scholarly journals Computational Intelligence Approaches for Energy Load Forecasting in Smart Energy Management Grids: State of the Art, Future Challenges, and Research Directions

Energies ◽  
2018 ◽  
Vol 11 (3) ◽  
pp. 596 ◽  
Author(s):  
Seyedeh Fallah ◽  
Ravinesh Deo ◽  
Mohammad Shojafar ◽  
Mauro Conti ◽  
Shahaboddin Shamshirband
Keyword(s):  
Energy Management ◽  
Computational Intelligence ◽  
State Of The Art ◽  
Load Forecasting ◽  
Research Directions ◽  
Future Challenges ◽  
Smart Energy Management

Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions

2018 ◽  
Vol 276 ◽  
pp. 2-22 ◽  
Author(s):  
Ali Kalantari ◽  
Amirrudin Kamsin ◽  
Shahaboddin Shamshirband ◽  
Abdullah Gani ◽  
Hamid Alinejad-Rokny ◽  
...  
Keyword(s):  
Computational Intelligence ◽  
State Of The Art ◽  
Medical Data ◽  
Research Directions ◽  
Future Challenges

scholarly journals Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges

2020 ◽  
Vol 12 (20) ◽  
pp. 8495
Author(s):  
Tri-Hai Nguyen ◽  
Luong Vuong Nguyen ◽  
Jason J. Jung ◽  
Israel Edem Agbehadji ◽  
Samuel Ofori Frimpong ◽  
...  
Keyword(s):  
Energy Management ◽  
Smart Grids ◽  
Optimization Problems ◽  
State Of The Art ◽  
Biological Evolution ◽  
Optimization Methods ◽  
Management Systems ◽  
Collective Behaviors ◽  
Energy Management Systems ◽  
Smart Energy Management

Sustainable energy development consists of design, planning, and control optimization problems that are typically complex and computationally challenging for traditional optimization approaches. However, with developments in artificial intelligence, bio-inspired algorithms mimicking the concepts of biological evolution in nature and collective behaviors in societies of agents have recently become popular and shown potential success for these issues. Therefore, we investigate the latest research on bio-inspired approaches for smart energy management systems in smart homes, smart buildings, and smart grids in this paper. In particular, we give an overview of the well-known and emerging bio-inspired algorithms, including evolutionary-based and swarm-based optimization methods. Then, state-of-the-art studies using bio-inspired techniques for smart energy management systems are presented. Lastly, open challenges and future directions are also addressed to improve research in this field.

scholarly journals Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island’s power system

2019 ◽  
Vol 238 ◽  
pp. 627-642 ◽  
Author(s):  
Spyridon Chapaloglou ◽  
Athanasios Nesiadis ◽  
Petros Iliadis ◽  
Konstantinos Atsonios ◽  
Nikos Nikolopoulos ◽  
...  
Keyword(s):  
Power System ◽  
Energy Management ◽  
Load Forecasting ◽  
Peak Shaving ◽  
Management Algorithm ◽  
Smart Energy Management

scholarly journals Intelligent Robots for Fruit Harvesting: Recent Developments and Future Challenges

2021 ◽  
Author(s):  
Hongyu Zhou ◽  
Xing Wang ◽  
Wesley Au ◽  
Hanwen Kang ◽  
Chao Chen
Keyword(s):  
State Of The Art ◽  
Future Research ◽  
User Requirements ◽  
Research Directions ◽  
System Architectures ◽  
The Past ◽  
Intelligent Robots ◽  
Future Challenges ◽  
Recent Developments ◽  
Growing Population

Abstract Intelligent robots for fruit harvesting have been actively developed over the past decades to bridge the increasing gap between feeding a rapidly growing population and limited labour resources. Despite significant advancements in this field, widespread use of harvesting robots in orchards is yet to be seen. To identify the challenges and formulate future research and development directions, this work reviews the state-of-the-art of intelligent fruit harvesting robots by comparing their system architectures, visual perception approaches, fruit detachment methods and system performances. The potential reasons behind the inadequate performance of existing harvesting robots are analysed and a novel map of challenges and potential research directions is created, considering both environmental factors and user requirements.

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