The fact that outburst traffic in industrial Ethemet was focused on that would bring self-similar phenomenon leading to the delay increase of the cyclical data, and a hybrid priority queue schedule model was proposed ...The fact that outburst traffic in industrial Ethemet was focused on that would bring self-similar phenomenon leading to the delay increase of the cyclical data, and a hybrid priority queue schedule model was proposed in which the outburst data was given the highest priority. Some properties of the self-similar outburst data were proved by network calculus, and its service curve scheduled by the switch was gained. And then the performance of the scheduling algorithm was obtained. The simulation results are close to those calculated by using network calculus model. Some results are of actual significance to the construction of switched industrial Ethernet.展开更多
This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on ...This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on portfolio investment based on the practical conditions of securities market. In addition, investors should adjust the portfolio according to market changes, changing or not changing the category of risky securities. Markowitz meanvariance approach is applied to the multi-period portfolio selection problems. Because the sub-models are optimal mixed integer program, whose objective function is not unimodal and feasible set is with a particular structure, traditional optimization method usually fails to find a globally optimal solution. So this paper employs the hybrid genetic algorithm to solve the problem. Investment policies that accord with finance market and are easy to operate for investors are put forward with an illustration of application.展开更多
For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude...For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude oil blending process. The objective is to keep the property of feedstock, mainly described by the true boiling point (TBP) data, consistent and suitable. Firstly, the mathematical model is established. Then, a heuristically initialized hybrid iterative (HIHI) algorithm based on a two-level optimization structure, in which tabu search (TS) and differential evolution (DE) are used for upper-level and lower-level optimization, respectively, is proposed to get the model solution. Finally, the effectiveness and efficiency of the scheduling strategy is validated via real data from a certain refinery.展开更多
This letter proposes an effective and robust speech feature extraction method based on statistical analysis of Pitch Frequency Distributions (PFD) for speaker identification. Compared with the conventional cepstrum, P...This letter proposes an effective and robust speech feature extraction method based on statistical analysis of Pitch Frequency Distributions (PFD) for speaker identification. Compared with the conventional cepstrum, PFD is relatively insensitive to Additive White Gaussian Noise (AWGN), but it does not show good performance for speaker identification, even if under clean environments. To compensate this shortcoming, PFD and conventional cepstrum are combined to make the ultimate decision, instead of simply taking one kind of features into account.Experimental results indicate that the hybrid approach can give outstanding improvement for text-independent speaker identification under noisy environments corrupted by AWGN.展开更多
Under the smart grid paradigm, in the near future all consumers will be exposed to variable pricing schemes introduced by utilities. Hence, there is a need to develop algorithms which could be used by the consumers to...Under the smart grid paradigm, in the near future all consumers will be exposed to variable pricing schemes introduced by utilities. Hence, there is a need to develop algorithms which could be used by the consumers to schedule their loads. In this paper, load scheduling problem is formulated as a LCP （load commitment problem）. The load model is general and can model atomic and non-atomic loads. Furthermore, it can also take into consideration the relative discomfort caused by delay in scheduling any load. For this purpose, a single parameter ＂uric＂ is introduced in the load model which captures the relative discomfort caused by delay in scheduling a particular load. Guidelines for choosing this parameter are given. All the other parameters of the proposed load model can be easily specified by the consumer. The paper shows that the general LCP can be viewed as multi-stage decision making problem or a MDP （Markov decision problem）. RL （reinforcement learning） based algorithm is developed to solve this problem. The efficacy of the algorithm is investigated when the price of electricity is available in advance as well as for the case when it is random. The scalability of the approach is also investigated.展开更多
It makes an empirical study of college students＇ employment ability and influence factor situation. Based on the questionnaire of 388 graduates of different subjects, through the explorative Ihctors and confirmatory ...It makes an empirical study of college students＇ employment ability and influence factor situation. Based on the questionnaire of 388 graduates of different subjects, through the explorative Ihctors and confirmatory factor analysis, it finds that the college students＇ employment ability influence factor model includes employment quality and employment expectation of 13 factors, and the model fitting is better. The employment ability influence factor model of college students is good for university education, enterprise recruitment strategy adjustment and students＇ self development.展开更多
