The need for travel demand models is growing worldwide. Obtaining reasonably accurate level of service (LOS) attributes of different travel modes such as travel time and cost representing the performance of transporta...The need for travel demand models is growing worldwide. Obtaining reasonably accurate level of service (LOS) attributes of different travel modes such as travel time and cost representing the performance of transportation system is not a trivial task, especially in growing cities of developing countries. This study investigates the sensitivity of results of a travel mode choice model to different specifications of network-based LOS attributes using a mixed logit model. The study also looks at the possibilities of correcting some of the inaccuracies in network-based LOS attributes. Further, the study also explores the effects of different specifications of LOS data on implied values of time and aggregation forecasting. The findings indicate that the implied values of time are very sensitive to specification of data and model implying that utmost care must be taken if the purpose of the model is to estimate values of time. Models estimated on all specifications of LOS-data perform well in prediction, likely suggesting that the extra expense on developing a more detailed and accurate network models so as to derive more precise LOS attributes is unnecessary for impact analyses of some policies.展开更多
Pythagorean fuzzy set(PFS) can provide more flexibility than intuitionistic fuzzy set(IFS) for handling uncertain information, and PFS has been increasingly used in multi-attribute decision making problems. This paper...Pythagorean fuzzy set(PFS) can provide more flexibility than intuitionistic fuzzy set(IFS) for handling uncertain information, and PFS has been increasingly used in multi-attribute decision making problems. This paper proposes a new multiattribute group decision making method based on Pythagorean uncertain linguistic variable Hamy mean(PULVHM) operator and VIKOR method. Firstly, we define operation rules and a new aggregation operator of Pythagorean uncertain linguistic variable(PULV) and explore some properties of the operator.Secondly, taking the decision makers' hesitation degree into account, a new score function is defined, and we further develop a new group decision making approach integrated with VIKOR method. Finally, an investment example is demonstrated to elaborate the validity of the proposed method. Sensibility analysis and comprehensive comparisons with another two methods are performed to show the stability and advantage of our method.展开更多
It has been a dream that theoretical biology can be extensively applied in experimental biology to accelerate the understanding of the sophiscated movements in living organisms. A brave assay and an excellent example ...It has been a dream that theoretical biology can be extensively applied in experimental biology to accelerate the understanding of the sophiscated movements in living organisms. A brave assay and an excellent example were represented by enzymology, in which the well-established physico-chemistry is used to describe, to fit, to predict and to improve enzyme reactions. Before the modern bioinformatics, the developments of the combination of theoretical biology and experimental biology have been mainly limited to various classic formulations. The systematic use of graphic rules by Prof. Kuo-Chen Chou and his co-workers has significantly facilitated to deal with complicated enzyme systems. With the recent fast progress of bioinformatics, prediction of protein structures and various protein attributes have been well established by Chou and co-workers, stimulating the experimental biology. For example, their recent method for predicting protein subcellular localization (one of the important attributes of proteins) has been extensively applied by scientific colleagues, yielding many new results with thousands of citations. The research by Prof. Chou is characterized by introducing novel physical concepts as well as powerful and elegant mathematical methods into important biomedical problems, a focus throughout his career, even when facing enormous difficulties. His efforts in 50 years have greatly helped us to realize the dream to make “theoretical and experimental biology in one”. Prof. Richard Giege is well known for his multi-disciplinary research combining physics, chemistry, enzymology and molecular biology. His major focus of study is on the identity of tRNAs and their interactions with aminoacyl-tRNA synthetases (aaRS), which are of critical importance to the fidelity of protein biosynthesis. He and his colleagues have carried out the first crystallization of a tRNA/aaRS complex, that between tRNAAsp and AspRS from yeast. The determination of the complex structure contributed significantly to under- stand the interaction of protein and RNA. From his fine research, they have also found other biological function of these small RNAs. He has developed in parallel appropriate methods for his research, of which the protein crystallogenesis, a name he has coined, is an excellent example. Now macromolecular crystallogenesis has become a developed science. In fact, such contribution has accelerated the development of protein crystallography, stimulating the study of macromolecular structure and function.展开更多
In this paper, we have proposed a class of ratio-cum-product estimator for estimating population mean of study variable for single phase sampling using multi-auxiliary attributes. The expressions for mean square error...In this paper, we have proposed a class of ratio-cum-product estimator for estimating population mean of study variable for single phase sampling using multi-auxiliary attributes. The expressions for mean square error are derived. An empirical study is given to compare the performance of the estimator with existing estimators. It has been found that the ratio-cum-product estimator using multiple auxiliary attributes is more efficient than mean per unit, product and ratio estimators using one auxiliary attribute, and Product and Ratio estimators using multiple auxiliary attributes in single phase sampling.展开更多
