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Considering that the neural network increases rapidly in complexity and is greatly extended in training time due to the gradually increasing input vectors, a fusion algorithm modified by rough set is proposed to preprocess the inputs before neural network. Firstly, the input sample space is reduced to obtain the new decision table according to attribute significance in rough set. Then the reduced...
The structure, function and core part of the mine wind pressure monitoring and alarming system based on BP was introduced in this paper. This system runs stably and reliably, and plays an important role in the safety of coal mining.
The identification of temperature filed of monitored region is one of the key steps for the energy efficiency management in intelligent building. In this paper, the identification of temperature field in monitored region is formalized as one optimization problem. With the formalization, a feed forward neural network is used to identify the temperature field of monitored region in an intelligent building...
Predictions on elevation changes of the Xin River Cable-stayed Bridge were made using the BP neural network algorithm, which is the nonlinear relationship between the input parameters and output parameter. The analysis used the factors which affect the girder segment elevation changes as input samples and which measured the elevation changes as output samples in the training of the BP neural network...
In order to overcome the disadvantages such as low calculation precision and convergence rate of traditional BP neural network algorithm, a kind of nonlinear optimization method-BFGS method for unconstrained extreme problem is introduced into BP neural network algorithm, and a BFGS-BP neural network model is developed, which is applied well in structure deformation monitoring data processing and forecasting...
Deformation that happens in the real world is a nonlinear process, and so are the outliers in deformation observations. With the requirements on automation, real-time and accuracy becoming stronger and stronger, it is also more and more important to fast detect and remove the outliers in monitoring observations. In the paper the approximation of nonlinear function mapping relation using artificial...
With the study and analysis on intelligent fault diagnosis for inverting circuit, an improved diagnosis method combined BP neuron network and D-S evidence theory was proposed. Each measuring point was extracted by BP neural network to obtain the local diagnosis, which is adopted to design the belief function of D-S evidence theory. Multiple monitoring points' information is fused to receive the comprehensive...
By the comprehensive use of DSP technique and BP Neural Network, the system realizes the automatic monitoring to the black smoke pollution and the classification to Ringelmann black degree. Along with the radical avoidance of the measure error caused by subjective factors, it avoids the out-dated status of subjective evaluating. With the use of time and space domain combined background brightness...
Based on the study of the theory and constituent of the electronic nose systems, a set of combined gas sensor array, microcontroller and PC for detection of gas mixture is designed and constructed. Four kinds of gas (hydrogen, methane, acetylene, propane) are tested by the system. The feature parameters are picked up from each curve of the gas sensor's reaction. The experimental samples are analyzed...
A intelligent monitor and control system on multi-factor of aquaculture environment based on wireless sensor networks is designed adopting BP neural networks. The system uses wireless sensor nodes to detect a variety of water quality parameters transmitted to the on-site monitoring host computer through sink node wirelessly. The control module consists of fuzzy controller and decoupling neural network...
Driver's distraction in driving is one of the major causes of the traffic accidents. The abnormal behavior of the driver's head movement and the facial expressions were studied in detail in order to get the characteristics of the inattention status. With real-time monitoring on the driver's attention characteristics: the position and movement status information of eyes and mouth, the detection mechanisms...
Based on the analysis of condensate and feed water system, a fault knowledge repository is established considering operation experience. The D-S inference of Information Fusion theory has the ability of dealing with uncertain information and Artificial Neural Network (ANN) has the advantage of high tolerance and robust. In this paper, a model for fault diagnosis utilizing D-S theory of evidence together...
Recently, there are many problems in software laboratory course management. It is, particularly, widespread that student play video games or do other things which are unrelated to the course. However, most of present monitoring software are all based on the operation of teachers, rather than a real-time system, which is very inconvenient. In order to carry out the laboratory course management better...
On the basis of traditional BP neural network model, a series of optimization methods are used to improve application capability and range in the water quality assessment, which can help diagnosis of River Basin Water Environment. The improved models are applied to evaluate water quality of Moshui river china, from 2001 to 2007, and relative conclusions are obtained.
Water quality model is a useful tool to evaluate the future state of river water through evaluation of actual pollution loading or different management options. Based on the human brain physiology research, artificial neural network(ANN), which simulates the structure and mechanism of the human brain, is a kind of dynamic information processing system that eventually achieves certain functions of...
Security management is a urgent problem to solve for underground engineering because of nonlinear characteristics of rock mass. The method of combining data mining and monitoring information is proposed to manage the deformation of surrounding rock. Information recognition model of surrounding rock is established by using the BP neural network which has self-learning ability in the data mining technology,...
Intrusion detection is the process of identifying and responding to suspicious activities targeted at computing and communication resources, and it has become the mainstream of information assurance as the dramatic increase in the number of attacks. Intrusion detection system (IDS) monitors and collects data from a target system that should be protected, processes and correlates the gathered information,...
To guarantee the grain’s safe storage, it’s necessary to strictly control the stored-grain’s internal and external influence factors such as temperature, moisture, humidity and pests. The application of information fusion techniques on monitoring and controlling system of stored-grain condition is a useful consideration. In this paper, a new method based on multi-parameter and two stage information...
In popular outlier processing methods, some emphasize on spotted outliers processing and some emphasize on isolated outliers processing. They have seldom processed outliers from the perspective of outlier producing mechanism. This paper aims at the problem of outliers in dam safety monitoring and an outlier identify method which based on BP neural network is presented. This method based on the mechanism...
According to the characteristics of broad frequency and abundant spectral components of mine microseismic signal, we use AR model parameters and BP neural network to propose a method of filtering treatment for the signal and noise with different frequency ranges. We can use this method to separate noise and signal, and decompose different frequency band signals, so we can achieve the goal of filtering...
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