scholarly journals A Web Services, Ontology and Big Data Analysis Technology-Based Cloud Case-Based Reasoning Agent for Energy Conservation of Sustainability Science

2020 ◽  
Vol 10 (4) ◽  
pp. 1387
Author(s):  
Shih-Chin Chen ◽  
Sheng-Yuan Yang
Keyword(s):  
Big Data ◽  
Web Services ◽  
Energy Conservation ◽  
Energy Saving ◽  
Sustainability Science ◽  
Big Data Analytics ◽  
Case Based Reasoning ◽  
Core Technology ◽  
Reasoning Agent ◽  
Case Based

Energy conservation is one of the important topics for sustainability science, while case-based reasoning is one of the most important techniques for sustainable processing. This study aimed to develop a cloud case-based reasoning agent that integrates multiple intelligent technologies and supports, which can help users to quickly, accurately, and effectively obtain useful cloud energy-saving information in a timely manner for sustainability science. The system was successfully built with the support of Web services technology, ontology, and big data analytics. To set up this energy-saving case-based reasoning agent, this study reviewed the relevant technologies for building a web services platform and explored how to widely integrate and support the cloud interaction of the energy-saving data processing agent via the technologies. In addition to presenting relevant R&D technologies and results in detail, this study carefully conducted performance and learning experiments to prove the system’s effectiveness. The results showed that the core technology of the case-based reasoning agent achieved good performance and that the learning effectiveness of the overall system was also great.

scholarly journals Maintenance of Case Bases: Current Algorithms after Fifty Years

2018 ◽  
Author(s):  
Jose M. Juarez ◽  
Susan Craw ◽  
J. Ricardo Lopez-Delgado ◽  
Manuel Campos
Keyword(s):  
Big Data ◽  
50Th Anniversary ◽  
Case Based Reasoning ◽  
Changing Environments ◽  
Model Based ◽  
New Knowledge ◽  
Case Base ◽  
Case Based

Case-Based Reasoning (CBR) learns new knowledge from data and so can cope with changing environments. CBR is very different from model-based systems since it can learn incrementally as new data is available, storing new cases in its case-base. This means that it can benefit from readily available new data, but also case-base maintenance (CBM) is essential to manage the cases, deleting and compacting the case-base. In the 50th anniversary of CNN (considered the first CBM algorithm), new CBM methods are proposed to deal with the new requirements of Big Data scenarios. In this paper, we present an accessible historic perspective of CBM and we classify and analyse the most recent approaches to deal with these requirements.

Bioinformatics Web Services Composition with Case based Reasoning

2011 ◽  
Vol 6 (2) ◽  
pp. 240-253
Author(s):  
Shuang Qiu ◽  
Yadong Wang ◽  
Yongzhuang Liu ◽  
Liang Cheng
Keyword(s):  
Web Services ◽  
Case Based Reasoning ◽  
Web Services Composition ◽  
Services Composition ◽  
Case Based

scholarly journals Improving biomedical signal search results in big data case-based reasoning environments

2016 ◽  
Vol 28 ◽  
pp. 69-80 ◽  
Author(s):  
Jonathan Woodbridge ◽  
Bobak Mortazavi ◽  
Alex A.T. Bui ◽  
Majid Sarrafzadeh
Keyword(s):  
Big Data ◽  
Case Based Reasoning ◽  
Biomedical Signal ◽  
Search Results ◽  
Signal Search ◽  
Case Based

scholarly journals Spatial and Temporal Wind Power Forecasting by Case-Based Reasoning Using Big-Data

Energies ◽  
2017 ◽  
Vol 10 (2) ◽  
pp. 252 ◽  
Author(s):  
Fabrizio De Caro ◽  
Alfredo Vaccaro ◽  
Domenico Villacci
Keyword(s):  
Big Data ◽  
Wind Power ◽  
Case Based Reasoning ◽  
Wind Power Forecasting ◽  
Case Based ◽  
Power Forecasting

scholarly journals Utilisation of Case-Based Reasoning for Semantic Web Services Composition

2009 ◽  
Vol 5 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Taha Osman ◽  
Dhavalkumar Thakker ◽  
David Al-Dabass
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Semantic Web Services ◽  
Case Based Reasoning ◽  
Web Services Composition ◽  
Services Composition ◽  
Case Based

Research on the Air-Fuel Ratio Intelligent Control Method for Coke Oven Combustion Energy Saving

2011 ◽  
Vol 121-126 ◽  
pp. 2873-2877 ◽  
Author(s):  
Gong Fa Li ◽  
Yuan He ◽  
Guo Zhang Jiang ◽  
Jian Yi Kong ◽  
Liang Xi Xie
Keyword(s):  
Energy Saving ◽  
Working Conditions ◽  
Gas Flow ◽  
Control Method ◽  
Combustion Process ◽  
Coke Oven ◽  
Case Based Reasoning ◽  
Fuel Ratio ◽  
Intelligent Technology ◽  
Case Based

Coke combustion process, the constant proportion of the combustion air-fuel ratio control results in low combustion efficiency and fault-prone, difficult to adapt to changes in complex working conditions. Application of intelligent technology of case-based reasoning, fuzzy control, proposed for intelligent energy saving air-fuel ratio control method. Based on current trends in working conditions and combustion process in case of failure, predict the typical faults with case-based reasoning technology to the combustion process. On this basis, through case-based reasoning algorithm realize the real-time air-fuel ratio correction. Based on fuzzy-PID temperature cascade control we can obtain the appropriate flue gas flow and flue suction and realize the stability of the combustion process to achieve optimal control.

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