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How to accurately estimate facial age is a difficult problem due to insufficiency of training data. In this paper, an effective approach is proposed to estimate facial age by means of extreme learning machine (ELM). In the proposed method, a set of features is randomly selected from the original features to consist of a feature subspace. Given an initial weight matrix, the training samples within...
In this paper, we present a fast approach for fall recognition. This approach according to human-body skeleton information which was obtained from Kinect sensor. First, following the falls defined by FICSIT, head and center joints, and their relative distance are considered as feature to describe the behavior. Second, applying the slide-window method and threshold for behavior action stage, motion...
Feature selection is an essential part of text categorization, which can effectively improve classification precision and efficiency. With some drawbacks proposed from traditional IG approach, an optimized approach that takes concentration and distribution into account is proposed for improving IG approach. The experimental results show that the improved IG approach is superior to traditional IG approach...
This paper studies off-line control and on-line control based on Adaptive Dynamical Programming and proposes an optimal adaptive algorithm with the combination of off-line and on-line training; The method using off-line value iteration algorithm gets off-line opitical controller, then using on-line policy iteration algorithm of Q learning improves the off-line opitical controller. Simulation results...
A method is proposed based on application of Error Correcting Output Codes Support Vector Machine (ECOC-SVM) in order to get better results of speech recognition. Some uncorrelated SVMs are constructed based on ECOC matrix codes to improve the integrated performance of fault tolerance of classification model. This paper gives four commonly-used encodings of ECOC. By comparing the results with that...
Trajectory tracking is popularity in industrial procession, such as machining parts control, high automatic control for a roller of shearer cutting in memory mode, etc. In these cases, trajectory tracked was often artificially pre-determined, and essentially belongs to the fields of predictable control. There are still some shortages in the respect of tracking accuracy and responsiveness among the...
In order to improve the level of electronic commerce credit rating, we establish a full set of E-commerce credit rating level system, and present a method which based on the combination of a principal component analysis and BP neural networks. This method improved the traditional BP neural networks, by using a principal component analysis could eliminate the correlation between the inputs of neural...
Mathematical software is a subject newly set for the major of mathematics in university. The author points out several problems in the teaching of this subject: the importance of the subject of mathematical software is not realized by the universities and students; there is no appropriate teaching material for this subject; the subject has no close connection with other subjects, etc. Besides, reform...
This paper presents a novel real-time optimal neural controller which is based on improved Action-Depended Dual Heuristic Dynamic Programming (ADDHP) method, including its schematic diagram, the training algorithms and its implementation steps. This method requires neither an explicit model of the controlled plant nor the indispensable system performance index `J' which is explicitly defined in the...
The boiler combustion process of power plant is a typical process with the features of multi-input, multi-output, strong non-linearity, strong jamming and close coupling. The coupling relationship between its parameters correlated with combustion process is very anfractuous, so it is very hard to solve its optimal control problem with conventional control methods. And Adaptive Critic Designs (ACDs)...
In the setting of supply chain, order evaluation of the core manufacture enterprise is a task of demand management and the prerequisite for production planning. Order selection is a multi-attribute issue which involves integrated decision-making. In this paper, firstly, an order priority evaluation index system is constructed within a more systematic and comprehensive supply chain setting. Secondly,...
Data classification has been studied widely in the fields of Artificial Intelligence, Machine Learning, Data Mining and Pattern Recognition. Up to the present, the development of classification has made great achievements, and many kinds of classified technology and theory will continue to emerge. This paper discusses a great deal of classification algorithms based on the Artificial Neural Networks,...
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