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In this paper, mathematical model for heat treatment is constructed according to the process requirement of Roller-hearth Normalizing Furnace. Based on the intelligent control theory of neural network and particle swarm algorithms, the improved PSO-ANN model is established and simulated using lots of data acquired from the site. The result indicates the improved PSO-ANN model can raise the precision...
By introducing status and progress of data mining and analyzing characteristics of medical data, a mathematical model of clinical medicine data mining is designed using data preprocessing, artificial neural network and manifold learning, focusing on data mining of clinical biochemical examining results for high-risk population with cancer and cardiovascular disease, and taking model output whose input...
Network security situation perception is to predict the probability of attacks, may occur in the future, by a variety of predicting methods, by recent network attacking data obtained from IDS (Intrusion Detection System). Neural Network model has many features, high degree of fault tolerance, associability, self-organizing and self-learning ability, and strong nonlinear mapping and generalization...
This paper provides a neural network model to address the problem of travel time prediction. A single segment model based on the state space neural network is used for modeling traffic flow on one single signalized segment. Thus, modelling a longer arterial covering several controlled intersections is conducted by assembling each individual segment models. This reduces significantly the amount of...
This paper is aimed at applying BP neural network and Dempster-Shafer (D-S) evidence theory to realize the real-time monitoring and the fault diagnosis by taking power transformer as the object of fault diagnosis. We make use of the neural network's ability of better fault tolerance, strong generalization capability, characteristics of self-organization, self-learning, and self-adaptation, and take...
In this paper, we expand previous work and present an accurate electricity load forecasting algorithm with back propagation neural networks. It contributes to short-term electricity load forecast methodology with neural network with weather feature such as max centigrade, min centigrade and weather types. The original electricity load is from shanghai district, which is composed of original every...
Two-dimensional principal component analysis technique is an important and well-developed area of image recognition and to date this method has been put forward. A new face recognition method two-dimensional principal component analysis (2DPCA) based on BP neural networks, named 2DPCA-BP method, was proposed. 2DPCA was used to obtain a family of projected feature vectors, in which face image was projected...
ldquoEnergy-faultrdquo method is introduced for faults warning of ventilators, which is based on wavelet package analysis and BP neural network. Character vectors which reflect different faults state of ventilators are extracted from different frequency segments with the technology of wavelet package analysis, and taking them into BP neural network model which is trained with character vectors of...
Nozzle plays very important role to control the gas flow during the interruption for SF6 circuit breaker (CB). Due to the higher non-linear global mapping relationship between interruption performance of SF6 CB and its nozzle structural parameters, artificial neural network (ANN) and genetic algorithm (GA) were applied to the nozzle parameter optimization of SF6 CB on the basis of the non-linear mapping...
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