zqr10159 opened a new pull request, #3909:
URL: https://github.com/apache/hertzbeat/pull/3909

   This pull request introduces a new analysis module to the project, focused 
on time series forecasting and preprocessing. It adds a Maven module with its 
own dependencies, implements core algorithms for time series prediction 
(including a robust NLinear model and a lightweight Prophet-inspired model), 
and provides supporting infrastructure for data preprocessing and service 
abstraction.
   
   Key changes include:
   
   **Module Setup and Dependencies**
   - Added a new Maven module `hertzbeat-analysis` with its own `pom.xml`, 
specifying dependencies on core Hertzbeat modules, Spring Boot, and Apache 
Commons Math. Java 17 is set as the source/target version.
   
   **Core Algorithms for Time Series Forecasting**
   - Implemented `NLinearModel`, an industrial-grade robust time series 
forecasting model using ridge regression (L2 regularization) for stability and 
overfitting prevention. Includes logic for flat line detection and fallback 
strategies.
   - Added `TinyProphet`, a lightweight time series forecasting model inspired 
by Prophet, using OLS regression with Fourier features for seasonality and 
trend detection.
   - Created `PredictionResult` as a data class to encapsulate forecast values 
and confidence intervals.
   
   **Data Preprocessing**
   - Added `TimeSeriesPreprocessor` for resampling and interpolating time 
series data, handling missing values and aligning data to fixed time steps for 
model input.
   
   **Service Abstraction and Spring Integration**
   - Defined `AnalysisService` interface for model training and forecasting, 
establishing a contract for future service implementations.
   - Added `AnalysisModule` as a Spring configuration class to enable component 
scanning for the new analysis package.


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