A new method for combining features via importance-inhibition analysis (IIA) is described to obtain more effective feature combination in learning question classification. Features are combined based on the inhibiti...A new method for combining features via importance-inhibition analysis (IIA) is described to obtain more effective feature combination in learning question classification. Features are combined based on the inhibition among features as well as the importance of individual features. Experimental results on the Chinese questions set show that, the IIA method shows a gradual increase in average and maximum accuracies at all feature combinations, and achieves great improvement over the importance analysis(IA) method on the whole. Moreover, the IIA method achieves the same highest accuracy as the one by the exhaustive method, and further improves the performance of question classification.展开更多
The objective of this study is to investigate a network failure problem with a significant path, emerging from the context of crisis management, such as in the case of natural disasters. For a given tree with m failed...The objective of this study is to investigate a network failure problem with a significant path, emerging from the context of crisis management, such as in the case of natural disasters. For a given tree with m failed edges, we assume that we have sufficient resources to recover k edges of the m edges. Each node has a positive weight. In this situation, we consider which k edges should be fixed in order to maximize the sum of the weights of the nodes reachable from the significant path. In this paper, we formulate such a problem as a combinatorial problem. Further, we show that a part of our problem may be solved by translating it into the terms of the so-called tree knapsack problem.展开更多
Recent research shows using network sion efficiency in wireless networks greatly et for retransmission over composite fading coding for reliable multicast can improve the retransmis- In this paper, we study how to co...Recent research shows using network sion efficiency in wireless networks greatly et for retransmission over composite fading coding for reliable multicast can improve the retransmis- In this paper, we study how to code the composite pack- channels efficiently. For the composite fading environ- ment with muhiple receivers, receivers experience different fading at any time. It' s very important to code the composite packet so that intended receivers are in good channel qualities, because in- tended receivers in deep fading have little opportunity to receive the composite packet correctly. Hence, we propose a novel composite packet coding principle of maximizing the total SNR of intend- ed receivers. Since the proposed principle is an NP-complete problem, an efficient heuristic algo- rithm with low complexity is given for finding a suboptimal solution. Simulation results show the heu- ristic based scheme achieves higher transmission efficiency than other network coding-based schemes due to the multi-user diversity gain.展开更多
The TODIM(an acronym in Portuguese for interactive and multiple attribute decision making) method is a valuable tool to solve the multiple attribute decision making(MADM) problems considering the behavior of the decis...The TODIM(an acronym in Portuguese for interactive and multiple attribute decision making) method is a valuable tool to solve the multiple attribute decision making(MADM) problems considering the behavior of the decision maker(DM), while it cannot be used to handle the problem with unknown weight information on attributes. In this paper, a novel method based on the classical TODIM method is proposed to solve the hybrid MADM problems with unknown weight information on attributes,in which attribute values are represented in four different formats:crisp numbers, interval numbers, triangular fuzzy numbers and trapezoidal fuzzy numbers. Firstly, the positive-ideal alternative and negative-ideal alternative are determined, and the gain and loss matrices are constructed by calculating the gain and loss of each alternative relatived to the ideal alternatives concerning each attribute based on different distance calculation formulas, which may avoid the information missing or information distortion in the process of unifying multiform attribute values into a certain representation form. Secondly, an optimization model based on the maximizing deviation(MD) method, by which the attribute weights can be determined, is established for the TODIM method. Further, the calculation steps to solve the hybrid MADM problems are given. Finally, two numerical examples are presented to illustrate the usefulness of the proposed method, and the results show that the DM's psychological behavior, attribute weights and the transformed information would highly affect the ranking orders of alternatives.展开更多
Gravity gradients acquired by the Gravity field and steady-state Ocean Circulation Explorer(GOCE) do not cover the entire earth because of its sun-synchronous orbit leaving data gaps with a radius of about 6.5° i...Gravity gradients acquired by the Gravity field and steady-state Ocean Circulation Explorer(GOCE) do not cover the entire earth because of its sun-synchronous orbit leaving data gaps with a radius of about 6.5° in the polar regions.Previous studies showed that the loss of data in the polar regions deteriorates the accuracy of the low order(or near zonal) coefficients of the earth gravity model,which is the so-called polar gap problem in geodesy.In order to find a stable solution for the earth gravity model from the GOCE gravity gradients,three models,i.e.the Gauss-Markov model,light constraint model and the mixed model,are compared and evaluated numerically with the gravity gradient simulated with the EGM2008.The comparison shows that the Best Linear Uniformly Unbiased Estimation(BLUUE) estimator of the mixed model can solve the polar gap problem as effectively as the light constraint model;furthermore,the mixed model is more rigorous in dealing with the supplementary information and leads to a better accuracy in determining the global geoid.展开更多
基金The National Natural Science Foundation of China(No.61003112,61170181)the Open Research Fund of State Key Laboratory for Novel Softw are Technology of China(No.KFKT2010B02)the Key Project of Natural Science Research for Anhui Colleges of China(No.KJ2011A048)
文摘A new method for combining features via importance-inhibition analysis (IIA) is described to obtain more effective feature combination in learning question classification. Features are combined based on the inhibition among features as well as the importance of individual features. Experimental results on the Chinese questions set show that, the IIA method shows a gradual increase in average and maximum accuracies at all feature combinations, and achieves great improvement over the importance analysis(IA) method on the whole. Moreover, the IIA method achieves the same highest accuracy as the one by the exhaustive method, and further improves the performance of question classification.
