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With the development of the Rough Sets and Neural Network, dynamic prediction research on financial crisis has become as a developing trend. Based on this situation, this paper makes use of the Rough Sets' attribute reduction technique to reduce the financial index firstly, then imposes the Neural Network to train network so as to establish financial crisis alarming model to drop out enterprise's...
Comprehensive assessment of sustainable utilization of regional water resources, including three subsystems: social economy, water resources and eco-environment, is a large complicated and systematic evaluating problem. The selection of the index system for the regional sustainable development of water resources was discussed herein. Furthermore, a neural network methodology for regional water resources...
Short-term traffic flow forecast is an important topic in the research field of intelligent transportation systems. The article analyses the preliminary results in the short-term traffic flow forecast, takes full advantage of the characteristics of grid technology, and builds a model based on chaos theory and neural network. It uses grid resource management mechanisms and migration strategies to solve...
The pre-diagnosis to type 2 diabetes, and the effective prophylaxis and treatment of its complication is to be worthy paying attention to. So an intelligent diagnosis based on quantum particle swarm optimization (QPSO) algorithm and weighted least squares support vector machines (WLS-SVM) is presented, which can overcome the disadvantage of large sample data, slow model-building and rather large deviation...
Effective prediction on the states of moving objects paves the way for successful motion planning. In this paper, particle filter is used to predict the robot position and velocity and the experimental results of target prediction in robot path planning are presented to verify its performance. Particle filter can also be combined with the system overall strategies to plan its motion and improve the...
This paper presents output feedback neural control for helicopters in single-channel modes of operation with dynamics in single-input single-output (SISO) nonlinear nonaffine form. A constructive approach for adaptive NN control design with guaranteed stability is proposed based on the use of the Implicit Function Theorem, Mean Value Theorem, and high gain observer. It is shown that the output tracking...
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