hybrid neural network systems
Hybrid Neural Network Architecture for On Line Learning
... varying systems are: Aircraft during flight since the configurations of control surfaces as well as flight conditions and the weight of the aircraft are continually changing; the human vocal tract, as the shape of ...
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A Hybrid Recurrent Neural Network For Music Transcription
... (AMT) systems to improve their performance. We use recurrent neural net- works (RNNs) and their variants as music language models (MLMs) and present a generative architecture for combining these models with ...
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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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A Hybrid Recurrent Neural Network For Music Transcription
... (AMT) systems to improve their performance. We use recurrent neural net- works (RNNs) and their variants as music language models (MLMs) and present a generative architecture for combining these models with ...
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A HYBRID TECHNIQUE FOR FREQUENCY DOMAIN IDENTIFICATION OF SERVO SYSTEM WITH FRICTION FORCE
... a hybrid technique for identifying the servo systems with frictional ...the neural network and GA, which is a popular evolutionary ...servo systems with frictional ...
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Hybrid Power Systems Energy Controller Based on Neural Network and Fuzzy Logic
... reference variable to select from among the four PV pan- els. This training data set covers the different solar radia- tion and temperature conditions that could possibly take place. The training patterns were presented ...
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Implementation of hybrid classification model in distributed systems for network monitoring
... and Neural Networks classification algorithms identify the pitfalls and propose a new hybrid classification algorithm which is reliable, fast, efficient and robust handling large data ...using Neural ...
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Data mining using intelligent systems : an optimized weighted fuzzy decision tree approach
... difficulties, 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 ...
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Static Gesture Recognizer Using Hybrid Neural Network
... forward neural network trained with Hebbian algorithm [6]. The neural network is well suited for real-time systems because of their fast response and computational times which are ...
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Role of Knowledge Engineering in the Development of a Hybrid Knowledge Based Medical Information System for Atrial Fibrillation
... a hybrid knowledge based medical information ...pert systems, neural network, artificial intelligence, hybrid intelligent systems, data mining, decision support systems, ...
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Intelligent Decision Support Systems for Oil Price Forecasting
... of hybrid algorithms for predicting the prices of crude ...and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used ...
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Adaptive and intelligent navigation of autonomous planetary rovers – a survey
... learning-based hybrid algorithms have been trialed for path planning ...layer neural network that does not require adjustment of weights, is combined with reinforcement Q-learning [27] to enable ...
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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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Soft Computing Stock Market Price Prediction for the Nigerian Stock Exchange
... Artificial Neural Network (ANN) and Fuzzy Artificial Neural Network (FANN) hybrid model were used to forecast the next day’s closing ...
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Spam detection using hybrid of artificial neural network and genetic algorithm
... of neural network algorithm has been done to save time for parameter selection and to optimize network training in order to increase the performance of spam detection, and to evaluate the performance ...
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Online Full Text
... After developing the two different baseline models, we find that the decision tree model provides better performances than ANN. This implies that DT is likely to extract more noisy data or outliers than ANN for the ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... of neural networks become ap- parent only for large-scale problems, which are computationally intensive and not feasible for hand ...MATLAB, neural network al- gorithms can be quickly implemented, ...
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The Task Scheduling Problem: A NeuroGenetic Approach
... a neural network approach for solving combinatorial optimization ...Tank’s neural network approach to solve small job-shop scheduling ...augmented neural network (AugNN) approach ...
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A SYSTEMATIC REVIEW OF MOBILE BASED ASSESSMENT ACCEPTANCE STUDIES FROM 2009 TO 2019
... two systems, namely the Fuzzy Expert System (FES) and Neuro Fuzzy System ...Both systems are used to diagnose the potential risk of high blood ...both systems have been compared to identify which ...
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A Hybrid Neural Network Model for Commonsense Reasoning
... The second category of models are semantic similarity models. Wang et al. (2019); Opitz and Frank (2018) formulated WSC and PDP as a se- mantic matching problem, and proposed to use two variations of the Deep Structured ...
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