歡迎光臨

 

呂岡玶 Kang-Ping Lu

Email Address: kplu@nutc.edu.tw

 

學歷

美國愛荷華大學統計博士 80,8~83,7

美國愛荷華大學財務金融碩士 79, 6~80, 7

美國愛荷華大學統計精算碩士77, 8~79, 5

國立臺灣師範大學數學系學士 70,8~74,7

 

經歷

國立臺中科技大學應用統計系教授 108,02~

國立臺中科技大學應用統計系副教授 94,8~108,01

私立中國文化大學應用數學系副教授 83, 8~94, 7

台北市立大同國中數學教師 74, 8~77, 7

 

證照

ASA (Associate of the Society of Actuaries)

 

研究

A.    期刋論文

1.          Kang-Ping Lu, Shao-Tung Chang*. (2020) Robust algorithms for multiphase regression models. Applied Mathematical Modelling 77, 1643-1661. SCI, 2018-IF 2.841, 17/105, Mathematics-Interdisciplinary applications.

2.          Kang-Ping Lu, Shao-Tung Chang*. (2020) Robust fuzzy clustering algorithms for change-point regression models. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, 701-725. SCI, 2018 IF-1.286, Computer Science-Artificial intelligence.

3.          Yi-Wen Chang, Kang-Ping Lu, Shao-Tung Chang*. (2020) Cluster validity indices for mixture hazards regression models. Mathematical Biosciences and Engineering 17, 1616-1636. SCI, 2018-IF 1.313, Mathematical & Computational Biology.

4.          Kang-Ping Lu, Shao-Tung Chang*. (2019) Fuzzy maximum likelihood change-point algorithms for identifying the time of shifts in process data. Neural Computing & Application, 31, 2431-2446. SCI, 2018-IF 4.664, 21/133, Computer Science-Artificial intelligence.

5.          Kang-Ping Lu, Shao-Tung Chang*. (2018) A fuzzy classification approach to piecewise regression models. Applied Soft Computing Journal 69, 671-688. SCI, 2018-IF 4.873, 11/106, Computer Science, Interdisciplinary Applications.

6.          Kang-Ping Lu, Shao-Tung Chang*. (2016) Detecting change-points for shifts in mean and variance using fuzzy classification maximum likelihood change-point algorithms. Journal of Computational and Applied Mathematics 308, 447–463. SCI, 5-Year IF 1.413; 2016-IF 1.357; Journal ranking: 63/254 (Q1), Applied Mathematics.

7.          Kang-Ping Lu, Shao-Tung Chang*, & Miin-Shen Yang. (2016) Change-point detection for shifts in control charts using fuzzy shift change-point algorithms. Computers & Industrial Engineering 93, 12–27. SCI, 5-Year IF 2.859, 2016-IF 2.623, Journal ranking: 9/44, (Q1) Engineering, Industrial; 28/104, Computer Science, Interdisciplinary Applications.

8.          Shao-Tung Chang & Kang-Ping Lu*. (2016) Change-point detection for shifts in control charts using EM change-point algorithms. Quality and Reliability Engineering International 32, 889–900 DOI: 10.1002/qre.1800. SCI, 5-year IF 1.573, 2016-IF:1.366; Journal ranking: Engineering, Multidisciplinary: 34/85, Industrial Engineering: 28/44.

9.          Shao-Tung Chang, Kang-Ping Lu, & Miin-Shen Yang*. (2016) Stepwise possibilistic c-regressions. Information Sciences 334, 307-322. SCI, 5-year IF 4.732, 2016-IF 4.832; Journal ranking: 7/146, Computer Science, Information Systems.

10.      Shao-Tung Chang, Kang-Ping Lu, & Miin-Shen Yang*. (2015) Fuzzy Change-Point Algorithms for Regression Models. IEEE Transactions on Fuzzy System 23(6), 2343-2357. SCI, 5-Year IF 7.198, 2015-IF 6.701; Journal ranking: 1/130, Computer Science, Artificial Intelligence; 2/257, Engineering, Electrical & Electronic.

 

B.研討會論文

1.      Kang-Ping Lu, Shao-Tung Chang*. (2019, Jul.) Robust Fitting Regression Models with Change Points to data, The 8th International Conference on Pure and Applied Mathematics (ICPAM 2019), Burssels, Belgium.

2.      Shao-Tung Chang, Kang-Ping Lu*. (2019, Jul.) A Robust Method for Piecewise Regression Models, The 8th International Conference on Pure and Applied Mathematics (ICPAM 2019), Burssels, Belgium.

