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  • About Us
    • About CRAIL
    • Core Objectives
    • Research Areas
    • Contact Us
  • Our Methods
    • Causal Modeling
    • Intervention Experiments
    • Prediction&Optimization
  • Research Structure
    • Causal Discovery
    • Causal Inference
    • Counterfactual Simulation
    • Intervention Experiments
    • Feedback & Optimization
  • Application Scenarios
    • Healthcare & Medicine
    • Economics & Public Policy
    • Career Development
    • Personal Legal Risk
  • More
    • Home
    • About Us
      • About CRAIL
      • Core Objectives
      • Research Areas
      • Contact Us
    • Our Methods
      • Causal Modeling
      • Intervention Experiments
      • Prediction&Optimization
    • Research Structure
      • Causal Discovery
      • Causal Inference
      • Counterfactual Simulation
      • Intervention Experiments
      • Feedback & Optimization
    • Application Scenarios
      • Healthcare & Medicine
      • Economics & Public Policy
      • Career Development
      • Personal Legal Risk
  • Home
  • About Us
    • About CRAIL
    • Core Objectives
    • Research Areas
    • Contact Us
  • Our Methods
    • Causal Modeling
    • Intervention Experiments
    • Prediction&Optimization
  • Research Structure
    • Causal Discovery
    • Causal Inference
    • Counterfactual Simulation
    • Intervention Experiments
    • Feedback & Optimization
  • Application Scenarios
    • Healthcare & Medicine
    • Economics & Public Policy
    • Career Development
    • Personal Legal Risk

The Prediction by Esotericism,Xuanxue or Mysticism

In the cultures of many ethnic groups,Metaphysics and Mysticism are regarded as wise methods of prediction. Examples include the Five Elements and Eight Trigrams,Zi Wei Dou Shu,and Physiognomy in the east,as well as Astrology and Tarot Cards in the west .Throught history,there have been a mumber of renowned figures.

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Forecasting Future Outcomes

Statistical Models : Linear regression, Bayesian inference,time series models (ARIMA, Prophet);

Machine Learning : Decision trees, neural networks, deep learning;

Causal Inference : Structural causal models (SCM), counterfactual reasoning;

Simulation : Monte Carlo methods, agent-based modeling;

Finding the Best Solution

Linear & Nonlinear Optimization : Used in resource allocation and logistics;

Convex & Non-Convex Optimization : Essential for AI and machine learning models;

Combinatorial Optimization : Applied in scheduling,routing, and game theory;

Reinforcement Learning : Optimizing long-term rewards in dynamic environments;

Integration of Prediction and Optimization

Precicting Customer Demand+Optimizing  ;

Forecasting Traffic Patterns + Optimizing Transportation Routes;

Estimating Disease Spread + Allocating Medical Resources Efficiently;

Predicting Market Trends + Optimizing Investment Strategies;

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