Distributed and Self-learning Approaches for Energy Management

2021 ◽  
pp. 307-327
Author(s):  
Hussein Joumaa ◽  
Khoder Jneid ◽  
Mireille Jacomino
Keyword(s):  
Energy Management ◽  
Learning Approaches ◽  
Self Learning

scholarly journals Anomaly detection in discrete manufacturing using self-learning approaches

Procedia CIRP ◽  
2019 ◽  
Vol 79 ◽  
pp. 313-318 ◽  
Author(s):  
Benjamin Lindemann ◽  
Fabian Fesenmayr ◽  
Nasser Jazdi ◽  
Michael Weyrich
Keyword(s):  
Anomaly Detection ◽  
Learning Approaches ◽  
Discrete Manufacturing ◽  
Self Learning

scholarly journals Self-directed learning in the context of a nursing curriculum: Development of a learning plan

Curationis ◽  
1996 ◽  
Vol 19 (2) ◽  
Author(s):  
B. Majumdar
Keyword(s):  
Health Care ◽  
Nursing Curriculum ◽  
Learning Approaches ◽  
Self Directed Learning ◽  
Learning Plan ◽  
Directed Learning ◽  
Rapid Pace ◽  
Biological Health ◽  
Learning Contract ◽  
Self Learning

The rapid pace at which biological health breakthroughs and advancements in technology occur is creating unique challenges to health care programmes. The curricula of all health care programmes will need to be set in learning environments where students will be able to develop learning skills that are transportable across situations, over a whole lifetime. This article attempts to focus on self-directed learning (SDL) concepts and the development of a learning contract/plan, including the roles of both the student and faculty in self-learning approaches and contractual development.

scholarly journals Self-Learning Approaches for Real Optical Networks

2019 ◽  
Author(s):  
Marc Ruiz ◽  
Fabien Boitier ◽  
Patricia Layec ◽  
Luis Velasco
Keyword(s):  
Optical Networks ◽  
Learning Approaches ◽  
Self Learning

scholarly journals Dynamic Residential Energy Management for Real-Time Pricing

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2562
Author(s):  
Leehter Yao ◽  
Fazida Hanim Hashim ◽  
Chien-Chi Lai
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Smart Home ◽  
Solar Power ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Learning Scheme ◽  
Home Energy Management ◽  
Self Learning

A home energy management system (HEMS) was designed in this paper for a smart home that uses integrated energy resources such as power from the grid, solar power generated from photovoltaic (PV) panels, and power from an energy storage system (ESS). A fuzzy controller is proposed for the HEMS to optimally manage the integrated power of the smart home. The fuzzy controller is designed to control the power rectifier for regulating the AC power in response to the variations in the residential electric load, solar power from PV panels, power of the ESS, and the real-time electricity prices. A self-learning scheme is designed for the proposed fuzzy controller to adapt with short-term and seasonal climatic changes and residential load variations. A parsimonious parameterization scheme for both the antecedent and consequent parts of the fuzzy rule base is utilized so that the self-learning scheme of the fuzzy controller is computationally efficient.

scholarly journals Analytical framework for optimized feature extraction for upgrading occupancy sensing performance

2020 ◽  
Vol 10 (4) ◽  
pp. 4093
Author(s):  
Preethi Krishna Rao Mane ◽  
K. Narasimha Rao
Keyword(s):  
Machine Learning ◽  
Energy Management ◽  
Doppler Radar ◽  
Analytical Framework ◽  
Learning Approaches ◽  
Analytical Methodology ◽  
Efficient Selection ◽  
Accuracy Performance ◽  
Selection Of ◽  
Sensing Performance

The adoption of the occupancy sensors has become an inevitable in commercial and non-commercial security devices, owing to their proficiency in the energy management. It has been found that the usages of conventional sensors is shrouded with operational problems, hence the use of the Doppler radar offers better mitigation of such problems. However, the usage of Doppler radar towards occupancy sensing in existing system is found to be very much in infancy stage. Moreover, the performance of monitoring using Doppler radar is yet to be improved more. Therefore, this paper introduces a simplified framework for enriching the event sensing performance by efficient selection of minimal robust attributes using Doppler radar. Adoption of analytical methodology has been carried out to find that different machine learning approaches could be further used for improving the accuracy performance for the feature that has been extracted in the proposed system of occuancy system.

QoE Prediction for Multimedia Services

2015 ◽  
pp. 1784-1804
Author(s):  
Natalia Kushik ◽  
Jeevan Pokhrel ◽  
Nina Yevtushenko ◽  
Ana Cavalli ◽  
Wissam Mallouli
Keyword(s):  
Fuzzy Logic ◽  
Expert Systems ◽  
Logic Circuit ◽  
Experimental Results ◽  
Multimedia Service ◽  
Learning Approaches ◽  
Multimedia Services ◽  
Prediction Ability ◽  
Self Learning

This paper is devoted to the problem of evaluating the quality of experience (QoE) for a given multimedia service based on the values of service parameters such as QoS indicators. This paper proposes to compare two self learning approaches for predicting the QoE index, namely the approach based on logic circuit learning and the approach based on fuzzy logic expert systems. Experimental results for comparing these two approaches with respect to the prediction ability and the performance are provided.

Self‐learning energy management for plug‐in hybrid electric bus considering expert experience and generalization performance

2020 ◽  
Vol 44 (7) ◽  
pp. 5659-5674
Author(s):  
Hongqiang Guo ◽  
Fengrui Zhao ◽  
Hongliang Guo ◽  
Qinghu Cui ◽  
Erlei Du ◽  
...  
Keyword(s):  
Energy Management ◽  
Generalization Performance ◽  
Hybrid Electric Bus ◽  
Electric Bus ◽  
Hybrid Electric ◽  
Self Learning
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