Enhancing intelligence source performance management through two-stage stochastic programming and machine learning techniques

The findings demonstrated that scenario-based probabilistic planning offers significant advantages over static heuristics in managing uncertainty in HUMINT operations. While the simulation results are promising, validation through field data is required before operational deployment.

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Publication Details

Journal
Frontiers in Big Data
Published
2025-09-22
DOI
https://doi.org/10.3389/fdata.2025.1640539
Primary Topic
Machine Learning and Data Classification
Type
article
Field-Weighted Citation Impact
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article

Enhancing intelligence source performance management through two-stage stochastic programming and machine learning techniques

Lucas Wafula Wekesa, Stephen Korir
Frontiers in Big Data
Machine Learning and Data Classification
article

Enhancing intelligence source performance management through two-stage stochastic programming and machine learning techniques

Lucas Wafula Wekesa, Stephen Korir
article en

Abstract

The findings demonstrated that scenario-based probabilistic planning offers significant advantages over static heuristics in managing uncertainty in HUMINT operations. While the simulation results are promising, validation through field data is required before operational deployment.

Frontiers in Big DataVol. 8
Strathmore University (KE)
Openalex Percentile: Top 86%
Machine Learning and Data Classification
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Enhancing intelligence source performance management through two-stage stochastic programming and machine learning techniques — Lucas Wafula Wekesa, Stephen Korir · Frontiers in Big Data (2025) | TGRS Research Map | TGRS