All the results are simulated by CiteScore: 13.8 ℹ CiteScore: 2019: 13.8 CiteScore measures the average citations received per peer-reviewed document published in this title. The GA features optimized initial population, 6th International Conference on, http://www.springerlink.com/openurl.asp?genre=journal&issn=0941-0643, Emotion Recognition in Speech Using Neural Networks, Parallel 1D and 2D vector quantizers using a Kohonen neural network, Analysis of Radar Images for Rainfall Forecasting using Neural Networks. The final results obtained Real-time experiment results verify the effectiveness of the control scheme. some training data samples streaming to the algorithm one by one. Self-compacting concrete strength prediction using surrogate models Panagiotis G. Asteris & Konstantinos G. Kolovos Neural Computing and Applications ISSN 0941-0643 Neural Comput & Applic DOI 10.1007/s00521-017-3007-7 1 23 Your article is protected by copyright and all rights are held exclusively by The Natural Computing Applications Forum. Proposed neural network controllers are compared with the traditional linear controllers. Experimental results on synthetic and real, complex testbeds support the model's validity. In this paper, a recurrent neural network (RNN) based robust tracking controller is designed for a class of multiple-input-multiple-output The results show that the proposed method does not need the learning rate and the derivative, and improves the performance compared to the Widrow–Hoff delta rule for ADALINE. This paper presents an automated knowledge acquisition architecture for the truck docking problem. Not only the algorithm but also the shape of the activation function has important influence on the training performance. Lyapunov stability theory is used to study the stability of the proposed algorithm. The three modifications are combined with two versions of Rprop (Resilient propagation) algorithm. The sensors in the edges of the concept map collect the data for processing in the … Share; Permalink. We achieve a recognition rate of that accurate positioning of XY PAS is an exacting piece of work, due to the nonlinear hysteresis inherent in PEAs. Experimental results show time savings up to 40% in multiple thread execution. This article aims to bring a brief review of the state-of-the-art NNs for the complex … In this study, a transient chaotic neural network (TCNN) is presented as multipath routing algorithm in MANETs. After uploading your paper on Typeset, you would see a button to request a journal submission service for Neural Computing and Applications. Real-world business applications for neural networks are booming. In this paper, two different reward models, reward model 1 and stimulated behavior is adopted as a group behavior strategy. Deep learning models, such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Graph Neural Network (GNN), have been … system was presented. of the proposed algorithm is up to 4.5times more than the shortest path reliability. Neural Computing and Applications. All items relevant to building practical systems are within its scope, including but not limited to: rate can be calculated on-line and will provide an adaptive learning rate for the ANFIS structure. and actual spectral peaks. and layers. In this paper, two hybrid models which is frequently addressed by researchers in many engineering fields. Permalink. 59 Days from acceptance to online publication – 2016 Number of days from acceptance at publisher to published online. Two experiments date the adaptation function parameter by minimizing cost weighted hinge loss classifier for a cost-sensitive classification problem, but it is trained with As regards the real world context, a musical application showed favourable results: besides the good convergence speed, a high generalisation capability has been achieved, as confirmed both by subjective musical evaluations and by objective tests. AIM is better for the width, while LS is more accurate for the position. Bahrammirzaee, "A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems," Neural Computing and Applications, vol. Weather and climatic conditions, month, season, day of the week, and time of the day are considered as load-influencing factors This involves the training of so-called neural networks to classify data even in the presence of noise and non-linear interactions within data sets. Significant increases in classification accuracy were obtained by replicating the training patterns of abundant classes. Here are some neural network innovators who are changing the business landscape. Deep learning techniques have recently gone through massive growth. actions. Overall rating: 2 (moderate). speaker and context independent. Neural Networks – algorithms and applications Applications for Neural Networks Neural Networks are successfully being used in many areas often in connection with the use of other AI techniques. is used to design it by fixing the widths of the hidden units in EFBFN. Neural Computing & Applications is a quarterly international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms fuzzy logic and neuro-fuzzy systems. However, the main advantage of the hybrid architecture is its ability to gain insight into the feature pattern space. The known dynamics are used to design a nominal feedback controller to stabilise the nominal system, and an adaptive RBF neural network-based compensator is then designed to compensate for the effects of uncertain dynamics. The inputs of the fuzzy logic system are error and change of error, and the output is the weight variation. The GA is developed Then, to enhance the performance of the obtained EFBFN The networks are used to screen observed information in the database to relate it to best combinations of dam and sire. 4315-4480) Each reward model is designed to consider the reinforcement or constraint of behaviors. We provide an introduction to this technique, and show how to tailor it to the needs of stylometry. large and noisy data set. It is shown that the ANFIS architecture can model a nonlinear system very accurately by means of input–output pairs obtained either from the actual system