A Multi-Agent Based Intelligent Query Processing System for Hadoop with Foundation for Intelligent Physical Agents-OS Using Cooperating Agent in Cloud Environment

Tharunya, S.; Manuel, Alwin; Shunmuganathan, K. L.

doi:10.1166/jctn.2016.4917

Cited by 2 publications

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“…This may lead to disagreements between users and administrators with competing goals (optimal convenience for users and optimum operating cost for managers). As proven by the authors in [ 80 , 82 ], MAS can manage these correlations to optimize construct performance ( Table 6 ).…”

Section: Discussion and Perspectivesmentioning

confidence: 99%

“… Pro-action: Putting IAs into practice fosters an analytical mindset that shows how the agent continually modifies his behaviors to attain his objectives. For instance, the agent may look for another agent who offers the same services if he loses touch with another agent whose services depend on him accomplishing his objectives [ 80 ]. Social aptitude: Intelligent agents can communicate with other intelligent entities.…”

Section: Intelligent Agentmentioning

confidence: 99%

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Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Binyamin

Slama

2022

Sensors

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Multi-Agent Systems (MAS) have been seen as an attractive area of research for civil engineering professionals to subdivide complex issues. Based on the assignment’s history, nearby agents, and objective, the agent intended to take the appropriate action to complete the task. MAS models complex systems, smart grids, and computer networks. MAS has problems with agent coordination, security, and work distribution despite its use. This paper reviews MAS definitions, attributes, applications, issues, and communications. For this reason, MASs have drawn interest from computer science and civil engineering experts to solve complex difficulties by subdividing them into smaller assignments. Agents have individual responsibilities. Each agent selects the best action based on its activity history, interactions with neighbors, and purpose. MAS uses the modeling of complex systems, smart grids, and computer networks. Despite their extensive use, MAS still confronts agent coordination, security, and work distribution challenges. This study examines MAS’s definitions, characteristics, applications, issues, communications, and evaluation, as well as the classification of MAS applications and difficulties, plus research references. This paper should be a helpful resource for MAS researchers and practitioners. MAS in controlling smart grids, including energy management, energy marketing, pricing, energy scheduling, reliability, network security, fault handling capability, agent-to-agent communication, SG-electrical cars, SG-building energy systems, and soft grids, have been examined. More than 100 MAS-based smart grid control publications have been reviewed, categorized, and compiled.

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Section: Discussion and Perspectivesmentioning

confidence: 99%

Section: Intelligent Agentmentioning

confidence: 99%

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Binyamin

Slama

2022

Sensors

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“…The functions of most data fusion systems include correlation detection, perception, and estimation, and the functional mode is shown in Figure 1. The fusion system is divided into two levels of low-level processing and high-level processing [28,29]. Low-level processing includes data extraction, data connection, target state evaluation, and characterization and is numerical processing that produces numerical results.…”

Section: Data Fusionmentioning

confidence: 99%

Construction of an Intelligent Processing Platform for Equestrian Event Information Based on Data Fusion and Data Mining

Zhou

2021

Journal of Sensors

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In the past two years, equestrian sports have become more and more popular with the public. Due to the comprehensive development of equestrian preparations for the 2020 Olympic Games in China, the equestrian sports industry presents an unprecedented favorable development environment in China. This article is aimed at studying the construction of an equestrian event information intelligent processing platform based on data fusion and data mining. This article introduces the relevant theoretical knowledge of data mining and data fusion, including the description of the concept of data mining, the common analysis methods and algorithms of data mining, the basic concepts of data fusion, and the functional structure of data fusion. It discusses various algorithms in cluster analysis and focuses on the analysis of distance measurement and similarity coefficient in cluster analysis. In the experimental part, in order to intelligently process and acquire information, an information intelligent processing platform is constructed based on data fusion and data mining technology. The experimental results of this paper show that the precision rate, recall rate, and F -score of the platform under closed test are much higher than those under open test, and the precision rate is increased by about 7.26%.

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A Multi-Agent Based Intelligent Query Processing System for Hadoop with Foundation for Intelligent Physical Agents-OS Using Cooperating Agent in Cloud Environment

Cited by 2 publications

References 0 publications

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Construction of an Intelligent Processing Platform for Equestrian Event Information Based on Data Fusion and Data Mining

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