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Accelerating and Predicting Map Projections with CUDA and MLP

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2018, Master of Science, Ohio State University, Computer Science and Engineering.
We provide a precise mathematical definition of map distortion, and introduce three strategies for finding the best oblique map projections, having the same distortion properties as their normal aspect counterparts on earth regions, that have minimal distortion for certain specific regions of the earth (namely, regions whose boundary consists of one or two parallels of latitude). We use heap map to visualize the distortion of several unusually shaped countries under particular oblique projection applying our strategies, and then optimize the time efficiency of original sequential executed programs with CUDA, a GPU parallel computation method, impressively.
Han-wei Shen (Advisor)
yusu Wang (Committee Member)
73 p.

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Citations

  • Zhang, J. (2018). Accelerating and Predicting Map Projections with CUDA and MLP [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523394255002174

    APA Style (7th edition)

  • Zhang, Jiaqi. Accelerating and Predicting Map Projections with CUDA and MLP. 2018. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1523394255002174.

    MLA Style (8th edition)

  • Zhang, Jiaqi. "Accelerating and Predicting Map Projections with CUDA and MLP." Master's thesis, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523394255002174

    Chicago Manual of Style (17th edition)