SYSTEMS AND METHODS FOR QUANTIFYING NETWORK GROWTH USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING MODELS

Smart overview of the Invention

The application details a system designed to quantify network growth by leveraging artificial intelligence and machine learning models. It processes data related to consumer characteristics and network services to determine the likelihood of consumers utilizing specific network services. This involves calculating probabilities and predicting utilization states over time, ultimately helping to determine penetration rates and inform strategic actions for network service expansion.

Background

Network services, such as broadband Internet, are increasingly in demand, compelling Internet service providers (ISPs) to expand their infrastructure. However, deploying new technologies like optical fiber involves significant investment and complex decision-making. Accurate forecasting of customer growth is crucial for ISPs to optimize financial outcomes and strategic planning, as traditional methods relying on historical data may not sufficiently capture consumer behavior dynamics.

Prediction System Functionality

The system predicts and quantifies growth opportunities by analyzing consumer data with propensity models. It calculates the probability of consumers adopting network services and tracks utilization states over time. By aggregating these states, the system determines service penetration rates, helping ISPs identify optimal strategies for network deployment while conserving resources by avoiding over- or underestimation of customer utilization.

Components and Modules

The prediction system comprises several modules: a machine learning module for generating propensity models, a state transition module for assigning consumer states, a microsimulation module for predicting state transitions, an aggregation module for compiling data across regions, and a decisioning module for scenario analysis. These components work together to maximize growth opportunities while minimizing costs.

Data Utilization

The system utilizes historical data from various sources to understand consumer decisions regarding network services. It analyzes demographic, property, behavioral, and geographic features to create comprehensive datasets. This analysis helps predict consumer transitions between different service states and adjusts predictions based on factors like workforce availability and market conditions.