What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Information technology
- Operating system
Yacine Rezgui mainly focuses on Knowledge management, Information and Communications Technology, Artificial neural network, Energy consumption and Construction management.
He interconnects Software deployment, Information system and Process management in the investigation of issues within Knowledge management.
His studies deal with areas such as Web service, Data management, Liability, Corporate governance and Action research as well as Information and Communications Technology.
His Artificial neural network research integrates issues from Baseline, Model predictive control, Energy management, Occupancy and Simulation.
His Energy consumption study combines topics from a wide range of disciplines, such as Genetic algorithm, Mathematical optimization, Efficient energy use and Management system.
His study in Construction management is interdisciplinary in nature, drawing from both Information technology, Identification, Virtual team, Virtual collaboration and Application service provider.
His most cited work include:
- Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption (249 citations)
- Building energy metering and environmental monitoring – A state-of-the-art review and directions for future research (164 citations)
- Sustainable building assessment tool development approach (139 citations)
What are the main themes of his work throughout his whole career to date?
Yacine Rezgui focuses on Knowledge management, Energy consumption, Process, Building information modeling and Context.
His work deals with themes such as Information and Communications Technology, Construction management, Information system and Process management, which intersect with Knowledge management.
His research in Information and Communications Technology focuses on subjects like Engineering management, which are connected to Information technology.
In his work, Renewable energy is strongly intertwined with Energy management, which is a subfield of Energy consumption.
His studies in Building information modeling integrate themes in fields like Corporate governance, Systems engineering, Supply chain, Cloud computing and Efficient energy use.
His Systems engineering study integrates concerns from other disciplines, such as Ontology and Software engineering.
He most often published in these fields:
- Knowledge management (28.83%)
- Energy consumption (10.21%)
- Process (10.21%)
What were the highlights of his more recent work (between 2016-2021)?
- Energy consumption (10.21%)
- Building information modeling (9.91%)
- Efficient energy use (6.91%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Energy consumption, Building information modeling, Efficient energy use, Built environment and Renewable energy.
In his research on the topic of Energy consumption, Data mining, Occupancy, Regression analysis, Demand forecasting and Random forest is strongly related with Artificial neural network.
His work carried out in the field of Building information modeling brings together such families of science as Knowledge management, Cloud computing, Systems engineering and Process management.
His Knowledge management research is multidisciplinary, incorporating elements of Digital transformation, Corporate governance, Data exchange, The Internet and Information and Communications Technology.
In his study, which falls under the umbrella issue of Built environment, Key is strongly linked to Resilience.
The study incorporates disciplines such as Energy management, Smart grid, Port, Photovoltaic system and Environmental economics in addition to Renewable energy.
Between 2016 and 2021, his most popular works were:
- Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption (249 citations)
- Towards the next generation of smart grids: Semantic and holonic multi-agent management of distributed energy resources (94 citations)
- Electrical load forecasting models: A critical systematic review (86 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Information technology
- Operating system
His primary areas of study are Building information modeling, Efficient energy use, Systems engineering, Energy management and Energy consumption.
His research in Building information modeling tackles topics such as Corporate governance which are related to areas like Information and Communications Technology, Intellectual property, Data management, Data governance and Knowledge management.
The various areas that Yacine Rezgui examines in his Knowledge management study include Outsourcing, Distributed generation, Key and Process management.
His Systems engineering study which covers Interoperability that intersects with State.
While the research belongs to areas of Energy management, Yacine Rezgui spends his time largely on the problem of Smart grid, intersecting his research to questions surrounding Environmental economics and Renewable energy.
His Energy consumption study combines topics in areas such as Artificial neural network, Genetic algorithm, Energy engineering and Data mining.
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