Matches in SemOpenAlex for { <https://semopenalex.org/work/W2884061570> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W2884061570 abstract "This paper presents a novel data-driven approach for predicting the number of vegetation-related outages that occur in power distribution systems on a monthly basis. In order to develop an approach that is able to successfully fulfill this objective, there are two main challenges that ought to be addressed. The first challenge is to define the extent of the target area. An unsupervised machine learning approach is proposed to overcome this difficulty. The second challenge is to correctly identify the main causes of vegetation-related outages and to thoroughly investigate their nature. In this paper, these outages are categorized into two main groups: growth-related and weather-related outages, and two types of models, namely time series and non-linear machine learning regression models are proposed to conduct the prediction tasks, respectively. Moreover, various features that can explain the variability in vegetation-related outages are engineered and employed. Actual outage data, obtained from a major utility in the U.S., in addition to different types of weather and geographical data are utilized to build the proposed approach. Finally, by utilizing various time series models and machine learning methods, a comprehensive case study is carried out to demonstrate how the proposed approach can be used to successfully predict the number of vegetation-related outages and to help decision-makers to detect vulnerable zones in their systems." @default.
- W2884061570 created "2018-08-03" @default.
- W2884061570 creator A5014663025 @default.
- W2884061570 creator A5081816027 @default.
- W2884061570 creator A5083024857 @default.
- W2884061570 date "2018-07-17" @default.
- W2884061570 modified "2023-09-27" @default.
- W2884061570 title "A Data-Driven Approach for Predicting Vegetation-Related Outages in Power Distribution Systems" @default.
- W2884061570 cites W1995698543 @default.
- W2884061570 cites W2133553065 @default.
- W2884061570 cites W2137130182 @default.
- W2884061570 cites W2156530876 @default.
- W2884061570 cites W2162089259 @default.
- W2884061570 cites W2172018462 @default.
- W2884061570 cites W2245860473 @default.
- W2884061570 cites W2412717324 @default.
- W2884061570 cites W2798056406 @default.
- W2884061570 cites W2811507150 @default.
- W2884061570 cites W3145506661 @default.
- W2884061570 cites W775021449 @default.
- W2884061570 cites W933982334 @default.
- W2884061570 hasPublicationYear "2018" @default.
- W2884061570 type Work @default.
- W2884061570 sameAs 2884061570 @default.
- W2884061570 citedByCount "0" @default.
- W2884061570 crossrefType "posted-content" @default.
- W2884061570 hasAuthorship W2884061570A5014663025 @default.
- W2884061570 hasAuthorship W2884061570A5081816027 @default.
- W2884061570 hasAuthorship W2884061570A5083024857 @default.
- W2884061570 hasConcept C119857082 @default.
- W2884061570 hasConcept C124101348 @default.
- W2884061570 hasConcept C142724271 @default.
- W2884061570 hasConcept C151406439 @default.
- W2884061570 hasConcept C154945302 @default.
- W2884061570 hasConcept C2776133958 @default.
- W2884061570 hasConcept C41008148 @default.
- W2884061570 hasConcept C45804977 @default.
- W2884061570 hasConcept C71924100 @default.
- W2884061570 hasConceptScore W2884061570C119857082 @default.
- W2884061570 hasConceptScore W2884061570C124101348 @default.
- W2884061570 hasConceptScore W2884061570C142724271 @default.
- W2884061570 hasConceptScore W2884061570C151406439 @default.
- W2884061570 hasConceptScore W2884061570C154945302 @default.
- W2884061570 hasConceptScore W2884061570C2776133958 @default.
- W2884061570 hasConceptScore W2884061570C41008148 @default.
- W2884061570 hasConceptScore W2884061570C45804977 @default.
- W2884061570 hasConceptScore W2884061570C71924100 @default.
- W2884061570 hasLocation W28840615701 @default.
- W2884061570 hasOpenAccess W2884061570 @default.
- W2884061570 hasPrimaryLocation W28840615701 @default.
- W2884061570 hasRelatedWork W1493085991 @default.
- W2884061570 hasRelatedWork W2143887693 @default.
- W2884061570 hasRelatedWork W2790863358 @default.
- W2884061570 hasRelatedWork W2807138771 @default.
- W2884061570 hasRelatedWork W2887537217 @default.
- W2884061570 hasRelatedWork W2897428373 @default.
- W2884061570 hasRelatedWork W2963617448 @default.
- W2884061570 hasRelatedWork W2964768871 @default.
- W2884061570 hasRelatedWork W2984931012 @default.
- W2884061570 hasRelatedWork W2988276440 @default.
- W2884061570 hasRelatedWork W2990233129 @default.
- W2884061570 hasRelatedWork W3022246423 @default.
- W2884061570 hasRelatedWork W3034993221 @default.
- W2884061570 hasRelatedWork W3035598877 @default.
- W2884061570 hasRelatedWork W3037647675 @default.
- W2884061570 hasRelatedWork W3132246361 @default.
- W2884061570 hasRelatedWork W3177070589 @default.
- W2884061570 hasRelatedWork W3186031152 @default.
- W2884061570 hasRelatedWork W3205041477 @default.
- W2884061570 hasRelatedWork W3111105136 @default.
- W2884061570 isParatext "false" @default.
- W2884061570 isRetracted "false" @default.
- W2884061570 magId "2884061570" @default.
- W2884061570 workType "article" @default.