzzy Systems generally are based on expert view or fuzzy logic for deciding the thresholds or boundaries. Subsequently the data is fed to neural network for training. After training the ...
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Study of Existing Work on Soft Computing Methodologies and Fusion of Neural Network and Fuzzy Logic for Estimation and Approximation
... such systems is essential because humans do not think in precise ...neuro-fuzzy systems is to mimic human thought and ...of neural network architecture for learning to solve different ...
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Modelling Metal cutting Parameters Using Intelligent Techniques
... (artificial neural networks and neuro-fuzzy systems) in the modeling of the cutting process parameters, and not measuring the exact value of maximum cutting ...
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Evolving Intelligent Systems, eIS
... Intelligent systems can be defined as systems that incorporate some form of reasoning that is typical for ...humans. Fuzzy Systems are well known for being able to formalize the approximate ...
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Adaptive and intelligent navigation of autonomous planetary rovers – a survey
... with fuzzy systems and neural networks (these are further discussed ...manual fuzzy, genetic algorithm-based fuzzy, PSO-based fuzzy, and neuro-fuzzy) to assess the ...
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A Neuro-Fuzzy System For Diagnosis of Soya-Beans Diseases
... Soyabean is an important legume crop, extensively cultivated for food on which low-income population highly depend because of its proteineous nutrient on daily basis for food.The efforts of farm- ers to specifically ...
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Computational Intelligence in Manufacturing Handbook Jun Wang pdf
... of neural networks for process monitoring and control include tool wear monitoring, machining process monitoring, process modeling, and process ...The neural network models used were multilayer feedforward ...
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Neuro fuzzy Modeling of an Eco friendly Melting Furnace Parameters using Bio fuels for the Agile Production of Quality Castings
... extracting fuzzy knowledge from numerical data and linguistic data into the ...applying fuzzy logic for systems represented by numerical knowledge (data sets), or in applying neural networks ...
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Dental Expert System
... Since then, researchers have applied different methods to provide clinical applications with knowledge. More recent work on Dental expert system has focused on integration of these applications with clinical databases. ...
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Type-2 Fuzzy Logic Approach To Increase The Accuracy Of Software Development Effort Estimation
... of neural network and fuzzy logic, determines the parameters of the fuzzy system using the neural network learning ...the fuzzy system, indicative of uncertainty. Simultaneous ...
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A Hybrid Intelligent Decision Making System for Navigation with Optimized Performance
... CNN’s can be trained to accomplish a specific task just like human brain as they are very good in extracting features relevant to find a particular task. It enables us to have a spatial outlook in which each layer ...
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SIGN LANGUAGE RECOGNITION ? A NEW TREND
... After survey on the approaches used in various vocabulary-based sign language recognition systems, we can give an opinion about the methodologies and algorithms involved. Man times, a combination of different ...
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Bounded solutions for fuzzy integral equations
... of fuzzy functions ...of fuzzy derivative, which is a generalization of the Hukuhara derivative and the fuzzy integral, which is the same as that proposed by Dubois and Prade [7, ...of fuzzy ...
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Framework for a Genetic-Neuro-Fuzzy Inferential System for Diagnosis of Diabetes Mellitus
... This section presents design of the system’s architecture and procedures performed by each component of the architecture during diagnosis. Components of the architecture are presented in the database, ...
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Knowledge Extraction in Fuzzy Relational Systems Based on Genetic and Neural Approach
... for fuzzy relation matrix identification is accomplished in two ...the fuzzy knowledge base and elements of the relational matrix are defined using the genetic ...
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Data mining using intelligent systems : an optimized weighted fuzzy decision tree approach
... hybrid systems can be introduced to both train the neural networks and represent knowledge which is interpretable to ...when neural networks are combined with fuzzy logic, the extracted rules ...
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Improving the Performance of Electronic Systems Using Matlab As A Simulation Tool
... A very important feature of MATLAB is a collection of increasingly Add-On – Application specific solutions referred to as Tool Boxes. These are comprehensive collections of MATLAB functions referred to as M.-files. ...
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