SwePub
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Bjertness Espen) ;pers:(Naghavi Mohsen)"

Sökning: WFRF:(Bjertness Espen) > Naghavi Mohsen

  • Resultat 1-4 av 4
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  •  
2.
  •  
3.
  • Lowe, Robert, et al. (författare)
  • Affective-Associative Two-Process theory: A neural network investigation of adaptive behaviour in differential outcomes training
  • 2017
  • Ingår i: Adaptive Behavior. - : SAGE Publications. - 1059-7123 .- 1741-2633. ; 25:1, s. 5-23
  • Tidskriftsartikel (refereegranskat)abstract
    • In this article we present a novel neural network implementation of Associative Two-Process (ATP) theory based on an Actor-Critic-like architecture. Our implementation emphasizes the affective components of differential reward magnitude and reward omission expectation and thus we model Affective-Associative Two-Process theory (Aff-ATP). ATP has been used to explain the findings of differential outcomes training (DOT) procedures, which emphasize learning differentially valuated outcomes for cueing actions previously associated with those outcomes. ATP hypothesizes the existence of a prospective' memory route through which outcome expectations can bring to bear on decision making and can even substitute for decision making based on the retrospective' inputs of standard working memory. While DOT procedures are well recognized in the animal learning literature they have not previously been computationally modelled. The model presented in this article helps clarify the role of ATP computationally through the capturing of empirical data based on DOT. Our Aff-ATP model illuminates the different roles that prospective and retrospective memory can have in decision making (combining inputs to action selection functions). In specific cases, the model's prospective route allows for adaptive switching (correct action selection prior to learning) following changes in the stimulus-response-outcome contingencies.
  •  
4.
  • Wang, Dong, et al. (författare)
  • Toward Delicate Anomaly Detection of Energy Consumption for Buildings : Enhance the Performance From Two Levels
  • 2022
  • Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 10, s. 31649-31659
  • Tidskriftsartikel (refereegranskat)abstract
    • Buildings are highly energy-consuming and therefore are largely accountable for environmental degradation. Detecting anomalous energy consumption is one of the effective ways to reduce energy consumption. Besides, it can contribute to the safety and robustness of building systems since anomalies in the energy data are usually the reflection of malfunctions in building systems. As the most flexible and applicable type of anomaly detection approach, unsupervised anomaly detection has been implemented in several studies for building energy data. However, no studies have investigated the joint influence of data structures and algorithms’ mechanisms on the performance of unsupervised anomaly detection for building energy data. Thus, we put forward a novel workflow based on two levels, data structure level and algorithm mechanism level, to effectively detect the imperceptible anomalies in the energy consumption profiles of buildings. The proposed workflow was implemented in a case study for identifying the anomalies in three real-world energy consumption datasets from two types of commercial buildings. Two aims were achieved through the case study. First, it precisely detected the contextual anomalies concealed beneath the time variation of the energy consumption profiles of the three buildings. The performance in terms of areas under the precision-recall curves (AUC_PR) for the three given datasets were 0.989, 0.941, and 0.957, respectively. Second, more broadly, the joint effect of the two levels was examined. On the data level, all four detectors on the contextualized data were superior to their counterparts on the original data. On the algorithm level, there was a consistent ranking of detectors regarding their detecting performances on the contextualized data. The consistent ranking suggests that local approaches outperform global approaches in the scenarios where the goal is to detect the instances deviating from their contextual neighbors rather than the rest of the entire data.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-4 av 4

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy