The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, the characteristics of the excitations and the vibration responses of cylinder head are analyzed in detail. The methods of reconstructing cylinder pressures are investigated. To avoid some shortcomings of traditional linear methods, a new reconstructing cylinder pressure method by using ANN is presented in this paper. A standard BP neural network was trained with the measured cylinder...
This paper will use fuzzy integral to structure the diagnostic model of gestational diabetes mellitus. The Sugeno measure is obtained by training of BP neural network. The BP neural network is easy to get into local optimum, so the algorithm of simulated annealing is used to optimize the BP neural network, and it will obtain an approximate global optimal solution. In this diagnostic model, there are...
Because of the shortage of the traditional methods for evaluating regional innovation capability, it presents a new method based on rough set and BP neural network in this paper. Firstly, index system for evaluating about regional innovation capability is set up, and then rough set is used to simplify the attributes of the index system, it will ease the burden of training and learning of BP network...
The effective way of improving the efficiency of intrusion detection is to reduce the heavy data process workload. In this paper, the dimensionality reduction use of technology in the classic dimensionality reduction algorithm principal component to analysis large-scale data source for reduced-made features of the original data be retained and improved the efficiency of intrusion detection. And use...
In order to solve the dimensionality curse of BP neural network in pattern recognition, this paper proposes a model of dimensionality reduction which based on rough set theory. While training network, the model first carries out attribute reduction based on rough set theory, and then picks up important characteristics of ideal samples to reduce input space dimensions. Hence the speed of network training...
In order to improve the correct rate, this paper puts forward a method of the vibration fault diagnosis of hydroelectric generating unit by neural network based on particle swarm optimization (PSO). Some fault characteristics through the feature extraction are selected as the inputs of neural network for training, then the fault diagnosis is accomplished via the trained and optimized neural network...
Unemployment is a major problem in China at the present time, it is also a critical factor relative with the development of society. For this reason, predicting unemployment rate as a method of economic and social studies is being paid more and more attention. An accurate predicted outcome is significant for the government to formulate and promulgate the relative policies. In this paper, according...
This paper puts forward a multisensor information fusion method, combining the BP neural network with the D-S evidence theory, which not only gets over the shortcoming of not being real-time caused by unitary neural network that reaches high accuracy at the cost of many times of iteration, but trains the neural network by using large amount of standard samples, so as to make the D-S evidence theorypsilas...
The paper is given a new modified differential evolution (MDE) algorithm in which a novel mutation operator is introduced. The MDE algorithm can obtain a good balance between global search and local search and was applied in BP neural network training. The numerical results demonstrate that the new MDE algorithm has the abilities of good global search and faster convergence speed and higher convergence...
A short-term load forecasting method based on BP neural network which is optimized by particle swarm optimization (PSO) algorithm is presented in this paper. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Here, real load and weather data from the Xingtai power plant databases used as inputs to the neural network, which...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.