1. EXECUTIVE SUMMARY
2. MARKET SNAPSHOT
2.1. Market Overview
2.2. Market Definition
2.3. Scope of the Study
2.4. Market Segmentation
3. BUSINESS LANDSCAPE
3.1. Market Drivers
3.2. Market Restraints
3.3. Market Opportunities
3.4. Porter's Five Forces Analysis
3.5. Industry Value Chain Analysis
3.6. Policies and Regulations
3.7. Strategic Recommendations
4. TECHNOLOGICAL OUTLOOK
5. GERMANY ARTIFICIAL INTELLIGENCE (AI) IN WEATHER PREDICTION MARKET BY TECHNOLOGY
5.1. Introduction
5.2. Machine Learning
5.3. Deep Learning
5.4. Others
6. GERMANY ARTIFICIAL INTELLIGENCE (AI) IN WEATHER PREDICTION MARKET BY SERVICES
6.1. Introduction
6.2. Weather Forecasting
6.3. Climate Modeling
6.4. Severe Weather Prediction
6.5. Others
7. GERMANY ARTIFICIAL INTELLIGENCE (AI) IN WEATHER PREDICTION MARKET BY END-USER
7.1. Introduction
7.2. Aviation
7.3. Marine
7.4. Agriculture
7.5. Energy and Utilities
7.6. Transportation and Logistics
7.7. Others
8. COMPETITIVE ENVIRONMENT AND ANALYSIS
8.1. Major Players and Strategy Analysis
8.2. Market Share Analysis
8.3. Mergers, Acquisitions, Agreements, and Collaborations
8.4. Competitive Dashboard
9. COMPANY PROFILES
9.1. Meteomatics
9.2. MeteoIQ
9.3. MeteoGroup Germany
9.4. DWD (Deutscher Wetterdienst)
9.5. ICON Weather Model
9.6. WetterOnline
9.7. Nowcast
9.8. Ubimet
9.9. 4cast
9.10. Infineon
10. APPENDIX
10.1. Currency
10.2. Assumptions
10.3. Base and Forecast Years Timeline
10.4. Key benefits for the stakeholders
10.5. Research Methodology
10.6. Abbreviations
LIST OF FIGURES
LIST OF TABLES