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RETRACTED ARTICLE: Human---computer interaction using vision-based hand gesture recognition systems: a survey

Considerable effort has been put toward the development of intelligent and natural interfaces between users and computer systems. In line with this endeavor, several modes of information (e.g., visual, audio, and pen) that are used either individually ...

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Swarm robots reinforcement learning convergence accuracy-based learning classifier systems with gradient descent (XCS-GD)

This paper presented a novel approach accuracy-based learning classifier system with gradient descent (XCS-GD) to research on swarm robots reinforcement learning convergence. XCS-GD combines covering operator and genetic algorithm. XCS-GD is responsible ...

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A linear hybrid methodology for improving accuracy of time series forecasting

Modeling and forecasting of time series data are integral parts of many scientific and engineering applications. Increasing precision of the performed forecasts is highly desirable but a difficult task, facing a number of mathematical as well as ...

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Short-term wind power prediction using differential EMD and relevance vector machine

As a renewable energy source, wind turbine generators are considered to be important generation alternatives in electric power systems because of their nonexhaustible nature. With the increase in wind power penetration, wind power forecasting is ...

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Hybrid memristor/RTD structure-based cellular neural networks with applications in image processing

Cellular neural network (CNN) has been acted as a high-speed parallel analog signal processor gradually. However, recently, since the decrease in the size of transistor is going to approach the utmost, the transistor-based integrated circuit technology ...

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Hybrid krill herd algorithm with differential evolution for global numerical optimization

In order to overcome the poor exploitation of the krill herd (KH) algorithm, a hybrid differential evolution KH (DEKH) method has been developed for function optimization. The improvement involves adding a new hybrid differential evolution (HDE) ...

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Adaptive neural control and learning of affine nonlinear systems

This paper presents deterministic learning from adaptive neural network control of affine nonlinear systems with completely unknown system dynamics. Thanks to the learning capability of radial basis function, neural network (NN), stable adaptive NN ...

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The effectiveness of the combined use of VIX and Support Vector Machines on the prediction of S&P 500

The aim of this research is to analyse the effectiveness of the Chicago Board Options Exchange Market Volatility Index (VIX) when used with Support Vector Machines (SVMs) in order to forecast the weekly change in the S&P 500 index. The data provided ...

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Adaptive subspace learning: an iterative approach for document clustering

The performance of clustering in document space can be influenced by the high dimension of the vectors, because there exists a great deal of redundant information in the high-dimensional vectors, which may make the similarity between vectors inaccurate. ...

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Game-theoretic approach to cooperative control of distributed energy resources in islanded microgrid considering voltage and frequency stability

A microgrid (MG) comprises a low-voltage network with several microsources, critical and noncritical loads, and energy storage systems (ESSs). It can operate in the grid-connected or islanded modes. In islanded mode, the voltage and frequency of the MG ...

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Point-of-care diagnosis of bacterial pathogens in vitro, utilising an electronic nose and wavelet neural networks

Current clinical diagnostics are based on biochemical, immunological or microbiological methods. However, these methods are operator dependent, time-consuming and expensive and require special skills, and are therefore not suitable for point-of-care ...

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A fuzzy system approach to multilateral automated negotiation in B2C e-commerce

Software agents in e-commerce systems are assigned to the participants. Buyer and supplier agents into multi-agent system architecture of the e-commerce system negotiate with others through an automated negotiation mechanism. In this study, an automated ...

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An optimized authentication protocol for mobile networks

Practical secure communication of mobile systems with low communication cost has become one of the major research directions. An established public key infrastructure (PKI) provides key management and key distribution mechanisms, which can lead to ...

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A new gear fault feature extraction method based on hybrid time---frequency analysis

Gear is one of the popular and important components in the rotary machinery transmission. Vibration monitoring is the common way to take gear feature extraction and fault diagnosis. The gear vibration signal collected in the running time often reflects ...

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Memristor crossbar-based unsupervised image learning

This letter presents a new memristor crossbar array system and demonstrates its applications in image learning. The controlled pulse and image overlay technique are introduced for the programming of memristor crossbars and promising a better performance ...

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Support vector set selection using pulse-coupled neural networks

A candidate set of support vectors is selected by using pulse-coupled neural networks to reduce computational cost in learning phase for support vector machines (SVMs). The size of the candidate set of support vectors selected this way is smaller than ...

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Applications and analysis of bio-inspired eagle strategy for engineering optimization

All swarm-intelligence-based optimization algorithms use some stochastic components to increase the diversity of solutions during the search process. Such randomization is often represented in terms of random walks. However, it is not yet clear why some ...

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A new Chinese character recognition approach based on the fuzzy clustering analysis

In this paper, a new Chinese character recognition (CCR) approach is proposed based on the fuzzy clustering analysis theory. Chinese characters (CCs) have various similar radicals and stroke components, which make it difficult to recognize features in ...

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Exponential synchronization of stochastic chaotic neural networks with mixed time delays and Markovian switching

This paper studies the exponential synchronization problem for a class of stochastic perturbed chaotic neural networks with both Markovian jump parameters and mixed time delays. The mixed delays consist of discrete and distributed time-varying delays. ...

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Predicting phishing websites based on self-structuring neural network

Internet has become an essential component of our everyday social and financial activities. Nevertheless, internet users may be vulnerable to different types of web threats, which may cause financial damages, identity theft, loss of private information, ...

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Bat algorithm based on simulated annealing and Gaussian perturbations

Bat algorithm (BA) is a new stochastic optimization technique for global optimization. In the paper, we introduce both simulated annealing and Gaussian perturbations into the standard bat algorithm so as to enhance its search performance. As a result, ...

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Transfer learning using the online Fuzzy Min---Max neural network

In this paper, we present an empirical analysis on transfer learning using the Fuzzy Min---Max (FMM) neural network with an online learning strategy. Three transfer learning benchmark data sets, i.e., 20 Newsgroups, WiFi Time, and Botswana, are used ...

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On ranking multiple touch-screen panel suppliers through the CTQ: applied fuzzy techniques for inspection with unavoidable measurement errors

The touch-screen panel (TSP) market has significantly brought up a great deal of business opportunities; in fact, it shows continuous growth in revenue, units, and area. Therefore, the high growth rate of the TSP market forces all the manufactures in ...

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