@article{scholars5348,
            note = {cited By 0; Conference of 3rd International Conference on Green Buildings Technologies and Materials, GBTM 2013 ; Conference Date: 21 December 2013 Through 22 December 2013; Conference Code:105356},
          volume = {935},
             doi = {10.4028/www.scientific.net/AMR.935.159},
         address = {Kuala Lumpur},
           title = {Extreme value analysis and joint densities of wind directionality, wind speed and wave height for Malaysian waters},
            year = {2014},
         journal = {Advanced Materials Research},
       publisher = {Trans Tech Publications},
           pages = {159--162},
        abstract = {Prediction of extreme environmental loadings is crucial in the design of offshore platforms. Combinations of independent 100-year loadings are usually used assuming that it will bring the maximum value that is suitable for the design. It is rather impossible for such independent combinations to occur at the same time. Addressing this issue requires approaches in two methods. The first would be to find the probabilities of joint effect of these parameters, while the second would be to forecast the extreme value of each parameter. Joint densities and extreme value analysis have become available due to significant advancements in fluid dynamics and computer science. By using the combination of these two techniques, the actual loading of wind and wave can be obtained, leading to optimum and robust design. {\^A}{\copyright} (2014) Trans Tech Publications, Switzerland.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901508722&doi=10.4028\%2fwww.scientific.net\%2fAMR.935.159&partnerID=40&md5=ca535c5efc38fd60ad9a94440fe5e248},
        keywords = {Drilling platforms; Offshore structures; Product design; Value engineering; Water waves; Wind, Extreme value; Joint densities; Mean return interval; Wave heights; Wind speed, Loading},
            isbn = {9783038350828},
          author = {Termizi, W. S. A. and Liew, M. S.},
            issn = {10226680}
}