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.
Aiming at the BP artificial neural network unable to auto select and optimize input variables, this paper integrates BPANN with grey relational analysis method, establishes an optimized BP artificial neural network arithmetic (GM2BPANN) which based on the grey relational analysis method. The hybrid approach has been used to forecasting the online item price. The result shows that the new model can...
Due to the inherent limitations of structure and dimensional, it is difficult to measure the surface roughness of micro-heterogeneous surface in deep hole. In this paper, the microscopic image of micro-heterogeneous surface is obtained by the long working distance lenses of digital microscopic camera, firstly. Thereafter, two artificial neural network models, which take microscopic image features...
This study develops and implements a SoC-based HW/SW (Hardware-Software) codesign for an intelligent diagnostic system. To improve the efficiency of the VLSI (Very Large Scale Integration) design process, the components of the intelligent diagnostic system are designed in the form of SIP (Silicon Intellectual Property) modules. The SIP modules, including the CPU module, the GPIO (General Purpose I/O)...
P2P traffic has become one of the most significant portions of the network traffic. How to improve the accuracy of the traffic identification efficiently is still a difficult problem. A promising approach that has recently received some attention is traffic classification using machine learning techniques. In this paper, we propose a BP neural network algorithm for P2P traffic classification problem...
A new inductive transfer-learning algorithm called NEDRT is presented in this paper in order to improve the classification accuracy of a domain task by using the knowledge learned from labeled data generated from a different domain. NEDRT introduces a novel error function for a constructed neural network by summing a weighted squared difference between the real output and the neural network output...
Considering the chaotic characteristic of power system load, a method based on bee evolution modifying particle swarm optimization (BEMPSO) and chaotic neural network is presented for power system load forecasting to improve precision. In this paper, builds the chaotic neural network model and integrates bee evolution modifying with particle swarm optimization. The novel BEMPSO algorithm is proposed...
As a representative method of swarm intelligence particle swarm optimization (PSO) is an algorithm for search the multidimensional complex space through cooperation and competition among the individuals in a population of particles. A novel modified particle swarm optimization (MPSO) algorithm is proposed. The MPSO is determined by linearly decreasing inertia weight and constriction factor weight...
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.