IT Tools for Mathematical Modelling 數學建模IT工具
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:
https://mathmodelcuhk.shinyapps.io/find-what-fit/ (Find What Fits)
https://mathmodelcuhk.shinyapps.io/linear-regression/ (Linear Regression)
https://mathmodelcuhk.shinyapps.io/non-linear-regression-xy/ (Nonlinear Regression for XY data)
https://mathmodelcuhk.shinyapps.io/non-linear-regression/ (Nonlinear Regression for time data)
https://mathmodelcuhk.shinyapps.io/multi-regression/ (Multi-Regression)
https://mathmodelcuhk.shinyapps.io/curve-fitting/ (Curve Fitting)
If the above links do not work, please use the following link:
http://mathcal.math.cuhk.edu.hk:3838/ (including all R Shiny tools)
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Exploring various definitions of “best-fit” line 探索「最佳擬合」線的各種定義
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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
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Computing the predicted value at arbitrary x 計算任意點 x 的預測值
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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）
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Sample data file 參考數據檔案: [data_LR.csv]
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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
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Computing the predicted value at arbitrary x 計算任意點 x 的預測值
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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）
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Sample data file 參考數據檔案: [data_LR.csv]
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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
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Customizing the data time interval 自訂數據時間段
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Fitting multiple time intervals with different models 使用不同的模型擬合多個時間段
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Computing the predicted value at arbitrary time 計算在任意時間的預測值
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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）
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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.
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Sample data file 參考數據檔案: [data_NLR.csv]
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Performing multiple linear regression 進行多元線性迴歸
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Input data format: CSV, XLSX, or TXT file containing the data points (at least 2 columns of data) 輸入數據格式：包含數據點的 CSV、XLSX 或 TXT 檔案（最少 2 列資料）
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Sample data file 參考數據檔案: [data_MLR.csv]
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Performing data filtering and more advanced model fitting 進行數據過濾和更進階的模型擬合
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.
Copyright (c) 2024-2025, 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
First-ChatGPT-Then-Solve (FCTS) strategy
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Understanding problem background 了解問題背景
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Identifying relevant factors 找出相關因素
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Locating datasets 找尋數據集
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... and more!
Freely available AI tools 免費AI工具
Other useful IT tools 其他有用IT工具
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