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Artificial neural network (ANN) was proposed as an effective method to help multipath ultrasonic flowmeter (UFM) reduce its measurement error when determining the flowrate of complex flow field. However, the effectiveness of the ANN method heavily depends on the network architecture specified by the designer, and also the provided initial weights and layer biases. This hinders the ANN to be widely...
Faced with high dimensional and large amount of data, network intrusion detection is always the focus of current research in the network security field. With the advantages of nonlinear, distributed storage and easily computing, Artificial Neural Networks (ANNs) are widely used in machine learning and pattern recognition fields. In this paper, we adopt a feature selection algorithm based on Fisher...
The vehicle routing problem with time windows (VRPTW) is a well-known and complex combinatorial problem, which has received considerable attention in recent years. In this paper, an effective meta-heuristics for VRPTW was designed to minimize the vehicle number and total travel distance. Performances are compared with other heuristics appeared in the literature recently by the bench-mark data sets...
The concept of canopy spectral invariants expresses the observation that simple algebraic combinations of leaf and canopy spectral reflectances become wavelength independent and determine two canopy structure specific variables - the recollision and escape probabilities. The recollision probability (probability that a photon scattered from a phytoelement will interact within the canopy again) is a...
Growing complexity in Grid environment makes bandwidth monitoring and prediction both increasingly difficult and increasingly important. The challenge is to design a low-cost and online prediction system to provide Grid users and developers with detailed bandwidth information. Bandwidth prediction is designed based on Grid Service Infrastructure, it is composed of a series of Grid services including...
Recently, Epsilon-Insensitive Support Vector Regression (epsiv SVR) has been introduced to solve regression and prediction problems. However, the preprocessing of data set and the selection of parameters can become a real computational burden to developer and user. Improper parameters usually lead to prediction performance degradation. In this paper, by introducing Parallel Multidimensional Step Search...
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