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.
Based on the analysis of the importance of project termination decision and the review of related research, this paper constructs an R&D project termination decision model based on Kohonen neural network consisting of the principles of a system of evaluation indexes, the quantification of eigenvalues of the evaluating indexes, the basic principle of Kohonen and the establishment and application...
Statistical data shows that a driver who was lack of the ability to discover potential risk situation and safe driving awareness was more probably to cause an accident. The safe driving awareness was considered as a factor in contributing to vehicle crashes. In this study, a creative method to improve safety awareness based on driving simulator was proposed. Firstly, the definition and classification...
A novel neural network, retina neural network (RNN) is put forward, and its definition, network structure, parameters, and characteristic are presented. After training it using a set of samples, an ideal training waveform is obtained, which is a great guide for future research. Moreover, a model of permanent magnet synchronous motor (PMSM) PI controller is constructed based on RNN to test drive performances...
Organizational citizenship behavior is a hot topic in the area of modern human resources management, which focuses on the initiative behaviors beyond the requirements of position duties. OCB can influence organizational performance by increasing the ability of employees, motivating intrinsically, extending resources and creating favorable environments. There are mainly four factors affecting the organizational...
Analyzes the features of international project management talents and modes of their development; summarizes the shortages existing in English teaching for project management majors and explores from the perspective of English teaching the possible ways and means of cultivating international project management talents.
SVM is powerful for the problem with small samples, non linear and high dimension. But such important parameters as the kernel function parameters, the insensitive parameters and the penalty coefficient are determined based on experience and cross-validation in the SVM, so it has certain blindness. In the paper, support vector machine optimized particle algorithm is used to predict the intensity of...
Synthetic aperture radar (SAR) is well adapted to detect ocean pollution independently from daily or weather conditions. Oil slicks have a specific impact on ocean wave spectra because the presence of oil slicks can induce a damping of the backscattering to the sensor and a damping of the energy of wave spectra. Thus oil slicks can be discernible from the radar image. Several algorithms are applied...
A method to determine C,γ , the hyper-parameters, range for Radial Basis Function Support Vector Machines (RBF SVMs) is proposed. The γ range is determined by the extreme Squared Euclidean Distance (SED) quantiles of the training set, and the C range is determined by one pass whole training set training decreasingly along logγmax to the over-regularized limit first and increasingly along logγmedian...
Short-term prediction of intelligent traffic flow is in favor of road unblocked and vehicle waiting strategy. The algorithm of short-term prediction of intelligent traffic flow based on back propagation(BP) neural network and autoregressive integrated moving average (ARIMA) model can solve it partially. Firstly, Establishing a BP neural network sub-model and ARIMA sub-model, Then taking BP neural...
Applications of neural network were widely used in construct project cost estimate. Aim at handling weakness of poor convergence and insufficient forecast, an improved fuzzy neural network method based on SOFM (self-organizing feature map) and GA (genetic algorithm) was proposed to replace the fashionable T-S fuzzy neural network. The method illustrated how to apply SOFM and GA to improve the fault...
Based on the annual report data between 1995 and 2005 of all listed companies (LCs), the 25 initial financial indexes, widely used by experts and researchers aboard and at home, was deduced to 14 effective evaluation indicators using factor analysis and principal component analysis (PCA). The 14 evaluation indicators, covering five aspects for comprehensive evaluation of competitiveness of LC, retain...
In this research, the combination of modal data is used to identify the damage of a FEM model using neural networks. The identification ability with different levels of noise and incomplete mode shapes are also investigated. It has been proved that the neural network using combination of modal parameters as input has a excellent identification ability with ideal error tolerance and robustness. Numberical...
Online handwriting recognition is gaining more and more interest as there is increase of pen computing applications and new pen input devices. The main reason behind this is the easy availability of pen computing devices due to the advances in the technology. The recognition of Devnagari characters is different from western handwriting recognition and poses a special challenge. The objective of this...
One of the important issues in the design of fuzzy classifier is the formation of fuzzy if-then rules and the membership functions. This paper presents a Niched Pareto Genetic Algorithm (NPGA) approach to obtain the optimal rule-set and the membership function. To develop the fuzzy system the rule set and the membership functions are encoded into the chromosome and evolved simultaneously using NPGA...
In this paper we have proposed a new way to achieve the optimum learning rate that can reduce the learning time of the multi layer feed forward neural network. The effect of optimum numbers of inner iterations and numbers of hidden nodes on learning time and recognition rate has been shown. The Principal Component Analysis and Multilayer Feed Forward Neural Network are applied in face recognition...
In recent years, with the rapid proliferation of digital images, the need to search and retrieve the images accurately, efficiently, and conveniently is becoming more acute. Automatic image annotation with image semantic content has attracted increasing attention, as it is the preprocess of annotation based image retrieval which provides users accurate, efficient, and convenient image retrieval with...
Neutralizing pH value of sugar cane juice is the important craft in the control process in the clarifying process of sugar cane juice, which is the important factor to influence output and the quality of white sugar. On the one hand, it is an important content to control the neutralized pH value within a required range, which has the vital significance for acquiring high quality purified juice, reducing...
Multi-label classification is a popular learning task. However, some of the algorithms that learn from multi-label data, can only output a score for each label, so they cannot be readily used in applications that require bipartitions. In addition, several of the recent state-of-the-art multi-label classification algorithms, actually output a score vector primarily and employ one (sometimes simple)...
This paper presents a novel algorithm for multiobjective training of Radial Basis Function (RBF) networks based on least-squares and Particle Swarm Optimization methods. The formulation is based on the fundamental concept that supervised learning is a bi-objective optimization problem, in which two conflicting objectives should be minimized. The objectives are related to the empirical training error...
This paper presents the results from a neural network rule extraction algorithm applied to the LED display recognition problem. We show that pruned neural networks with small number of hidden nodes and connections are able to recognize all the 10 digits from 0 to 9. Earlier work by other researchers demonstrated how symbolic fuzzy rules can be extracted from trained neural networks to solve this problem...
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.