Investigating the influence of maintenance strategies on building energy performance: A systematic literature review

Alghanmi, Ashraf; Yunusa‐Kaltungo, Akilu; Edwards, Rodger

doi:10.1016/j.egyr.2022.10.441

Cited by 17 publications

(4 citation statements)

References 94 publications

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“…The methodology is structured into four main phases: Literature Collection, Screening & Selection, Bibliometric Analysis, and Synthesis. Each phase is meticulously designed to ensure a thorough exploration of the PKF's contributions and to uncover potential research trajectories within its applications [100][101][102][103][104][105][106][107][108][109][110][111][112][113][114][115][116].…”

Section: Methodsmentioning

confidence: 99%

The rise of the polarimetric Kalman filter: a bibliometric study on its growing significance

Obaideen,

AlShabi,

Gadsden

et al. 2024

Polarization: Measurement, Analysis, and Remote Sensing XVI

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This paper presents a comprehensive study on the evolution, applications, and impact of the Polarimetric Kalman Filter (PKF) in the fields of signal processing and remote sensing. By employing a methodological framework that integrates literature collection, screening and selection, bibliometric analysis, and synthesis, we aim to elucidate the PKF's contributions and potential research trajectories within its applications. Our findings highlight the PKF's significant role in enhancing data assimilation, improving predictive accuracy, and refining measurement techniques across various domains, particularly in meteorological research and environmental monitoring. The analysis reveals the interdisciplinary nature of PKF applications and its capability to merge theoretical advancements with practical implementations, underlining the importance of sophisticated signal processing algorithms in interpreting complex environmental data. The study also identifies emerging trends, such as the integration of PKF with machine learning and artificial intelligence, indicating future directions for research that promise to push the boundaries of current methodologies and applications. This paper underscores the PKF's pivotal role in advancing signal processing and remote sensing technologies, offering insights into its continuing development and the expanding scope of its applications.

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Section: Methodsmentioning

confidence: 99%

The rise of the polarimetric Kalman filter: a bibliometric study on its growing significance

Obaideen,

AlShabi,

Gadsden

et al. 2024

Polarization: Measurement, Analysis, and Remote Sensing XVI

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“…This paper uses an all-inclusive method that examines and combines the application of the EnKF within the renewable energy sector as well as employs Scopus for literature retrieval and VOSviewer for bibliometric analysis [45][46][47][48][49][50][51][52][53]. The methodological framework, shown in Figure 1, is delineated into several phases: literature collection, screening, analysis, and synthesis in details are as follows:…”

Section: Methodsmentioning

confidence: 99%

Beyond conventional predictions: unfolding the ensemble Kalman filter's publications in renewable energy

Obaideen,

Faroukh,

AlShabi

2024

Energy Harvesting and Storage: Materials, Devices, and Applications XIV

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Within the process of development of sustainable energy solutions, the Ensemble Kalman Filter (EnKF) holds an allimportant key by assisting in forecasting and optimization of renewable energy systems. This essay describes in detail how the EnKF is utilized in diverse sectors of the renewable energy, of which one of its many vital roles is managing the variability and uncertainty that characterize wind and solar energy sources. By performing a meta-analysis and bibliometric work we discover that EnKF do two things very well -the level of the predictive model accuracy is increased and it is also easy to allocate the resources. Grid stability is another issue which EnKF solves well. The versatility of EnKF in wind forecasting has been highlighted in light of a study which has not only demonstrated how this method may be applied in renewable energy sources but also sheds light on recent developments as well. We will leave the forward part to researching potential additional studies such as EnKF integration with machine learning methods and its use towards renewables recent development. The work above shows how EnKF capable advanced data assimilation methods are highly needed for phasing out fossil fuels and ensure the shift to renewable energy sources as the global primary energy source.

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“…As we can in Figure 1, this study employed a comprehensive methodological approach [95][96][97][98][99][100][101][102][103][104][105][106][107][108][109][110][111][112] which enables better insight into the progress and contexts of application of sliding mode and variable structure filters, for a coupled picture in order to realize the stage of development and status quo. First we did a detailed searching of academic publications and articles on signal-to-noise ratio and its applications in signal processing using the widely known "Scopus" database which is known for containing a large collection of scientific and technical research articles.…”

Section: Methodsmentioning

confidence: 99%

Sliding mode and variable structure filters for signal processing: a literature review

Obaideen,

Hilal,

Gadsden

et al. 2024

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII

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This paper will conduct an exhaustive analysis of sliding mode and variable structure filters, essential methodologies employed in signal processing that solve problems noisy and volatile environments induces. This study brings into focus the very foundations and practicality of interference filters by professional exploration of the theoretical basis, the extent of practical implementation, and the present research frontiers. It also emphasizes the critical role these filters play in making signal processing system more precise, adaptable, and resilient. The Sliding mode and the variable structure filters are optimal in the field of nonlinear problems that are augmented by interferences. These are what their purpose in noise reduction, error minimization and the system stability is. Review encompasses a wide range of applications, from robotics, aerospace to telecommunication with the aim to emphasis the variety and successfully of the filtering techniques when the signal processing is carried out in complex situations. The synthesis of the most recent achievements of the technology and discovery of the potential future directions passed down the concept of this work. The aim is to provide a push to developers to promote the implementation of the advanced application-specific solutions. And this discussion also demonstrates the flexible character that helps meet the demands of dynamic signal processing environments, forming the foundation for the next advanced systems that are adaptive and robust.

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Investigating the influence of maintenance strategies on building energy performance: A systematic literature review

Cited by 17 publications

References 94 publications

The rise of the polarimetric Kalman filter: a bibliometric study on its growing significance

The rise of the polarimetric Kalman filter: a bibliometric study on its growing significance

Beyond conventional predictions: unfolding the ensemble Kalman filter's publications in renewable energy

Sliding mode and variable structure filters for signal processing: a literature review

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