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The following topics are dealt with: power electronics; power drives; smart grids; hybrid energy systems; fuel cell; image processing; cloud computing and neural network.
High quality greenhouse control requires accurate modeling of the greenhouse as a thermal system along with all the influences affecting it. A decomposed model is the only way to tackle the complexity of such a system. A very important module of the decomposition is the heating system, due to its high impact on the overall financial cost of the greenhouse. This paper inspects the theoretical limits...
A novel Neural Network Based Fuzzy Inference System for financial default forecast will be introduced. A wide range of financial forecasts is known. This method is focusing on the economical default forecast, but the method can be used generally for other financial forecasts as well, for example for calculating the Value at Risk. This hybrid method is combined by two classical methods: the artificial...
The following topics are dealt with: user behavior; intention aware computing; Internet LAN based RFID; intrusion detection system; document analysis; Web service; search engine; machine learning; neural network; collaborative communication; virtualized server; collaborative learning; video summary; computer simulation; fingerprint image matching; data analysis; Bayesian network; text visualization;...
Recently, various types of robots have been researched and developed for supporting our life. Also, the perceptual system for the robot is researched. Visual perception includes a lot of valuable information and it is useful for all intelligent robot system. In this paper, we discuss intelligent robot vision in order to active sensing and information structuring for human-robot collaboration system...
Field-programmable gate arrays (FPGAs) can provide an efficient programmable resource for implementing hardware-based spiking neural networks (SNN). In this paper we present a hardware-software design that makes it possible to simulate large-scale (2 million neurons) biologically plausible SNNs on an FPGA-based system. We have chosen three SNN models from the various models available in the literature,...
In order to study the impact of drivers' distance cognition difference on traffic safety in dynamic environment of daytime and night-time, a real road tests was carried out by asking 19 drivers randomly selected to percept the distances of obstacles with different distances and velocities on daytime and nighttime. The values of cognition are obtained by statistical methods. The distance cognition...
Artificial neural network is an important research direction in data mining. It is used to solve classification and regression problems, and can find out the nonlinear relation between the input attribute and the output attribute, especially the smooth and continuous nonlinear relations. Use the Microsoft neural network to find out how the meteorological factors influence the precipitation, and to...
The paper studies the application of principal component analysis and ANN (Artificial Neural Networks) for pre-warning of enterprise financial crisis, analyzes the factors of financial crisis, and constructs the model of the enterprise financial crisis with principal component analysis and ANN. It integrates simplifying of enterprise financial crisis index, dynamic learning of financial crisis knowledge...
This paper takes commercial bank as the object of study, conducts the research on its logistics finance service pattern's risk evaluation. First, the paper analyses the principal patterns of commercial bank logistics finance services, unifies the characters of each kind of logistics finance service pattern, constructs risk evaluation index of commercial bank logistics finance under different patterns...
Anti-windup saturation compensation schemes in two-link flexible arms are studied. The singular perturbation approach is used to decompose the nonlinear system into a rigid subsystem and a fast subsystem, which allows a composite control design for the original system. A neural network is designed to compensate the saturation nonlinear in rigid subsystem, and a robust controller is employed to attenuate...
In this paper, based on investigating and analyzing on the affecting factors for support type of development roadways as well as the successful support cases in Chengchao Iron mine, the improved BP neural network is put forward to study on the support type of development roadways. It may be seen from the learning course of learning samples and the prediction results of support types that whether the...
For vary interval data serial, the data serial is interpolaed by Chaos-dynamic neural network method. combining the chaotic feature of data serial, the method of Wavelet denoising of data serial is improved, and the noise is effectively filtered, while the variation trend and data character of initial data can well be retained, and real signal (abnormal value) can be reserved. So these treatment methods...
It has been 50 years since the idea popped up that calculating systems can be made on the replica of the biological neural networks. Still, the development of this science branch made the improvement of these systems possible only in the last 25-30 years. Nowadays, neural computing is a very extensive, separate science. Its solid theory basis made it possible to use them to solve many kind of problems...
DDoS attack is a major Internet security problem-DoS is that lots of clients simultaneously send service requests to certain server on the internet such that this server is too busy to provide normal services for others. Attackers using legitimate packets and often changing package information, so that traditional detection methods based on feature descriptions is difficult to detect it. This paper...
This thesis introduces the forecasting methods of domestic and foreign road traffic flow, analyzes the advantages and shortcomings of all sorts of traffic flow forecasting methods and the actual forecasting effects. For the complexity of the urban traffic, the precision of some current traffic flow forecasting methods is not high. With respect to these questions, this thesis applies the chaotic neural...
Evaluating road safety is essential in identifying the potential road safety hazard which could result in casualties and property losses. in this paper, a BP neural network was built by using neural network toolkit in "Matlab", Two similar roadways are used in calibrating and validating the network. The high level of predictability provided that the application of BP neural network model...
It is very important to forecast the ice thickness of Transmission Line for the safe operation of transmission network. The author had introduced artificial neural network(ANN) to the prediction of the ice thickness of transmission line, and proposed a predictive model based on GA and BP addresses on the defects of BP network includes slow convergence and easiness of running to local minimum, and...
In the process of producing copper bar, because of the cast copper billet, rolling equipment, rolling process and other reasons, the surface of copper bar appear some defects such as crack, scarring, roller printing, scratches, holes, scales, pitting, and so on. These deficiencies not only affect the appearance of the product, but more importantly reduce the product's corrosion resistance, abrasion...
In order to investigate control method for indoor thermal comfort, the experimental environment of indoor thermal comfort is designed in this paper. Thermal comfort data are collected based on questionnaire means, ANN (artifical neural network) is trained using the data, and the ANN model trained can accurately forecast thermal comfort index. Relevant input parameters is conversely computed based...
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