文摘The objective of this study is to investigate a network failure problem with a significant path, emerging from the context of crisis management, such as in the case of natural disasters. For a given tree with m failed edges, we assume that we have sufficient resources to recover k edges of the m edges. Each node has a positive weight. In this situation, we consider which k edges should be fixed in order to maximize the sum of the weights of the nodes reachable from the significant path. In this paper, we formulate such a problem as a combinatorial problem. Further, we show that a part of our problem may be solved by translating it into the terms of the so-called tree knapsack problem.
文摘Recent research shows using network sion efficiency in wireless networks greatly et for retransmission over composite fading coding for reliable multicast can improve the retransmis- In this paper, we study how to code the composite pack- channels efficiently. For the composite fading environ- ment with muhiple receivers, receivers experience different fading at any time. It' s very important to code the composite packet so that intended receivers are in good channel qualities, because in- tended receivers in deep fading have little opportunity to receive the composite packet correctly. Hence, we propose a novel composite packet coding principle of maximizing the total SNR of intend- ed receivers. Since the proposed principle is an NP-complete problem, an efficient heuristic algo- rithm with low complexity is given for finding a suboptimal solution. Simulation results show the heu- ristic based scheme achieves higher transmission efficiency than other network coding-based schemes due to the multi-user diversity gain.
基金supported by the Ministry of Education Project of Humanities and Social Sciences(13XJC630011)the Specialized Research Fund for the Doctoral Program of Higher Education of China(20130203120024)+1 种基金the Soft Science Project of Shaanxi Province(2013KRZ25)the Xi’an Science and Technology Plan Projects(SF1404)
文摘The TODIM(an acronym in Portuguese for interactive and multiple attribute decision making) method is a valuable tool to solve the multiple attribute decision making(MADM) problems considering the behavior of the decision maker(DM), while it cannot be used to handle the problem with unknown weight information on attributes. In this paper, a novel method based on the classical TODIM method is proposed to solve the hybrid MADM problems with unknown weight information on attributes,in which attribute values are represented in four different formats:crisp numbers, interval numbers, triangular fuzzy numbers and trapezoidal fuzzy numbers. Firstly, the positive-ideal alternative and negative-ideal alternative are determined, and the gain and loss matrices are constructed by calculating the gain and loss of each alternative relatived to the ideal alternatives concerning each attribute based on different distance calculation formulas, which may avoid the information missing or information distortion in the process of unifying multiform attribute values into a certain representation form. Secondly, an optimization model based on the maximizing deviation(MD) method, by which the attribute weights can be determined, is established for the TODIM method. Further, the calculation steps to solve the hybrid MADM problems are given. Finally, two numerical examples are presented to illustrate the usefulness of the proposed method, and the results show that the DM's psychological behavior, attribute weights and the transformed information would highly affect the ranking orders of alternatives.
基金Supported by the National Natural Science Foundation of China (No.41004007)
文摘Gravity gradients acquired by the Gravity field and steady-state Ocean Circulation Explorer(GOCE) do not cover the entire earth because of its sun-synchronous orbit leaving data gaps with a radius of about 6.5° in the polar regions.Previous studies showed that the loss of data in the polar regions deteriorates the accuracy of the low order(or near zonal) coefficients of the earth gravity model,which is the so-called polar gap problem in geodesy.In order to find a stable solution for the earth gravity model from the GOCE gravity gradients,three models,i.e.the Gauss-Markov model,light constraint model and the mixed model,are compared and evaluated numerically with the gravity gradient simulated with the EGM2008.The comparison shows that the Best Linear Uniformly Unbiased Estimation(BLUUE) estimator of the mixed model can solve the polar gap problem as effectively as the light constraint model;furthermore,the mixed model is more rigorous in dealing with the supplementary information and leads to a better accuracy in determining the global geoid.