Data Visualization and Analysis Tools for Mathematical Modelling 數學建模數據可視化及分析工具
We have developed a suite of interactive data visualization and analysis R Shiny tools for mathematical modelling. All tools are freely available to everyone interested in mathematical modelling. The tools can be accessed below:
我們開發了一系列的數學建模數據可視化及分析 R Shiny 工具。所有工具均免費供對數學建模有興趣的師生使用。工具可以透過以下連結開啟：
If the above links do not work, please use the following alternative link:
如果以上連結有任何問題，請使用以下替代連結： http://mathcal.math.cuhk.edu.hk:3838/ (including all R Shiny tools 包括所有 R Shiny 工具)
Performing linear regression and other customized linear fits based on (x,y) data 根據 (x,y) 數據進行線性迴歸和其他自訂線性擬合
Computing the predicted value at arbitrary x 計算任意點 x 的預測值
Input data format: CSV, XLSX, or TXT file containing the data points (2 columns of data representing x and y values) 輸入數據格式：包含數據點的 CSV、XLSX 或 TXT 檔案（2 列資料代表 x 和 y 值）
Performing linear, quadratic, cubic, polynomial, power, exponential, and logarithmic regression based on (x,y) data 根據 (x,y) 數據進行線性、二次、三次、多項式、冪、指數和對數迴歸
Computing the predicted value at arbitrary x 計算任意點 x 的預測值
Input data format: CSV, XLSX, or TXT file containing the data points (2 columns of data representing x and y values) 輸入數據格式：包含數據點的 CSV、XLSX 或 TXT 檔案（2 列資料代表 x 和 y 值）
Performing linear, quadratic, cubic, polynomial, power, exponential, and logarithmic regression based on time data 根據時間數據進行線性、二次、三次、多項式、冪、指數和對數迴歸
In the best-fit curve calculation, we convert the dates into numbers by introducing a new variable x, where x is the number of days from the earliest date in the dataset. 在最佳擬合曲線的計算中，我們透過引入新變數 x 將日期轉換為數字，其中 x 是由數據集中最早日期起計的天數。
Customizing the data time interval 自訂數據時間段
Fitting multiple time intervals with different models 使用不同的模型擬合多個時間段
Computing the predicted value at arbitrary time 計算在任意時間的預測值
Input data format: CSV, XLSX, or TXT file containing the data points (2 columns of data representing date and value) 輸入數據格式：包含數據點的 CSV、XLSX 或 TXT 檔案（2 列資料代表日期和數值）
The date format can be 輸入時期格式可以為: YYYY-MM-DD, YYYY/MM/DD, DD-MM-YYYY, DD/MM/YYYY, YYYY-MM, YYYY/MM, MM-YYYY, MM/YYYY, or YYYY.
Performing general model fitting based on (x,y) data 根據 (x,y) 數據進行一般曲線擬合
Customizing the form of the fitting function and finding the best-fit parameters 自訂擬合函數的形式並找出最佳系數
Computing the predicted value at arbitrary x 計算任意點 x 的預測值
Input data format: CSV, XLSX, or TXT file containing the data points (2 columns of data representing x and y values) 輸入數據格式：包含數據點的 CSV、XLSX 或 TXT 檔案（2 列資料代表 x 和 y 值）
Interactive visualization of different clustering methods 不同聚類分析方法的互動式視覺化
Covering partitional clustering (K-means, K-medoids), hierarchical clustering (agglomerative, divisive), density-based clustering (DBSCAN), and other clustering methods. 涵蓋劃分式聚類（K-means、K-medoids）、層次聚類（凝聚式、分裂式）、基於密度的聚類（DBSCAN），以及其他聚類方法
Remark: Currently only support 2D data input 備註：現時只支持二維數據輸入
Input data format: CSV, XLSX, or TXT file containing the data points (2 columns of data representing x and y values) 輸入數據格式：包含數據點的 CSV、XLSX 或 TXT 檔案（2 列資料代表 x 和 y 值）
Disclaimer: The results obtained from the above tools are for your reference only and without warranty. For any comments or questions about the tools, please contact us at mathmodel@math.cuhk.edu.hk.
免責聲明：以上工具所獲得的結果僅供參考，不提供任何保證。如對工具有任何意見或問題，請聯絡我們：mathmodel@math.cuhk.edu.hk。
Copyright (c) 2024-2026, Department of Mathematics, The Chinese University of Hong Kong
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
AI-based Tools for Mathematical Modelling 數學建模 AI 工具
