The ordered weighted geometric averaging(OWGA) operator is extended to accommodate uncertain conditions where all input arguments take the forms of interval numbers. First, a possibility degree formula for the compa...The ordered weighted geometric averaging(OWGA) operator is extended to accommodate uncertain conditions where all input arguments take the forms of interval numbers. First, a possibility degree formula for the comparison between interval numbers is introduced. It is proved that the introduced formula is equivalent to the existing formulae, and also some desired properties of the possibility degree is presented. Secondly, the uncertain OWGA operator is investigated in which the associated weighting parameters cannot be specified, but value ranges can be obtained and the associated aggregated values of an uncertain OWGA operator are known. A linear objective-programming model is established; by solving this model, the associated weights vector of an uncertain OWGA operator can be determined, and also the estimated aggregated values of the alternatives can be obtained. Then the alternatives can be ranked by the comparison of the estimated aggregated values using the possibility degree formula. Finally, a numerical example is given to show the feasibility and effectiveness of the developed method.展开更多
Based on the quantifier guided method,an ordered weighted averaging(OWA)weights generating method under given orness level with regular increasing monotone(RIM)quantifiers is proposed.Then the RIM quantifier based OWA...Based on the quantifier guided method,an ordered weighted averaging(OWA)weights generating method under given orness level with regular increasing monotone(RIM)quantifiers is proposed.Then the RIM quantifier based OWA weights generating method is modified to make the generated weights be monotonic,which can be used to express the decision maker's consistent preference information.Finally,both of these weights generating methods are extended to their generic forms,so that they can generate the OWA weights for any ordinary elements set with any given aggregated value.展开更多
To improve the applicability of the global pressure and temperature 2 wet(GPT2w)model in estimating the weighted mean temperature in China and adjacent areas,the error compensation technology based on the neural netwo...To improve the applicability of the global pressure and temperature 2 wet(GPT2w)model in estimating the weighted mean temperature in China and adjacent areas,the error compensation technology based on the neural network was proposed,and a total of 374800 meteorological profiles measured from 2006 to 2015 of 100 radiosonde stations distributed in China and adjacent areas were used to establish an enhanced empirical model for estimating the weighted mean temperature in this region.The data from 2016 to 2018 of the remaining 92 stations in this region was used to test the performance of the proposed model.Results show that the proposed model is about 14.9%better than the GPT2w model and about 7.6%better than the Bevis model with measured surface temperature in accuracy.The performance of the proposed model is significantly improved compared with the GPT2w model not only at different height ranges,but also in different months throughout the year.Moreover,the accuracy of the weighted mean temperature estimation is greatly improved in the northwestern region of China where the radiosonde stations are very rarely distributed.The proposed model shows a great application potential in the nationwide real-time ground-based global navigation satellite system(GNSS)water vapor remote sensing.展开更多
Based on the advantages and disadvantages of the standard median filter and the standard wean filter, a new Adaptive Weighted Mean Filter(AWFM) was proposed in this paper. The filter window's size of every pixel wa...Based on the advantages and disadvantages of the standard median filter and the standard wean filter, a new Adaptive Weighted Mean Filter(AWFM) was proposed in this paper. The filter window's size of every pixel was adaptively adjusted. Then the suspidons noise points were examined by certain rules. After that, the authors calculate the weighting factors of the pixels by weighting function which was canstructed according to the differences between their gray values and the median value of all elements in the window. Finally they use the weighted average of gray values to substitute the gray value of the central pixel in the window. The results indicate that this filtering method is not only effective for impulse noise like median filter, but also better than the standard median filters. Compared with conventional filter, this filter methed can effectivdy suppress the mixture noise of images, and protect image's details well.展开更多
The importance of water vapor in research of global climate change and weather forecast cannot be over emphasized; therefore substantial efforts have been made in exploring the optimal methods to measure water vapor. ...The importance of water vapor in research of global climate change and weather forecast cannot be over emphasized; therefore substantial efforts have been made in exploring the optimal methods to measure water vapor. It is well-established that with a conversion factor, zenith wet delays can be mapped onto precipitable water vapor (PWV). However, the determination of the exact conversion factor depends heavily on the accurate calculation of a key variable, weighted mean temperature of the trop- osphere (Tin). AS a critical parameter in Global Positioning System (GPS) meteorology, Tm has recently been modeled into a global grid known as GWMT. The GWMT model only requires the location and the day of year to calculate Tm. Despite the advantages that the GWMT model offers, anomalies still exist in oceanic areas due to low sampling resolution. In this study, we refine the GWMT model by incorporating the global Tm grid from Global Geodetic Observing System (GGOS) and obtain an improved model, GWMT-G. The results indicate that the GWMT-G model successfully addresses the anomaly in oceanic areas in the GWMT model and significantly improves the accuracy of Tm in other regions.展开更多
基金The Technological Innovation Foundation of NanjingForestry University(No.163060033).
