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61.
Local feature-based approaches mainly aim to achieve robustness to variations in facial images by assuming that only some
parts of the facial images may be affected. However, such approaches may lose spatial information. In this study, a compromise
feature extraction scheme is studied which extracts local features while preserving spatial information. The proposed scheme
exploits an ensemble of classifiers where each member is constructed using randomly selected design parameters including the
size, number and location of sub-images for local feature extraction. Experiments conducted on FERET and ORL databases have
shown that proposed scheme surpasses the local feature-based reference systems which focus on either local information or
preserving spatial information. 相似文献
62.
63.
In this paper, a novel classification rule extraction algorithm which has been recently proposed by authors is employed to
determine the causes of quality defects in a fabric production facility in terms of predetermined parameters like machine
type, warp type etc. The proposed rule extraction algorithm works on the trained artificial neural networks in order to discover
the hidden information which is available in the form of connection weights in them. The proposed algorithm is mainly based
on a swarm intelligence metaheuristic which is known as Touring Ant Colony Optimization (TACO). The algorithm has a hierarchical
structure with two levels. In the first level, a multilayer perceptron type neural network is trained and its weights are
extracted. After obtaining the weights, in the second level, the TACO-based algorithm is applied to extract classification
rules. The main purpose of the present work is to determine and analyze the most effective parameters on the quality defects
in fabric production. The parameters and their levels which give the best quality results are tried to be discovered and evaluated
by making use of the proposed algorithm. It is also aimed to compare the accuracy of proposed algorithm with several other
rule-based algorithms in order to present its competitiveness. 相似文献
64.
Nilgün Fığlalı Celal Özkale Orhan Engin Alpaslan Fığlalı 《Computers & Industrial Engineering》2009,56(2):538-559
In recent years, one of the most important and promising research fields has been metaheuristics to find optimal or near-optimal solutions for NP-hard combinatorial optimization problems. Improving the quality of the solution or the solution time is basic research area on metaheuristics. Modifications of the existing ones or creation of hybrid approaches are the focus of these efforts. Another area of improving the solution quality of metaheuristics is finding the optimal combination of algorithm control parameters. This is usually done by design of experiments or one-at-a-time approach in genetic algorithms, simulated annealing and similar metaheuristics. We observe that, in studies which use Ant Colonies Optimization (ACO) as an optimization technique; the levels of control parameters are determined by some non-systematic initial experiments and the interactions of the parameters are not studied yet.In this study, the parameters of Ant System have been investigated on different sized and randomly generated job-shop scheduling problems by using design of experiments. The effects and interactions of the parameters have been interpreted with the outputs of the experiments. Referring to the statistical analysis it is observed that none of the interactions between the Ant System parameters has a significant effect on makespan value. A specific fractional experimental design is suggested instead of the full factorial design. Depending on the findings from the benchmark problems it will be a reliable approach to use the suggested design for saving time and effort in experiments without sacrificing the solution quality. 相似文献
65.
Öznur Özkasap 《Computer Communications》2009,32(4):668-678
For ensuring reliability at the transport level end-to-end multicasting, an efficient loss recovery mechanism is indispensable. We consider scalability, topology independence and robustness as the significant features that such a mechanism should offer, and demonstrate that an epidemic loss recovery approach is superior in all these aspects. We also show that the epidemic approach transparently handles network link failures by using pair-wise propagation of information, and compare it with feedback controlled loss recovery on identical network settings. The contribution of this work is the simulative analysis of recovery overhead distribution on multicast group members in the case of various link failures on the network, the impact of group size, randomized system-wide noise and message rate on scalability, and examination of various scenarios modeling the overlay networks. We investigate the important features of epidemic multicast loss recovery extensively together and reach concrete results on realistic network scenarios. 相似文献
66.
