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Prediction of regional logistics requirement provides a basis for the plan of regional logistics. In the study, support vector regression is presented to predict regional logistics requirement. The regional logistics data from 1996 to 2006 in Shanghai municipality are used as the application data of support vector regression. The comparison of prediction error between BP neural network and support...
In order to improve the recognition rate and practicability of the existing speech access control system, a method of HMM/ANN hybrid model was presented. By the analysis on the principle of speech recognition system, a speech access control system was designed by using DSP as the hardware platform. The working principle and the software design process of the system were described. In the training...
This paper firstly examines the traditional vehicle styling evaluation methods and issues, and then presents a new approach which uses ANN (artificial neural network) to build an expert system for bus styling evaluation. It describes the key technical issues of quasi-three-dimensional bus styling evaluation expert system from data collection, graphical pre-processing, graphics feature extraction,...
It is widely believed that human resource competitiveness is becoming the core competitiveness of an enterprise. Nowadays, IT (Information Technology) is widely used in human resource management. This paper extracted four factors-cost factor, turnover factor, human resource planning factor and employee development factor from 30 indexes of the enterprise human resource competitiveness by using PCA...
In Service Oriented Architecture, Quality of Service (Qos) represents an important issue which is often considered when selecting and composing services. For receiving up-to-date information, non-functional properties can be continuously monitored using current methods. Because of the occurrence of monitoring at every time of service calling, the current methods imposes some overhead on the SOA. The...
In order to overcome the shortcomings of BP neural network, the golden section theory was used to get the reasonable number of Back Propagation (BP) neural network's hidden nodes. By using Genetic Algorithm (GA) to optimize the initial weights and threshold value of BP neural network, the network converged quickly and the recognition precision was increased. The GA-BP neural network model was utilized...
With the development of science and technology, the case of crime prevention sharply increases in order that the effectiveness evaluation for security system becomes essential to a professional and technical work in people's lives in China. How to make the security system have the maximal protection effectiveness is the problem which is considered in the process of system design. In this paper, firstly,...
Singular points detection, a crucial step for fingerprint identification system, is accurately robust, and reliable. In the processing of the fingerprint image matching and classification, many method use singular points to align two fingerprint images to surmount the problems about rotation and translation. The performances of the fingerprint recognition system rely on the effect of singular points...
Although simple genetic algorithm (SGA) can, to some extent, improve the back propagation neural network (BP), it is prone to prematurity and losing the optimal solutions. Niche technology and fuzzy control theory are introduced to improve SGA and the improved one is used to optimize BP. The improved genetic algorithm is used to optimize BP neural network. In addition, due to the increasingly voltage...
In order to solve the problem of BP neural network, genetic support vector regression is presented to predict the lifetime of cylinder. Support vector regression (SVR) is a novel prediction algorithm based on structure risk minimization principles, which can lead to great generalization ability. In the genetic support vector regression model, the genetic algorithm is used to optimize the parameters...
Traffic flow prediction plays an important role in urban traffic management and control. Traditional prediction methods are mostly difficult to meet the high complexity, randomness and uncertainty characteristics of urban traffic flow. In this paper, a new prediction model is proposed based on self-adaptive neural network. Compared with other methods, it possesses the advantages of low computational...
Voting algorithms are used in a wide area of control systems from real-time and safety-critical control systems to pattern recognition, image processing and human organization systems in order to arbitrating among redundant results of processing in redundant hardware modules or software versions. From a point of view, voting algorithms can be categorized to agreement-based voters like plurality and...
This paper provides a solution for ERP software selection & elimination. ERP is a way to integrate data and processes of an organization into a centralized system that aims to have a single software solution where the information needed for decision making is shared across different departments. The selection or elimination of technology is a multi-criteria, multi-attribute, decision making problem,...
Decision-making structures are important building blocks in most of the software; however, it may be difficult to verify them because there are various input conditions and several paths causing them to behave differently. Test oracles are reliable sources of how the software must operate. The aim of the present paper is to study the applications of Artificial Neural Networks as an automated oracle...
This study evaluated the capability of neural classifier to perform the separation between epileptiform and non-epileptiform events. To processing the EEG signals was used the Wavelet Transform through the use of the Coiflet1 function. The main elements present in the EEG signals were separated in five distinct event classes (spikes, sharp waves, blinks, background activity and noise). All the events...
Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, thus it is the most promising for high security environments. Hence numbers of IRIS recognition algorithms are proposed, such as ICA (independent component analysis), SVD (singular value decomposition), Characterizing key local variation etc. which extracts iris features and...
The paper presents an adaptive Auto Rate Fallback (ARF) scheme to improve the performance of aggregate throughput in IEEE 802.11 Wireless Local Area Network (WLAN) with multiple nodes. When the number of contending nodes increases, using ARF will be likely to degrade transmission rates due to increasing packet collisions and can consequently cause a decline of the overall throughput. In this paper...
This study proposes to analyze morphological characteristics of electroencephalogram (EEG) signals in order to define a representation of epileptiform events that can distinguish them from other events occurring in the signal. Despite the existence of several studies on parameterization of EEG signals, particularly for automatic detection of paroxysms related to epilepsy, it was necessary to create...
Due to their adverse health effects and their abundance in urban areas, diesel exhaust particles (DEP) have been of great concern in the past years. An experiment was carried out on a direct injection, turbocharged diesel engine to investigate the number emission characteristics of particles. Furthermore, an artificial neural network (ANN) was used to establish an emission model of the diesel engine...
This paper presents an approach to the single output regression problem using ensemble of duo output neural networks based on bagging technique. Each component in the ensemble consists of a pair of duo output neural networks. The first neural network is trained to provide duo outputs which are a pair of truth and falsity values whereas the second neural network provides a pair of falsity and truth...
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