4+ years of extensive experience in statistics, data analysis, hydrology, climate change and programming, laying a good professional quality. Previous a project manager at evaluating the effect of climate change in Taiwan. Participated in two civil and water related international seminars and two domestic seminars in the form of posters. Published a journal in Taiwan Mining. Looking forward to applying the knowledge and experience I learned during my master's degree to solving practical problems related to human health and promoting public health.
Taichung,TW
Title of Thesis: The hydrological characteristics of Hehuan Mountain watershed and impact assessment of climate variation
Advisor: Kuo-Chin Hsu Ph.D
Resourceful, flexible, fast-learner, self-starter
Writing, reading, stock, minimalism, fitness
I have joined 2017 AECOM summer intern project, hired in ENV-RE department for 6 weeks. In the last week, my team used the district analysis to coordinate with soil and water improvement regulations, redesign the old camp into a smart elder health care center. Finally, we won the second place.
We tried to apply SWAT model in this article and then we got the distribution of the water components in Hehuan Mountain. On the other hand, we adopted IPCC AR4 as scenario simulation to assess the influence of climate change in the near future.
I brought my research to 2018 SWAT conference. In this conference, my topic was highly recognized. However, IPCC AR4 was not the newest climate change scenario, so I was suggested by the masters to adopt IPCC AR5 as new direction. Also, I got some new ideas by reading other works from this conference.
In this conference, I proposed that a data-based model could be a surrogate model of a physical-based model under the fractal behavior of input data. This idea was novel and showed a new possibility of modeling hydrological problem.
In this conference, we were asked to give a short introduction about our poster. This is a new policy and we were only informed the day before the presentation. My key contribution is to propose a easily used surrogate model that can be used to replace physical-based model that require detailed information when fractal behavior is observed in the input data.
Big data - ANN, DT, Cluster
In the class - Data Mining ( J. B. Tsai), I used use five different US stock market data to train the neural network parameters and analyze the price of TSMC. These five US stocks are Brent, NASDAQ, Dow Jones, S&P 500 and SOX. The data length is five years which is from 2013/10/14~2018/10/8. Decision tree and cluster also used to choose the vital variables. Applying ANN technology to prediction, the accuracy rate is up to 56%.
4+ years of extensive experience in statistics, data analysis, hydrology, climate change and programming, laying a good professional quality. Previous a project manager at evaluating the effect of climate change in Taiwan. Participated in two civil and water related international seminars and two domestic seminars in the form of posters. Published a journal in Taiwan Mining. Looking forward to applying the knowledge and experience I learned during my master's degree to solving practical problems related to human health and promoting public health.
Taichung,TW
Title of Thesis: The hydrological characteristics of Hehuan Mountain watershed and impact assessment of climate variation
Advisor: Kuo-Chin Hsu Ph.D
Resourceful, flexible, fast-learner, self-starter
Writing, reading, stock, minimalism, fitness
I have joined 2017 AECOM summer intern project, hired in ENV-RE department for 6 weeks. In the last week, my team used the district analysis to coordinate with soil and water improvement regulations, redesign the old camp into a smart elder health care center. Finally, we won the second place.
We tried to apply SWAT model in this article and then we got the distribution of the water components in Hehuan Mountain. On the other hand, we adopted IPCC AR4 as scenario simulation to assess the influence of climate change in the near future.
I brought my research to 2018 SWAT conference. In this conference, my topic was highly recognized. However, IPCC AR4 was not the newest climate change scenario, so I was suggested by the masters to adopt IPCC AR5 as new direction. Also, I got some new ideas by reading other works from this conference.
In this conference, I proposed that a data-based model could be a surrogate model of a physical-based model under the fractal behavior of input data. This idea was novel and showed a new possibility of modeling hydrological problem.
In this conference, we were asked to give a short introduction about our poster. This is a new policy and we were only informed the day before the presentation. My key contribution is to propose a easily used surrogate model that can be used to replace physical-based model that require detailed information when fractal behavior is observed in the input data.
Big data - ANN, DT, Cluster
In the class - Data Mining ( J. B. Tsai), I used use five different US stock market data to train the neural network parameters and analyze the price of TSMC. These five US stocks are Brent, NASDAQ, Dow Jones, S&P 500 and SOX. The data length is five years which is from 2013/10/14~2018/10/8. Decision tree and cluster also used to choose the vital variables. Applying ANN technology to prediction, the accuracy rate is up to 56%.