Journal•ISSN: 1006-9798
Journal of Qingdao University
Qingdao University
About: Journal of Qingdao University is an academic journal. The journal publishes majorly in the area(s): Supply chain & Control system. Over the lifetime, 290 publications have been published receiving 574 citations.
Topics: Supply chain, Control system, Fault (power engineering), Wavelet transform, Camera resectioning
Papers published on a yearly basis
Papers
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TL;DR: Experimental results show that the new algorithm can obtain the higher training efficiency and better forecasting results than the traditional RBFNN algorithm.
Abstract: A new Bacterial Colony Radial Basis Function Neural Network(RBFNN) algorithm,which was applied to forecast the stock price,was proposed on the basis of the bacterial colony algorithm,and a technological index model was introduced in the forecast.Experimental results show that the new algorithm can obtain the higher training efficiency and better forecasting results than the traditional RBFNN algorithm.
30 citations
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TL;DR: In this paper, the authors studied the oscillation of the linear differential equation with deviating arguments and obtained a new criterion for the above equation, which improved some known results and improved the performance.
Abstract: The aim of this paper is to study the oscillation for the linear differential equation with deviating arguments. By some new skills we obtain a new criterion for the above equation. These conditions improve some known results.
28 citations
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TL;DR: A SVMs classifier based on k-means clustering algorithm is presented for the classification of unlabeled data to solve the problem that the support vector machines (SVMs) must use a selected training set classified in advance.
Abstract: To solve the problem that the support vector machines (SVMs) must use a selected training set classified in advance, a SVMs classifier based on k-means clustering algorithm is presented for the classification of unlabeled data. The new algorithm is to firstly divide unlabeled data into many subsets with a new label by k-means clustering , then train the SVMs using the new data set to get decision boundary and support vectors, at last use the SVMs classifier to classify the unlabeled data. The simulations show that the classification error is less than 2% when the CPU training time is 1. 8280seconds and the number of support vector is 60.
23 citations
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TL;DR: In this article, the Fourier expansins for the Genocchi polynomials were derived by using the Lipschitz summation formula and obtaining the integral representations for the GPs.
Abstract: Applying the analytic method and the transformation technique of the series,we give the Fourier expansins for the Genocchi polynomials by using the Lipschitz summation formula and obtain the integral representations for the Genocchi polynomials.Furthermore,some new and interesting results of the Genocchi polynomials are also derived.
15 citations
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TL;DR: In this paper, a two-player, finite-horizon differential game model is proposed to analyze joint implementation in environmental projects, one of the flexible mechanisms considered in the Kyoto Protocol, and the results show that allowing for foreign investments increases the welfares of both parties involved in the project.
Abstract: This paper proposes a two-player,finite-horizon differential game model to analyzejoint implementation in environmental projects, one of the flexible mechanisms considered in the Kyoto Protocol. Our results show that allowing for foreign investments increases the welfares of both parties involved in the project. Further, imposing an environmental target constraint does not necessarily deteriorate the payoffs of both players.Finally, aleakage effect does occur when foreign investments are possible.
11 citations