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With rapidly analysis, no pollution, no damage, simple operation, low analysis cost, environmental protection and many other advantages, the near infrared spectroscopy (NIR) analysis has made breakthrough progress in the Chinese medicine field. In this paper, the near infrared spectrometry of extract of two kinds of astragalus is determined. Wavelet transform is used to compress the spectral variables,...
Research community has recently put more attention to the Extreme Learning Machines (ELMs) algorithm in Neural Network (NN) area. The ELMs are much faster than the traditional gradient-descent-based learning algorithms due to its analytical determination of output weights with the random choice of input weights and hidden layer bias. However, since the input weights and bias are randomly assigned...
In this study, we conduct agent-based simulation experiments of network formation focusing on a mathematical model proposed by Berninghaus et al. (2007) such that a periphery sponsored star network is the strict Nash equilibrium. Hayashida et al. (2011) conducted the simulation experiment using NN(Neural Network) and GA(Genetic Algorithm) model to analyze behavior of human subject in the experiment...
Micro-blog is easily posted and communicated because of its short text length. Meanwhile, its brevity limits the feature expression. This paper presents a blogger modeling method for Chinese micro-blog sentiment classification. The paper would adopt a multidimensional strategy to accomplish the feature extraction task. Compared with traditional feature extraction methods and combined with the interactive...
Nonstandard treatments for cancer patients are commonly seen in hospitals of developing countries like China. So it is crucial to standardize the treatments for cancer with technological means in order to supervise the process of treatments. Widespread of electronic health records (EHRs) has generated massive data sets which are far beyond the capability of traditional computing model. Although there...
The paper describes a new method of combining Artificial Neural Networks (ANN), technical analysis and fractal analysis for predicting share prices on the Warsaw Stock Exchange. The proposed hybrid model consists of two consecutive modules. In the first step share prices are preprocessed and calculated into moving averages and oscillators. Then, in the next step, they are given to the ANN inputs,...
Printed Circuit Board (PCB) traces are one of most important PCB Radiated Emissions (RE) sources. These traces is becoming electrically long as the trace length is comparable with the wavelength resulting in higher RE. Therefore, it is essential to predict the RE to avoid out of compliance test issues. In this paper, a neural network Multi-Layer Percetron (MLP) model is developed to predict the radiated...
A bug in a software application may be a requirement bug, development bug, testing bug or security bug, etc. To prediet the bug numbers accurately is a challenging task. Advance knowledge about bug numbers will help the software managers to take decision on resource allocation and effort investments. The developers will be aware of the number of bugs in advance and can take effective steps to reduce...
The global trend of population aging and the continuing maturity of the Internet of Things (IoT) technology drives the rapid development of health care. In the comprehensive applications of IoT technology, developing and constructing a prediction model for chronic diseases is a great improvement to healthcare technology as well as an exploration of IoT technology on the data-analysis and decision-making...
The modeling and simulation of bicycle conflict avoidance behaviors with other vehicles (motor-car\other bicycles\pedestrians) and the obstacle (safety island, fence etc.) at non-signalized intersections is of great importance in junction analysis. However, it is very difficult to simulate the conflict avoidance behaviors of individual bicycle because of the great variations in the cycling behaviors,...
In order to provide a scientific basis for the resource allocation in the stage of checked baggage, improve the service efficiency of airport passenger terminal. According to the flight data of an international airport passenger terminal in 2012 May, this paper establish the BP artificial neural network and multiple regression prediction models respectively, in which the influencing factors are decided...
Modern technologies such as DNA microarray have been developed to study the transcriptome of cancer cells. It has been used in many studies for tumor classification and of identification of marker genes associated with cancer. However, this technique often suffers the ‘curse of dimensionality’. A general approach to overcome this setback is to perform feature selection technique prior to classification...
Few studies of breast cancer surgery outcomes have used longitudinal data for more than five years. To validate the use of artificial neural network (ANN) models in predicting 5-year mortality for breast cancer surgery patients and to compare predictive accuracy between an ANN model and a multiple logistic regression (MLR) model. This study compared the performance of ANN and MLR models based on retrospective...
Accurate short term load forecasting is essential for reliable operation and several decision making processes of the power system. However, forecast model selection, network training issues and improper input selection of forecast model may significantly decrease the prediction accuracy of forecast model. As a result operational cost and reliability of system affected dramatically. In this paper,...
A new technique for analysis of nonlinear effects in smart antenna array transmitter systems is presented. The analysis is founded on a new type of dual-input circuit behavioral model which allows nonlinear effects caused by antenna mutual-coupling and mismatch to be predicted under realistic wideband signal excitations. The model formulation enables direct interface with multi-port antenna S-parameters...
With the advent of wireless networks, the usage of mobile devices has been rapidly exploded due to their cable-free convenience. The ubiquity and dense population of mobile devices have led several heterogeneous wireless networks to be redundantly deployed as an underlying infrastructure in a given area, allowing mobile users to choose their preferred wireless networks. These co-placed different networks,...
Plug-in hybrid electric vehicles (PHEVs), provide an option to use the stored energy in their batteries to support the electricity grid. The vehicle-to-grid (V2G) mode of PHEVs have been investigated in numerous recent studies from many aspects, while most of them have predicted a 10- to 15-year horizon for V2G to gain a wider acceptance of governments and stakeholders who are interested in changing...
In this paper, an adaptive technique based modeling of the optimal bidding strategies for competitive electricity market is proposed. Here, Artificial Bees Colony (ABC) is an optimization tool, which is used in two phases, the employee bee and the onlooker bee to optimize the bidding parameters. From the optimized parameters the exact solution is predicted by the Cuckoo Search (CS) algorithm, which...
Three models have been suggested for analysis of reliability of a complex repairable system, namely helicopter operating unit using Weibull distribution. The first model utilizes failure data for assessing reliability of the unit. The second model, in addition to the use of failure data, includes eight input variables and one composite system output for its analysis. The third model adds another parameter...
The paper proposes a hybrid model of an artificial neural network (ANN) and Fourier series model based on the least squares method (FLSM) for monthly forecasting of tidal current magnitude and direction. The proposed hybrid model is highly accurate and outperforms either of the ANN or the FLSM applied alone. This study was done using data collected from the Bay of Fundy, NS, Canada, in 2008.
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