Through the construction of the comprehensive evaluation index system and the coordination degree model of the rural in- frastructure and the rural economic development level, the author carries out an empirical analy...Through the construction of the comprehensive evaluation index system and the coordination degree model of the rural in- frastructure and the rural economic development level, the author carries out an empirical analysis on the rural infrastructure and economic coordinated development in the country＇s 31 regions. Research shows that the gap between the levels of the development of the rural in-frastructure in China is large, presenting the gradually reducing gradient distribution from the east to the west. The rural infrastructure de- velopment level has significant positive correlation with the level of economic development. For those provinces of the high development level of the rural economy, the infrastructure construction level is also relatively high. From the view of the coordination degree, it presents the obvious ＂dumbbell＂ shape, and there are more provinces which belong to the high quality coordination and the serious imbalance, with the coordinated degree in the eastern regions obviously higher than that in the central and western regions.展开更多
The cognition of low-carbon tourism among tourists is closely related to education level.In this study,the degree of coordination of low-carbon cognition with different educational levels is assessed by the coupling m...The cognition of low-carbon tourism among tourists is closely related to education level.In this study,the degree of coordination of low-carbon cognition with different educational levels is assessed by the coupling model in Wutai Mountain,and the effect of each factor on low-carbon cognition is analyzed by the geographical detector.The results show that:(1)The six cognition aspects of low-carbon tourism gradually transition from the level of intermediate coordination to good coordination with the advancement of the education level.Both the low-level and lower-level tourists belong to the lag type of low-carbon visiting cognition,and the higher-level tourists belong to the lag type of low-carbon shopping cognition,while the high-level tourists show the lag type of low-carbon food cognition.(2)According to the individual factors and interactive effects in the geographical detector,each impacting factor has a decisive effect on tourists’cognition of low-carbon tourism,and the effect of any two factors after interaction shows either a double-factor or nonlinear enhancement.The findings of this study provide valuable practical implications for helping tourism destinations to educate tourists and improve their low-carbon tourism options.At the same time,this study will provide theoretical standards for measuring tourists’cognition of low-carbon tourism,so as to enrich and improve the theoretical research related to low-carbon tourism.展开更多
The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode...The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode is fixed, either playback or real-time transmission. Considering the characteristic of the problem, a multi-satellite real-time and playback data transmission scheduling model is established and a novel algorithm based on quantum discrete particle swarm optimization(QDPSO)is proposed. Furthermore, we design the longest compatible transmission chain mutation operator to enhance the performance of the algorithm. Finally, some experiments are implemented to validate correctness and practicability of the proposed algorithm.展开更多
基金Project( 60425310) supported by the National Science Fund for Distinguished Young Scholars of ChinaProject(05JJ40118) supported by the Natural Science Foundation of Hunan Province, China
文摘The fact that outburst traffic in industrial Ethemet was focused on that would bring self-similar phenomenon leading to the delay increase of the cyclical data, and a hybrid priority queue schedule model was proposed in which the outburst data was given the highest priority. Some properties of the self-similar outburst data were proved by network calculus, and its service curve scheduled by the switch was gained. And then the performance of the scheduling algorithm was obtained. The simulation results are close to those calculated by using network calculus model. Some results are of actual significance to the construction of switched industrial Ethernet.
基金Supported by Natural Science Foundation of Tianjin (No 09JCYBJC01800, No07JCYBJC05200)Application Mathematic Center of Liu Hui, Nankai University and Tianjin University (No2001T08)
文摘This paper proposes a multi-period portfolio investment model with class constraints, transaction cost, and indivisible securities. When an investor joins the securities market for the first time, he should decide on portfolio investment based on the practical conditions of securities market. In addition, investors should adjust the portfolio according to market changes, changing or not changing the category of risky securities. Markowitz meanvariance approach is applied to the multi-period portfolio selection problems. Because the sub-models are optimal mixed integer program, whose objective function is not unimodal and feasible set is with a particular structure, traditional optimization method usually fails to find a globally optimal solution. So this paper employs the hybrid genetic algorithm to solve the problem. Investment policies that accord with finance market and are easy to operate for investors are put forward with an illustration of application.
基金Supported by the National High Technology Research and Development Program of China （2007AA04Z193） the National Natural Science Foundation of China （60974008 60704032）
文摘For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude oil blending process. The objective is to keep the property of feedstock, mainly described by the true boiling point (TBP) data, consistent and suitable. Firstly, the mathematical model is established. Then, a heuristically initialized hybrid iterative (HIHI) algorithm based on a two-level optimization structure, in which tabu search (TS) and differential evolution (DE) are used for upper-level and lower-level optimization, respectively, is proposed to get the model solution. Finally, the effectiveness and efficiency of the scheduling strategy is validated via real data from a certain refinery.