For the issue of evaluation of capability of enterprise agent coalition,an evaluation model based on information fusion and entropy weighting method is presented. The attribute reduction method is utilized to reduce i...For the issue of evaluation of capability of enterprise agent coalition,an evaluation model based on information fusion and entropy weighting method is presented. The attribute reduction method is utilized to reduce indicators of the capability according to the theory of rough set. The new indicator system can be determined. Attribute reduction can also reduce the workload and remove the redundant information,when there are too many indicators or the indicators have strong correlation. The research complexity can be reduced and the efficiency can be improved. Entropy weighting method is used to determine the weights of the remaining indicators,and the importance of indicators is analyzed. The information fusion model based on nearest neighbor method is developed and utilized to evaluate the capability of multiple agent coalitions,compared to cloud evaluation model and D-S evidence method. Simulation results are reasonable and with obvious distinction. Thus they verify the effectiveness and feasibility of the model. The information fusion model can provide more scientific,rational decision support for choosing the best agent coalition,and provide innovative steps for the evaluation process of capability of agent coalitions.展开更多
Miano area is one of the distinct major hydrocarbon producing fields of the Lower Indus basin. Lower Goru is the reservoir strait in this area. The aim of the present study is to exploit the channels reservoirs and ot...Miano area is one of the distinct major hydrocarbon producing fields of the Lower Indus basin. Lower Goru is the reservoir strait in this area. The aim of the present study is to exploit the channels reservoirs and other stratigraphic features in such a terrain where there is always a challenge for the geoscientist to search and exploit the channeled reservoirs. To resolve this issue we have utilized attribute analysis on high resolution 3D-seismic data for the detailed comparative studies for the channels. There are many astonishing features that are identified in the current study, which could not otherwise be easily enhanced with the help of 2D Seismic Data. Seismic attributes such as coherency, frequency (are also appropriate for lithological discrimination), which are sensitive to the channel edges are applied for the channel delineation and their geometrical analysis. Spectral decomposition techniques are also applied for the delineation of channels and to appropriately select the best band for channels identification. Three types of channel geometries are recognized: 1) highly sinuous channel;2) narrow-broad meandering belts;3) moderate to high sinuous channel. NW-SE, N-W trending faults can be helpful to compartmentalize the reservoir. Instantaneous and dominant frequency are more beneficial for further field development based on Gamma Ray logs from nearby drilled wells and dimensional perspectives analysis of the channel reservoir.展开更多
文摘The need for travel demand models is growing worldwide. Obtaining reasonably accurate level of service (LOS) attributes of different travel modes such as travel time and cost representing the performance of transportation system is not a trivial task, especially in growing cities of developing countries. This study investigates the sensitivity of results of a travel mode choice model to different specifications of network-based LOS attributes using a mixed logit model. The study also looks at the possibilities of correcting some of the inaccuracies in network-based LOS attributes. Further, the study also explores the effects of different specifications of LOS data on implied values of time and aggregation forecasting. The findings indicate that the implied values of time are very sensitive to specification of data and model implying that utmost care must be taken if the purpose of the model is to estimate values of time. Models estimated on all specifications of LOS-data perform well in prediction, likely suggesting that the extra expense on developing a more detailed and accurate network models so as to derive more precise LOS attributes is unnecessary for impact analyses of some policies.
基金supported by the National Natural Science Foundation of China(61402260,61473176)Taishan Scholar Project of Shandong Province(TSQN201812092)
文摘Pythagorean fuzzy set(PFS) can provide more flexibility than intuitionistic fuzzy set(IFS) for handling uncertain information, and PFS has been increasingly used in multi-attribute decision making problems. This paper proposes a new multiattribute group decision making method based on Pythagorean uncertain linguistic variable Hamy mean(PULVHM) operator and VIKOR method. Firstly, we define operation rules and a new aggregation operator of Pythagorean uncertain linguistic variable(PULV) and explore some properties of the operator.Secondly, taking the decision makers' hesitation degree into account, a new score function is defined, and we further develop a new group decision making approach integrated with VIKOR method. Finally, an investment example is demonstrated to elaborate the validity of the proposed method. Sensibility analysis and comprehensive comparisons with another two methods are performed to show the stability and advantage of our method.
