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Main factors which make water bloom engendering in river and lakes is analyzed, and the modeling method of short-time predicting for water bloom based on RBF neural network, including supervise learning method for the center, width and weight of base function in RBF neural network, error-correction algorithm based on gradient descent of RBF, is proposed. The effect which hidden layer of RBF brings...
To monitor building equipments, a method of design and realization for distributed measure and control system is proposed, and the configuration of three-level network based on field bus, Ethernet and Internet and their communication techniques are described respectively. The concentrate monitoring and control for building equipments can be realized with B/S model and ADO technique. The data integration...
Analyzing the characters of water-bloom eruption, one effective model on weightings attribute of forecasting water-bloom based on D-S evidence theory has been proposed. After pre-treating forecast index data, sets up water -bloom short-time forecast model based on neural network, which improves forecast precision of water-bloom, through simulation and testing, the result shows its affectivity and...
This paper present a method to acquire a realistic, visually convincing 3D model for indoor environment using a mobile robot platform with two laser range scanners and one omnidirectional camera. First, the vertical mounted laser scanner is used to acquire geometrical 3D model of indoor environment, while the horizontal mounted laser scanner is used to solve the simultaneous localization and mapping...
A new algorithm of data processing and a method of soft sensor based on process neural network (PNN) for time-varying system are represented in the paper. Process neural network is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information...
Process neural network (PNN) is a new type of artificial neural network studied in recent year. PNN is an extent of traditional neural network, in which the inputs and outputs may be time-variation. Some modified algorithms for raising the training speed of PNN were investigated emphatically. These algorithms were based on function orthogonal basis expansion which exist low-speed convergence in network...
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