Matches in SemOpenAlex for { <https://semopenalex.org/work/W2299391211> ?p ?o ?g. }
Showing items 1 to 55 of
55
with 100 items per page.
- W2299391211 abstract "With increasing prevalence of Wireless Sensor Networks (WSNs) in agriculture and hydrology, there exists an opportunity for providing a technologically viable solution for the conservation of already scarce fresh water resources. In this thesis, a novel framework is proposed for enabling a proactive management of agricultural drainage and nutrient losses at farm scale where complex models are replaced by in-situ sensing, communication and low complexity predictive models suited to an autonomous operation. This is achieved through the development of the proposed Water Quality Management using Collaborative Monitoring (WQMCM) framework that combines local farm-scale WSNs through an information sharing mechanism. Under the proposed WQMCM framework, various functional modules are developed to demonstrate the overall mechanism: (1) neighbour learning and linking, (2) low-complexity predictive models for drainage dynamics, (3) low-complexity predictive model for nitrate losses, and (4) decision support model for drainage and nitrate reusability. The predictive models for drainage dynamics and nitrate losses are developed by abstracting model complexity from the traditional models (National Resource Conservation Method (NRCS) and De-Nitrification-DeComposition (DNDC) model respectively). Machine learning algorithms such as M5 decision tree, multiple linear regression, artificial neural networks, C4.5, and Naive Bayes are used in this thesis. For the predictive models, validation is performed using 12-month long event dataset from a sub-catchment in Ireland. Overall, the following contributions are achieved: (1) framework architecture and implementation for WQMCM for a networked catchment, (2) model development for low-complexity drainage discharge dynamics and nitrate losses by reducing number of model parameters to less than 50%, (3) validation of the predictive models for drainage and nitrate losses using M5 tree algorithm and measured catchment data. Additionally modelling results are compared with existing models and further tested with using other learning algorithms, and (4) development of a decision support model, based on Naive Bayes algorithm, for suggesting reusability of drainage and nitrate losses." @default.
- W2299391211 created "2016-06-24" @default.
- W2299391211 creator A5064264477 @default.
- W2299391211 date "2015-06-01" @default.
- W2299391211 modified "2023-09-23" @default.
- W2299391211 title "Enabling proactive agricultural drainage reuse for improved water quality through collaborative networks and low-complexity data-driven modelling" @default.
- W2299391211 hasPublicationYear "2015" @default.
- W2299391211 type Work @default.
- W2299391211 sameAs 2299391211 @default.
- W2299391211 citedByCount "0" @default.
- W2299391211 crossrefType "dissertation" @default.
- W2299391211 hasAuthorship W2299391211A5064264477 @default.
- W2299391211 hasConcept C119857082 @default.
- W2299391211 hasConcept C18903297 @default.
- W2299391211 hasConcept C2780797713 @default.
- W2299391211 hasConcept C39432304 @default.
- W2299391211 hasConcept C41008148 @default.
- W2299391211 hasConcept C67592535 @default.
- W2299391211 hasConcept C84525736 @default.
- W2299391211 hasConcept C86803240 @default.
- W2299391211 hasConceptScore W2299391211C119857082 @default.
- W2299391211 hasConceptScore W2299391211C18903297 @default.
- W2299391211 hasConceptScore W2299391211C2780797713 @default.
- W2299391211 hasConceptScore W2299391211C39432304 @default.
- W2299391211 hasConceptScore W2299391211C41008148 @default.
- W2299391211 hasConceptScore W2299391211C67592535 @default.
- W2299391211 hasConceptScore W2299391211C84525736 @default.
- W2299391211 hasConceptScore W2299391211C86803240 @default.
- W2299391211 hasLocation W22993912111 @default.
- W2299391211 hasOpenAccess W2299391211 @default.
- W2299391211 hasPrimaryLocation W22993912111 @default.
- W2299391211 hasRelatedWork W1492727258 @default.
- W2299391211 hasRelatedWork W1606808875 @default.
- W2299391211 hasRelatedWork W2005931664 @default.
- W2299391211 hasRelatedWork W2071104170 @default.
- W2299391211 hasRelatedWork W2103911766 @default.
- W2299391211 hasRelatedWork W2246544348 @default.
- W2299391211 hasRelatedWork W2269752909 @default.
- W2299391211 hasRelatedWork W2587591094 @default.
- W2299391211 hasRelatedWork W2790863358 @default.
- W2299391211 hasRelatedWork W2889085598 @default.
- W2299391211 hasRelatedWork W2903586721 @default.
- W2299391211 hasRelatedWork W2969368436 @default.
- W2299391211 hasRelatedWork W2976704322 @default.
- W2299391211 hasRelatedWork W3093650434 @default.
- W2299391211 hasRelatedWork W3094552834 @default.
- W2299391211 hasRelatedWork W3110713355 @default.
- W2299391211 hasRelatedWork W3111895713 @default.
- W2299391211 hasRelatedWork W3118868694 @default.
- W2299391211 hasRelatedWork W64991062 @default.
- W2299391211 hasRelatedWork W2188547967 @default.
- W2299391211 isParatext "false" @default.
- W2299391211 isRetracted "false" @default.
- W2299391211 magId "2299391211" @default.
- W2299391211 workType "dissertation" @default.