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Cosmic acceleration with bulk viscosity in an anisotropic f(R, Lm) background

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Communications in Theoretical Physics 2023年第7期75卷 103-112页

作者： Raja Solanki Bina Patel lakhan v.jaybhaye P K Sahoo Department of Mathematics Birla Institute of Technology and Science-PilaniHyderabad CampusHyderabad-500078India Department of Mathematical Sciences P.D.Patel Institute of Applied SciencesCharotar University of Science and Technology(CHARUSAT)ChangaAnand 388421GujaratIndia

In this article,we investigate the observed cosmic acceleration in the framework of a cosmological f(R,Lm)model dominated by bulk viscous matter in an anisotropic *** consider the locally rotationally symmetric Bianchi type I metric and derive the Friedmann equations that drive the gravitational interactions in f((R,Lm)***,we assume the functional form f(R,Lm)=R/2+Lαm,where a is a free model parameter,and then find the exact solutions of field equations corresponding to our viscous matter dominated *** incorporate the updated H(z)data and the Pantheon data to acquire the best-fit values of parameters of our model by utilizing theχ2 minimization technique along with the Markov Chain Monte Carlo random sampling ***,we present the behavior of physical parameters that describe the Universe’s evolution phase,such as density,effective pressure and EoS parameters,skewness parameter,and the statefinder diagnostic *** find that the energy density indicates expected positive behavior,whereas the negative behavior of bulk viscous pressure contributes to the Universe’s *** effective EoS parameter favors the accelerating phase of the Universe’s ***,the skewness parameter shows the anisotropic nature of spacetime during the entire evolution phase of the ***,from the statefinder diagnostic test,we found that our cosmological f(R,Lm)model lies in the quintessence region,and it behaves like a de-Sitter universe in the far *** analyze different energy conditions in order to test the consistency of the obtained *** find that all energy conditions except strong energy condition(SEC)show positive behavior,while the violation of SEC favors the recently observed acceleration with the transition from decelerated to an accelerated epoch of the Universe’s expansion in the recent past.

关键词： LRS Bianchi type I metric f(R Lm)gravity bulk viscosity skewness parameter equation of state parameter statefinder parameter

Comparison between CBR and CA methods for estimating land use change in Dongguan, China

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Journal of Geographical Sciences 2012年第4期22卷 716-736页

作者： DU Yunyan GE Yong v.Chris lakhan SUN Yeran CAO Feng State Key Laboratory of Resources and Environmental Information System Institute of Geographic Science and Natural Resources ResearchCASBeijing 100101China Department of Earth and Environmental Sciences University of WindsorON N9B 3P4Canada

Many studies on land use change （LUC）, using different approaches and models, have yielded good results. Applications of these methods have revealed both advantages and limitations. However, LUC is a complex problem due to influences of many factors, and variations in policy and natural conditions. Hence, the characteristics and regional suitability of different methods require further research, and comparison of typical approaches is required. Since the late 1980s, CA has been used to simulate urban growth, urban sprawl and land use evolution successfully. Nowadays it is very popular in resolving the LUC estimating problem. Casebased reasoning （CBR）, as an artificial intelligence technology, has also been employed to study LUC by some researchers since the 2000s. More and more researchers used the CBR method in the study of LUC. The CA approach is a mathematical system constructed from many typical simple components, which together are capable of simulating complex behavior, while CBR is a problem-oriented analysis method to solve geographic problems, particularly when the driving mechanisms of geographic processes are not yet understood fully. These two methods were completely different in the LUC research. Thus, in this paper, based on the enhanced CBR model, which is proposed in our previous research （Duet aL 2009）, a comparison between the CBR and CA approaches to assessing LUC is presented. LUC in Dongguan coastal region, China is investigated. Applications of the improved CBR and the cellular automata （CA） to the study area, produce results demonstrating a similarity estimation accuracy of 89% from the improved CBR, and 70.7% accuracy from the CA. From the results, we can see that the accuracies of the CA and CBR approaches are both 〉70%. Although CA method has the distinct advantage in predicting the urban type, CBR method has the obvious tendency in predicting non-urban type. Considering the entire analytical process, the preprocessing workload in CBR is le

关键词： artificial intelligence case-based reasoning land use changes spatial relationship cellular automata Dongguan coastal region, China

Application of rough set-based analysis to extract spatial relationship indicator rules： An example of land use in Pearl River Delta

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Journal of Geographical Sciences 2011年第1期21卷 101-117页

作者： GE Yong CAO Feng DU Yunyan lakhan v. Chris WANG Yingjie LI Deyu State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China Department of Earth and Environmental Sciences University of Windsor ON N9B 3P4 Canada School of Computer & Information Technology of Shanxi University Taiyuan 030006 China

Spatial relations,reflecting the complex association between geographical phenomena and environments,are very important in the solution of geographical issues. Different spatial relations can be expressed by indicators which are useful for the analysis of geographical issues. Urbanization,an important geographical issue,is considered in this paper. The spatial relationship indicators concerning urbanization are expressed with a decision table. Thereafter,the spatial relationship indicator rules are extracted based on the application of rough set theory. The extraction process of spatial relationship indicator rules is illustrated with data from the urban and rural areas of Shenzhen and Hong Kong,located in the Pearl River Delta. Land use vector data of 1995 and 2000 are used. The extracted spatial relationship indicator rules of 1995 are used to identify the urban and rural areas in Zhongshan,Zhuhai and Macao. The identification accuracy is approximately 96.3%. Similar procedures are used to extract the spatial relationship indicator rules of 2000 for the urban and rural areas in Zhongshan,Zhuhai and Macao. An identification accuracy of about 83.6% is obtained.

关键词： rough set theory spatial relations spatial indicator rules land use change