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Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI)

Authors: Eoin M. Kenny; E. Ruelle; Anne Geoghegan; Laurence Shalloo; Micheál O’Leary; Michael O'Donovan; Mark T. Keane;

Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI)

Abstract

Smart agriculture has emerged as a rich application domain for AI-driven decision support systems (DSS) that support sustainable and responsible agriculture, by improving resource-utilization through better on-farm, management decisions. However, smart agriculture’s promise is often challenged by the high barriers to user adoption. This paper develops a case-based reasoning (CBR) system called PBI-CBR to predict grass growth for dairy farmers, that combines predictive accuracy and explanation capabilities designed to improve user adoption. The system provides post-hoc, personalized explanation-by-example for its predictions, by using explanatory cases from the same farm or county. A key novelty of PBI-CBR is its use of Bayesian methods for case exclusion in this regression domain. Experiments report the tradeoff that occurs between predictive accuracy and explanatory adequacy for different parametric variants of PBI-CBR, and how updating Bayesian priors each year reduces error.

Subjects by Vocabulary

Microsoft Academic Graph classification: Decision support system Computer science Bayesian probability Novelty Recommender system Domain (software engineering) Risk analysis (engineering) Application domain Case-based reasoning Dairy farming

32 references, page 1 of 4

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    10
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
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