PATENT CLAIM ANALYSIS

Application Number: 16101302
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["703", "006000"]

Abstract:
A multi-step iterative process for simulating complex agricultural situations where limited sets of data are available for such problems first predicts an outcome for each situation in a particular dataset, using initial assumptions of an applied primary model. The process then uses the errors across these situations to identify where opportunities exist among relevant predictive variables for the model to make changes to a response to such predictor variables to reduce the errors when averaged across all situations. The process then develops a correction model to identify adjustments based on combinations of the predictive variables, and applies the adjustments to the primary model to induce an altered outcome.

Claim (Index 11):
A method for simulating complex agricultural processes, comprising:\n ingesting, as input data, one or more of weather conditions data, soil conditions data, crop and soil properties data, and process-specific metadata over a period of time, the input data relative to an agricultural process; modeling the input data in a plurality of data processing modules within a computing environment in which the plurality of data processing modules are executed in conjunction with at least one processor, the data processing modules configured to simulate an agricultural process using available datasets, by:\n developing a primary model for simulating the agricultural process, the agricultural process dependent upon predictive variables derived from the input data relative to the agricultural process, \n calculating errors in the primary model using one or more validating observations related to the agricultural process during the period of time, \n developing a correction model that uses analogous predictive variables as in the primary model, and which identifies opportunities for adjustments to an output of the primary model, from one or more combinations of the predictive variables impacting an outcome of the primary model, to yield an overall reduction in the errors of the primary model, \n applying the adjustments as identified by the correction model to the outputs of primary model to induce an altered response from the primary model to reduce overall errors in prior simulations of the agricultural process; and \n iteratively repeating an interoperation of the primary model and the correction model until the errors in the primary model reach an apparent minimum.

Metadata:
- Claim Count in Document: 80.0
- Percentile: 96.0
- Lexical Diversity: 1.63768
- Patent Class: 703.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14853593', '15187963', '14603383', '14463111', '15883017']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2661041039206363
- 35 USC 102 Novelty (BERT): 0.4748484589536696
- Combined Prediction Score: 0.2869785394239396
- Mean Citation Score: 216.523014
- Max Citation Score: 222.74457
- Similarity Product: 197.4572065319878

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test