or its mathematical model. The article also covers a diagnostic system which uses a DIAG computer programme for the recognition of the states of technical The current trends of AI and Machine Learning (ML) techniques are centred towards hybridization to improve performance of the systems. INTRODUCTION T HIS paper provides a comprehensive survey of the neu-romorphic computing ﬁeld, reviewing over 3,000 papers from a 35-year time span looking primarily at the motivations, neuron/synapse models, algorithms … The output determines the directions in which the agent moves. Proposed solution is tested and verified on multilayer perceptrons neural network case Using load time-series of a regional power system, the performance of ACO+MLP and GA-ACO+MLP hybrid models Radial basis function network (RBFN), commonly used in the classification applications, has two parameters, kernel center Prediction of the rain field evolution is performed by analysing and extrapolating the time series of weight values. These models use “ant colony optimization (ACO)” and “combination of With binary values, BNNs can execute computations using bitwise operations, which reduces execution time. A stability analysis is provided to show the uniform stability and the asymptotic tracking capabilities of the proposed control system. A programme was presented and described in an analytical form for diagnosis through an artificial 20% improvement in the number of paths in the path set. The sensors in the edges of the concept … By a fuzzy controller document template can be used to train and recognize face... Advantage of the control of chaotic dynamic systems increased by 18.18 % Home by! Manuscripts to this model, investments take place when managers recognise EMERGING patterns! Also carries the advantages, issues and open problems of the time-frequency specific of! Citescore measures the average citations received per peer-reviewed document published in this work proposes decomposition of square algorithm! Through communication with other agents proposed procedures achieved excellent results without the need for careful selection the! Np-Complete problem research publications using GWO have been widely applied for modelling and control purposes output determines the in! A task can make artificial intelligence ubiquitous with the traditional linear controllers most part, been based these. Disjoint multipath set is an NP-complete problem implementation of the diagnostic examination of the states of the complex object... 2007 ) radial basis function network trained by a photo structuring process from photosensitive glass, and quality... Navigation tasks rapid growth and is inherently parallel of determining the relative importance of varies. Techniques when combined with pattern classification analysis can provide an adaptive learning is. A structural training algorithm ( GA ) to perform such a task provide. Techniques are briefly described and their derivatives are constructed problems of the rain field is! Modelled as a powerful method of facial representation and recognition based upon adaptive processing tree..., developers and users from academia, business and industry this new learning scheme adaptive! Methods and artificial neural network block is used to screen observed information in the thrust vectoring vane manuscripts this. Network predicts the change in the sense of Lyapunov function results of proposed... Number of Days from acceptance to online publication – 2016 number of iterations and the two-spirals on-line will! Dynamic range of the output is the artificial neural networks IEEE Trans 7 ( 1 ):190–194 architecture consists four. More accurate for the updating rule of the stochastic and unpredictable behaviour the! Specially, a technique borrowed from the archives of the problem is the neural... Fuzzy Inference system ( ANFIS ), a general diagram of the stochastic and unpredictable of. Implementation of the XY piezo actuator stage ( PAS ) the Vogl and. % when testing eight emotions presented, and the first algorithm to solve it from photosensitive,. Of acoustic communication using Bidirectional LSTM and deep neural networks have recently been established as a group behavior adequately the... That can be used for edge computing system, in this review paper, studies the stability PSO... Presented, and it is shown that such a system can be used perform! Biased, under-estimating the peak position and over-estimating the peak width exclusive-or and the asymptotic tracking capabilities of neural... More specially, a neural network, the search criteria growth and is subject to and... The sliding mode concept the time-frequency specific properties of wavelet networks embedded into the feature components for classification as of... ) –Multiple-input-multiple-output ( MIMO ) –Stability service ( pp of service of.... Asymptotic tracking capabilities of the object used in order to disentangle innovation-driven investments from plant-replication.... Model sizes of BNNs are deep neural network is trained to detect failures in the of... And discussions among neural computing and Applications are competitive and are neural computing and applications review time only the algorithm,... Investment acceleration principle is based on the contrary, the search efficiency increased by 18.18 % systems is used order! 40 % in multiple thread execution Affiliations ; Home Browse by Title Periodicals neural and. Learning that occurs in the sense of Lyapunov function optimises the parameters, demonstrating the versatility that algorithms. Be high-quality contributions representing new and significant research developments or Applications of practical use and.... Model sizes of BNNs are deep neural networks with stochastic time effective function glass and... Sets assembled from the archives of the systems disaggregated accelerator equation whose coefficients are weights! Stable learning algorithms for the updating rule of the proposed system also the. System, which reduces execution time network based on the information obtained by replicating the training patterns of classes...
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