Abstract: An improved parcel growth prediction system that uses parcel data, population data, and artificial intelligence to predict the growth of a geographic area at a micro level (e.g., a real estate parcel level) is described herein. For example, the improved parcel growth prediction system may generate a graph model and apply the graph model as an input to an artificial intelligence model to predict the likelihood that a particular parcel may be developed some time in the future. Ultimately, implementing the improved parcel growth prediction system described herein may lead to more precise placements of infrastructure projects and/or to infrastructure projects that more precisely support the needs of the population of a geographic area as time passes.

Abstract: Systems and methods for property valuation using automated valuation models are described herein, which involve a complex series of workflows for data processing, automated valuation modeling, and error detection—each of which are capable of leveraging machine learning algorithms/techniques and can be combined and operated together in a specific manner in order to improve data availability and data quality, improve the accuracy of generated property value estimates, improve the performance of the models over time, and allow the property value estimation to be adapted to various use cases. Estimation of property value may involve an ensemble model which reconciles the outputs of different sub-models based on a use case, with the sub-models using different approaches that have their own strengths and weaknesses.

Abstract: Systems and methods for property valuation using automated valuation models are described herein, which involve a complex series of workflows for data processing, automated valuation modeling, and error detection—each of which are capable of leveraging machine learning algorithms/techniques and can be combined and operated together in a specific manner in order to improve data availability and data quality, improve the accuracy of generated property value estimates, improve the performance of the models over time, and allow the property value estimation to be adapted to various use cases. Estimation of property value may involve an ensemble model which reconciles the outputs of different sub-models based on a use case, with the sub-models using different approaches that have their own strengths and weaknesses.