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Multi-Agent-Based Analysis and Design of Decision-Support System for Real-Time Environment Control

Multi-Agent-Based Analysis and Design of Decision-Support System for Real-Time Environment Control

Namrata Das, Anirban Kundu
Copyright: © 2018 |Volume: 9 |Issue: 1 |Pages: 19
ISSN: 1948-5018|EISSN: 1948-5026|EISBN13: 9781522545545|DOI: 10.4018/IJGC.2018010101
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MLA

Das, Namrata, and Anirban Kundu. "Multi-Agent-Based Analysis and Design of Decision-Support System for Real-Time Environment Control." IJGC vol.9, no.1 2018: pp.1-19. http://doi.org/10.4018/IJGC.2018010101

APA

Das, N. & Kundu, A. (2018). Multi-Agent-Based Analysis and Design of Decision-Support System for Real-Time Environment Control. International Journal of Green Computing (IJGC), 9(1), 1-19. http://doi.org/10.4018/IJGC.2018010101

Chicago

Das, Namrata, and Anirban Kundu. "Multi-Agent-Based Analysis and Design of Decision-Support System for Real-Time Environment Control," International Journal of Green Computing (IJGC) 9, no.1: 1-19. http://doi.org/10.4018/IJGC.2018010101

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Abstract

The authors analyze different temperatures in different times and different seasons. They apply well-known data analysis agents, such as interpretation analysis, observation analysis, deductive analysis, and predictive analysis on the proposed framework. Some temperature values fall in intersected zones in which it is not definite to decide output measurement based on real-time temperature. In such scenarios, they apply fuzzy reasoning for analyzing real-time data and find the best possible solutions. Maximum method and centroid method are used for better performance in achieving optimum results for specific decisions as a support system.

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