文摘The ordered weighted geometric averaging(OWGA) operator is extended to accommodate uncertain conditions where all input arguments take the forms of interval numbers. First, a possibility degree formula for the comparison between interval numbers is introduced. It is proved that the introduced formula is equivalent to the existing formulae, and also some desired properties of the possibility degree is presented. Secondly, the uncertain OWGA operator is investigated in which the associated weighting parameters cannot be specified, but value ranges can be obtained and the associated aggregated values of an uncertain OWGA operator are known. A linear objective-programming model is established; by solving this model, the associated weights vector of an uncertain OWGA operator can be determined, and also the estimated aggregated values of the alternatives can be obtained. Then the alternatives can be ranked by the comparison of the estimated aggregated values using the possibility degree formula. Finally, a numerical example is given to show the feasibility and effectiveness of the developed method.
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘Based on the quantifier guided method,an ordered weighted averaging(OWA)weights generating method under given orness level with regular increasing monotone(RIM)quantifiers is proposed.Then the RIM quantifier based OWA weights generating method is modified to make the generated weights be monotonic,which can be used to express the decision maker's consistent preference information.Finally,both of these weights generating methods are extended to their generic forms,so that they can generate the OWA weights for any ordinary elements set with any given aggregated value.
基金The National Natural Science Foundation of China(No.41574022)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX17_0150).
文摘To improve the applicability of the global pressure and temperature 2 wet(GPT2w)model in estimating the weighted mean temperature in China and adjacent areas,the error compensation technology based on the neural network was proposed,and a total of 374800 meteorological profiles measured from 2006 to 2015 of 100 radiosonde stations distributed in China and adjacent areas were used to establish an enhanced empirical model for estimating the weighted mean temperature in this region.The data from 2016 to 2018 of the remaining 92 stations in this region was used to test the performance of the proposed model.Results show that the proposed model is about 14.9%better than the GPT2w model and about 7.6%better than the Bevis model with measured surface temperature in accuracy.The performance of the proposed model is significantly improved compared with the GPT2w model not only at different height ranges,but also in different months throughout the year.Moreover,the accuracy of the weighted mean temperature estimation is greatly improved in the northwestern region of China where the radiosonde stations are very rarely distributed.The proposed model shows a great application potential in the nationwide real-time ground-based global navigation satellite system(GNSS)water vapor remote sensing.
基金supported by the University Independent innovation program of Jinan(No.200906005)the National Natural Science Foundation of Shandong Province(No.Y2008G31)
文摘Based on the advantages and disadvantages of the standard median filter and the standard wean filter, a new Adaptive Weighted Mean Filter(AWFM) was proposed in this paper. The filter window's size of every pixel was adaptively adjusted. Then the suspidons noise points were examined by certain rules. After that, the authors calculate the weighting factors of the pixels by weighting function which was canstructed according to the differences between their gray values and the median value of all elements in the window. Finally they use the weighted average of gray values to substitute the gray value of the central pixel in the window. The results indicate that this filtering method is not only effective for impulse noise like median filter, but also better than the standard median filters. Compared with conventional filter, this filter methed can effectivdy suppress the mixture noise of images, and protect image's details well.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41174012, 41274022)the National High Technology Research and Development Program of China (Grant No. 2013AA122502)the Open Foundation of Key Laboratory of Precise Engineering and Industry Surveying of National Administration of Surveying, Mapping and Geoinformation (Grant Nos. PF2012-14, PF2013-12)
文摘The importance of water vapor in research of global climate change and weather forecast cannot be over emphasized; therefore substantial efforts have been made in exploring the optimal methods to measure water vapor. It is well-established that with a conversion factor, zenith wet delays can be mapped onto precipitable water vapor (PWV). However, the determination of the exact conversion factor depends heavily on the accurate calculation of a key variable, weighted mean temperature of the trop- osphere (Tin). AS a critical parameter in Global Positioning System (GPS) meteorology, Tm has recently been modeled into a global grid known as GWMT. The GWMT model only requires the location and the day of year to calculate Tm. Despite the advantages that the GWMT model offers, anomalies still exist in oceanic areas due to low sampling resolution. In this study, we refine the GWMT model by incorporating the global Tm grid from Global Geodetic Observing System (GGOS) and obtain an improved model, GWMT-G. The results indicate that the GWMT-G model successfully addresses the anomaly in oceanic areas in the GWMT model and significantly improves the accuracy of Tm in other regions.