FIO-QO3: Fractal Information Ontology for Seismic Risk Detection
Description
FIO-QO3 Global is a physics-based framework for detecting pre-event regimes in seismic catalogs using Fractal Information Ontology (FIO). This repository contains the methodology, source code, and validation results for analyzing seismic activity through the lens of complex systems and information theory.
Core Methodology
The system analyzes the temporal structure of earthquake sequences by identifying "informational compression" and phase transitions in the Earth's crust. It utilizes four key invariants:
b-value (Aki-Utsu): A measure of differential stress accumulation. A significant drop (b < 0.75) signals a shift toward large-scale rupture preparation.
CV (Coefficient of Variation): A measure of temporal intermittency. The convergence CV -> 1 indicates a transition toward a self-organized critical (SOC) state.
Information Entropy: A detector for regime transitions. Decreasing Shannon entropy indicates a focusing of the seismic process.
Seismic Information Deficit (SID): A novel metric (introduced in T15) that measures the deviation from the background informational state.
Validation Results (Japan, JMA Data 2017–2023)
The framework has been rigorously tested using strict temporal train/test splits to prevent data leakage:
Skill Score: 0.08–0.10 (statistically significant improvement).
PR-AUC: Observed 4–5x improvement over stationary Poisson baselines for rare events (M >= 6.5).
Feature Importance: FIO components contribute approximately 50% of the model's predictive power.
Scientific Positioning and Constraints
CRITICAL DISTINCTION: This framework is designed for REGIME DETECTION, not deterministic earthquake prediction.
No Determinism: It provides probabilistic risk stratification, not a "time-location-magnitude" forecast.
Vulnerability Assessment: The system identifies states of elevated seismic vulnerability (pre-event regimes).
Academic Honesty: This work represents an incremental improvement in seismic risk assessment through complex systems physics.
Notes
Notes
All commercial usage, deployment, and sublicensing rights are strictly reserved by the Author, Igor Chechelnitsky. Unauthorized commercial use is prohibited. For commercial licensing inquiries, contact via Facebook. This software is part of the QADMON Canonical Research Framework.
Files
Muhomor2/Fractal-Information-Ontology-and-Multi-Scale-QO3-System-v1.0.0.zip
Files
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Additional details
Related works
- Is supplement to
- Software: https://github.com/Muhomor2/Fractal-Information-Ontology-and-Multi-Scale-QO3-System/tree/v1.0.0 (URL)
Software
- Repository URL
- https://github.com/Muhomor2/Fractal-Information-Ontology-and-Multi-Scale-QO3-System
- Programming language
- Python
References
- Aki, K. (1965). Maximum likelihood estimate of b in the formula log N = a − bM. Bull. Earthq. Res. Inst. 43, 237-239. Bak, P., Tang, C., Wiesenfeld, K. (1987). Self-organized criticality: An explanation of the 1/f noise. Phys. Rev. Lett. 59, 381-384.
- Bak, P., Tang, C., Wiesenfeld, K. (1987). Self-organized criticality: An explanation of the 1/f noise. Phys. Rev. Lett. 59, 381-384.
- Ogata, Y. (1988). Statistical models for earthquake occurrences and residual analysis for point processes. J. Am. Stat. Assoc. 83, 9-27.
- Scholz, C.H. (2015). On the stress dependence of the earthquake b value. Geophys. Res. Lett. 42, 1399-1402.
- Sornette, D. (2006). Critical Phenomena in Natural Sciences. Springer, Berlin.
- Utsu, T. (1965). A method for determining the value of b in a formula log n = a − bM. Geophys. Bull. Hokkaido Univ. 13, 99-103.