文摘It has been a dream that theoretical biology can be extensively applied in experimental biology to accelerate the understanding of the sophiscated movements in living organisms. A brave assay and an excellent example were represented by enzymology, in which the well-established physico-chemistry is used to describe, to fit, to predict and to improve enzyme reactions. Before the modern bioinformatics, the developments of the combination of theoretical biology and experimental biology have been mainly limited to various classic formulations. The systematic use of graphic rules by Prof. Kuo-Chen Chou and his co-workers has significantly facilitated to deal with complicated enzyme systems. With the recent fast progress of bioinformatics, prediction of protein structures and various protein attributes have been well established by Chou and co-workers, stimulating the experimental biology. For example, their recent method for predicting protein subcellular localization (one of the important attributes of proteins) has been extensively applied by scientific colleagues, yielding many new results with thousands of citations. The research by Prof. Chou is characterized by introducing novel physical concepts as well as powerful and elegant mathematical methods into important biomedical problems, a focus throughout his career, even when facing enormous difficulties. His efforts in 50 years have greatly helped us to realize the dream to make “theoretical and experimental biology in one”. Prof. Richard Giege is well known for his multi-disciplinary research combining physics, chemistry, enzymology and molecular biology. His major focus of study is on the identity of tRNAs and their interactions with aminoacyl-tRNA synthetases (aaRS), which are of critical importance to the fidelity of protein biosynthesis. He and his colleagues have carried out the first crystallization of a tRNA/aaRS complex, that between tRNAAsp and AspRS from yeast. The determination of the complex structure contributed significantly to under- stand the interaction of protein and RNA. From his fine research, they have also found other biological function of these small RNAs. He has developed in parallel appropriate methods for his research, of which the protein crystallogenesis, a name he has coined, is an excellent example. Now macromolecular crystallogenesis has become a developed science. In fact, such contribution has accelerated the development of protein crystallography, stimulating the study of macromolecular structure and function.
文摘In this paper, we have proposed a class of ratio-cum-product estimator for estimating population mean of study variable for single phase sampling using multi-auxiliary attributes. The expressions for mean square error are derived. An empirical study is given to compare the performance of the estimator with existing estimators. It has been found that the ratio-cum-product estimator using multiple auxiliary attributes is more efficient than mean per unit, product and ratio estimators using one auxiliary attribute, and Product and Ratio estimators using multiple auxiliary attributes in single phase sampling.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61173052)the China Postdoctoral Scinece Foundation(Grant No.2014M561363)
文摘For the issue of evaluation of capability of enterprise agent coalition,an evaluation model based on information fusion and entropy weighting method is presented. The attribute reduction method is utilized to reduce indicators of the capability according to the theory of rough set. The new indicator system can be determined. Attribute reduction can also reduce the workload and remove the redundant information,when there are too many indicators or the indicators have strong correlation. The research complexity can be reduced and the efficiency can be improved. Entropy weighting method is used to determine the weights of the remaining indicators,and the importance of indicators is analyzed. The information fusion model based on nearest neighbor method is developed and utilized to evaluate the capability of multiple agent coalitions,compared to cloud evaluation model and D-S evidence method. Simulation results are reasonable and with obvious distinction. Thus they verify the effectiveness and feasibility of the model. The information fusion model can provide more scientific,rational decision support for choosing the best agent coalition,and provide innovative steps for the evaluation process of capability of agent coalitions.
文摘Miano area is one of the distinct major hydrocarbon producing fields of the Lower Indus basin. Lower Goru is the reservoir strait in this area. The aim of the present study is to exploit the channels reservoirs and other stratigraphic features in such a terrain where there is always a challenge for the geoscientist to search and exploit the channeled reservoirs. To resolve this issue we have utilized attribute analysis on high resolution 3D-seismic data for the detailed comparative studies for the channels. There are many astonishing features that are identified in the current study, which could not otherwise be easily enhanced with the help of 2D Seismic Data. Seismic attributes such as coherency, frequency (are also appropriate for lithological discrimination), which are sensitive to the channel edges are applied for the channel delineation and their geometrical analysis. Spectral decomposition techniques are also applied for the delineation of channels and to appropriately select the best band for channels identification. Three types of channel geometries are recognized: 1) highly sinuous channel;2) narrow-broad meandering belts;3) moderate to high sinuous channel. NW-SE, N-W trending faults can be helpful to compartmentalize the reservoir. Instantaneous and dominant frequency are more beneficial for further field development based on Gamma Ray logs from nearby drilled wells and dimensional perspectives analysis of the channel reservoir.