Geno-mathematical identification of the multi-layer perceptron 总被引:1,自引:0,他引:1
Ralf Östermark 《Neural computing & applications》2009,18(4):331-344
In this paper, we will focus on the use of the three-layer backpropagation network in vector-valued time series estimation
problems. The neural network provides a framework for noncomplex calculations to solve the estimation problem, yet the search
for optimal or even feasible neural networks for stochastic processes is both time consuming and uncertain. The backpropagation
algorithm—written in strict ANSI C—has been implemented as a standalone support library for the genetic hybrid algorithm (GHA)
running on any sequential or parallel main frame computer. In order to cope with ill-conditioned time series problems, we
extended the original backpropagation algorithm to a K nearest neighbors algorithm (K-NARX), where the number K is determined genetically along with a set of key parameters. In the K-NARX algorithm, the terminal solution at instant t can be used as a starting point for the next t, which tends to stabilize the optimization process when dealing with autocorrelated time series vectors. This possibility
has proved to be especially useful in difficult time series problems. Following the prevailing research directions, we use
a genetic algorithm to determine optimal parameterizations for the network, including the lag structure for the nonlinear
vector time series system, the net structure with one or two hidden layers and the corresponding number of nodes, type of
activation function (currently the standard logistic sigmoid, a bipolar transformation, the hyperbolic tangent, an exponential
function and the sine function), the type of minimization algorithm, the number K of nearest neighbors in the K-NARX procedure, the initial value of the Levenberg–Marquardt damping parameter and the value of the neural learning (stabilization)
coefficient α. We have focused on a flexible structure allowing addition of, e.g., new minimization algorithms and activation
functions in the future. We demonstrate the power of the genetically trimmed K-NARX algorithm on a representative data set. 相似文献
67.
Halife Kodaz Seral Özşen Ahmet Arslan Salih Güneş 《Expert systems with applications》2009,36(2):3086-3092
In this paper, we have made medical application of a new artificial immune system named the information gain based artificial immune recognition system (IG-AIRS) which minimizes the negative effects of taking into account all attributes in calculating Euclidean distance in shape–space representation which is used in many artificial immune systems. For medical data, thyroid disease data set was applied in the performance analysis of our proposed system. Our proposed system reached 95.90% classification accuracy with 10-fold CV method. This result ensured that IG-AIRS would be helpful in diagnosing thyroid function based on laboratory tests, and would open the way to various ill diagnoses support by using the recent clinical examination data, and we are actually in progress. 相似文献
68.
Enterprise resource planning (ERP) systems have gained major prominence by enabling companies to streamline their operations, leverage and integrate business data process. In order to implement an ERP project successfully, it is necessary to select an ERP system which can be aligned with the needs of the company. Thus, a robust decision making approach for ERP software selection requires both company needs and characteristics of the ERP system and their interactions to be taken into account. This paper develops a novel decision framework for ERP software selection based on quality function deployment (QFD), fuzzy linear regression and zero–one goal programming. The proposed framework enables both company demands and ERP system characteristics to be considered, and provides the means for incorporating not only the relationships between company demands and ERP system characteristics but also the interactions between ERP system characteristics through adopting the QFD principles. The presented methodology appears as a sound investment decision making tool for ERP systems as well as other information systems. The potential use of the proposed decision framework is illustrated through an application. 相似文献
69.
In wind energy conversion systems, one of the operational problems is the changeability and discontinuity of wind. In most cases, wind speed can fluctuate rapidly. Hence, quality of produced energy becomes an important problem in wind energy conversion plants. Several control techniques have been applied to improve the quality of power generated from wind turbines. Pitch control is the most efficient and popular power control method, especially for variable-speed wind turbines. It is a useful method for power regulation above the rated wind speed. This paper proposes an artificial neural network-based pitch angle controller for wind turbines. In the simulations, a variable-speed wind turbine is modeled, and its operation is observed by using two types of artificial neural network controllers. These are multi-layer perceptrons with back propagation learning algorithm and radial basis function network. It is shown that the power output was successfully regulated during high wind speed, and as a result overloading or outage of the wind turbine was prevented. 相似文献
70.