文摘This letter proposes an effective and robust speech feature extraction method based on statistical analysis of Pitch Frequency Distributions (PFD) for speaker identification. Compared with the conventional cepstrum, PFD is relatively insensitive to Additive White Gaussian Noise (AWGN), but it does not show good performance for speaker identification, even if under clean environments. To compensate this shortcoming, PFD and conventional cepstrum are combined to make the ultimate decision, instead of simply taking one kind of features into account.Experimental results indicate that the hybrid approach can give outstanding improvement for text-independent speaker identification under noisy environments corrupted by AWGN.
文摘Under the smart grid paradigm, in the near future all consumers will be exposed to variable pricing schemes introduced by utilities. Hence, there is a need to develop algorithms which could be used by the consumers to schedule their loads. In this paper, load scheduling problem is formulated as a LCP （load commitment problem）. The load model is general and can model atomic and non-atomic loads. Furthermore, it can also take into consideration the relative discomfort caused by delay in scheduling any load. For this purpose, a single parameter ＂uric＂ is introduced in the load model which captures the relative discomfort caused by delay in scheduling a particular load. Guidelines for choosing this parameter are given. All the other parameters of the proposed load model can be easily specified by the consumer. The paper shows that the general LCP can be viewed as multi-stage decision making problem or a MDP （Markov decision problem）. RL （reinforcement learning） based algorithm is developed to solve this problem. The efficacy of the algorithm is investigated when the price of electricity is available in advance as well as for the case when it is random. The scalability of the approach is also investigated.
文摘It makes an empirical study of college students＇ employment ability and influence factor situation. Based on the questionnaire of 388 graduates of different subjects, through the explorative Ihctors and confirmatory factor analysis, it finds that the college students＇ employment ability influence factor model includes employment quality and employment expectation of 13 factors, and the model fitting is better. The employment ability influence factor model of college students is good for university education, enterprise recruitment strategy adjustment and students＇ self development.
文摘Through the construction of the comprehensive evaluation index system and the coordination degree model of the rural in- frastructure and the rural economic development level, the author carries out an empirical analysis on the rural infrastructure and economic coordinated development in the country＇s 31 regions. Research shows that the gap between the levels of the development of the rural in-frastructure in China is large, presenting the gradually reducing gradient distribution from the east to the west. The rural infrastructure de- velopment level has significant positive correlation with the level of economic development. For those provinces of the high development level of the rural economy, the infrastructure construction level is also relatively high. From the view of the coordination degree, it presents the obvious ＂dumbbell＂ shape, and there are more provinces which belong to the high quality coordination and the serious imbalance, with the coordinated degree in the eastern regions obviously higher than that in the central and western regions.
基金Supported by Program for the Philosophy and Social Sciences Research of Higher Learning Institutions of Shanxi(2023W064)。
文摘The cognition of low-carbon tourism among tourists is closely related to education level.In this study,the degree of coordination of low-carbon cognition with different educational levels is assessed by the coupling model in Wutai Mountain,and the effect of each factor on low-carbon cognition is analyzed by the geographical detector.The results show that:(1)The six cognition aspects of low-carbon tourism gradually transition from the level of intermediate coordination to good coordination with the advancement of the education level.Both the low-level and lower-level tourists belong to the lag type of low-carbon visiting cognition,and the higher-level tourists belong to the lag type of low-carbon shopping cognition,while the high-level tourists show the lag type of low-carbon food cognition.(2)According to the individual factors and interactive effects in the geographical detector,each impacting factor has a decisive effect on tourists’cognition of low-carbon tourism,and the effect of any two factors after interaction shows either a double-factor or nonlinear enhancement.The findings of this study provide valuable practical implications for helping tourism destinations to educate tourists and improve their low-carbon tourism options.At the same time,this study will provide theoretical standards for measuring tourists’cognition of low-carbon tourism,so as to enrich and improve the theoretical research related to low-carbon tourism.
基金supported by the National Natural Science Foundation of China(6110118461174159)
文摘The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode is fixed, either playback or real-time transmission. Considering the characteristic of the problem, a multi-satellite real-time and playback data transmission scheduling model is established and a novel algorithm based on quantum discrete particle swarm optimization(QDPSO)is proposed. Furthermore, we design the longest compatible transmission chain mutation operator to enhance the performance of the algorithm. Finally, some experiments are implemented to validate correctness and practicability of the proposed algorithm.