3.      呂岡玶*, 張少同。 (2019, Jun.) A robust clustering approach for piecewise regression models. 第二十八屆南區統計研討會暨2019中華機率統學年會及學術研討會暨2019 中華資料採礦協會年會及學術研討會; 國立中興大學，台中。

4.      張少同, 呂岡玶*。(2019, Jun.) Robust fitting of change-point regression models. 二十八屆南區統計研討會暨2019 中華機率統學年會及學術研討會暨2019中華資料採礦協會年會及學術研討會;台中, 國立中興大學， 台中。

5.      Shao-Tung Chang, Kang-Ping Lu*. (2018, Aug.) A progressive approach for mixture regressions, Academic Conference on Engineering, IT and Artificial Intelligence, (ACEITAI 2018) Czech Republic, Prague.

6.      Kang-Ping Lu, Shao-Tung Chang*. (2018, Aug.) Fuzzy clustering on change-point regression analysis, Academic Conference on Engineering, IT and Artificial Intelligence, (ACEITAI 2018) Czech Republic, Prague.

7.      Kang-Ping Lu*, Shao-Tung Chang. (2017, Jul.) A fuzzy partition approach for estimating change points. Universal Academic Cluster, International Summer Conference in Hokkaido, Japan.

8.      Shao-Tung Chang, Kang-Ping Lu*. (2017, Jul.) EM algorithms on change-point models. Universal Academic Cluster, International Summer Conference in Hokkaido, Japan.

9.      Kang-Ping Lu*, Shao-Tung Chang. (2017, Apr.) A fuzzy clustering method for change-point estimation.The 4th International Conference on Industrial Engineering and Applications (ICIEA 2017) Nagoya.

10.  Shao-Tung Chang, Kang-Ping Lu*. (2017, Apr.) Apply mixture models to change-point detection. The 4th International Conference on Industrial Engineering and Applications (ICIEA 2017) Nagoya, Japan.

11.  Kang-Ping Lu*, Shao-Tung Chang. (2016, Nov.) Applying data mining methods to investigating students' mathematics achievement and the associated factors. 104年度數學教育學門專題研究計畫成果討論會, 新竹。

12.  Kang-Ping Lu, Shao-Tung Chang*. (2016, Sep.) Applying multilevel mixture modelling to investigating factors affecting mathematics achievement for secondary school students in Taiwan based on TIMSS data. International Symposium on Education and Social Sciences ISESS, Singapore.

13.  呂岡玶, 張少同。 (2015, June) A fuzzy likelihood approach to change-points detection. 第二十四屆南區統計研討會暨2015中華機率統計學會年會及學術研討會, 彰化。

14.  呂岡玶, 張少同 (2015, May) 應用模糊分類法解決教育研究上混合廻歸模型的問題。2015第七屆科技與數學教育國際學術研討會暨數學教學工作坊。台中。

15.  Kang-Ping Lu, Shao-Tung Chang (2014, Dec). A fuzzy clustering approach to change-point regression models. 2014 國際統計學術研討會, 新竹。

16.   Shao-Tung Chang, Kang-Ping Lu* (2014, Dec). A mixture likelihood approach to detect the change-points of mean and variance in a statistical process. 2014 International Statistical Symposium 國際統計學術研討會, 新竹交通大學。

17.  Kang-Ping Lu, Shao-Tung Chang (2014, Nov). A fuzzy clustering approach to locate a mean shift in control charts. 管理學術研討會[國際科技創新與管理], 台中。

18.  呂岡玶, 張少同, 楊敏生 (2014, Aug). Applications of possibilistic clustering method to latent class regression models in educational research. 第十一屆海峽兩岸心理與教育測驗學術研討會, 台中。

19.  呂岡玶、張少同、楊敏生 (2014, May). Possibilistic c-regressions in comparison with fuzzy c-regressions. 2014台灣智慧科技與應用統計學會年會暨研討會, 台北。

20. 張少同,呂岡玶, 楊敏生 (2014, May). An EM approach to change-point regression. 2014台灣科技與應用統計學會年會暨研討會, 台北。

 

C.專書

1.          呂岡玶, 楊佑傑（2014年08月）。初級統計學(增訂二版)（ISBN：9789571459059）（2）。台灣, 台北：三民書局。

2.          呂岡玶, 楊佑傑（2016年08月）。初級統計學: 解開生活中的數字密碼.（ISBN：9789571461878）。台灣, 台北：三民書局。

 

近五年研究計畫

年度

計畫題目

編號及執行期限

補助單位

108

探究線性剖面監控的穩健法

MOST 108-2118-M-025-001 –

108/08/01 ∼ 109/07/31

科技部

107

隱藏類別及擴展的分群概似法於迴歸模型及製程剖面之改變點及參數的估計

MOST 107-2118-M-025-002 –

107/08/01 ∼ 108/07/31

科技部

106

混合模型於廻歸模型改變點之檢測及其於製程剖面監控之應用

MOST 106-2118-M-025-001

106/08/01~107/07/31

科技部

105

分群最大概似擴展式及其於管制圖改變點偵測的應用

MOST 105-2118-M-025-002

105/08/01~106/07/31

科技部

104

應用資料探勘方法研究學生數學成就及其相關因素

MOST 104-2511-S-025-003

104/11/01~105/10/31

科技部