Study on application of a neuro-fuzzy models in air conditioning systems

被引：11
|
作者：
Costa, Herbert R. do N. [1 ]
La Neve, Alessandro [2 ]
机构：
[1] Ctr Univ FEI, Dept Comp Sci, Sao Paulo, Brazil
[2] Ctr Univ FEI, Dept Elect Engn, Sao Paulo, Brazil
来源：
SOFT COMPUTING | 2015年 / 19卷 / 04期
关键词：
Membership Function; Fuzzy Control; Fuzzy Controller; Fuzzy Inference System; Consumption Reduction;
D O I：
10.1007/s00500-014-1431-5
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we present the application of neuro-fuzzy system-ANFIS for air conditioning systems to reduce electricity consumption. The current buildings have automation systems that provide data on lighting, electrical system, air conditioning system, etc. We studied the air conditioning system, in particular, to reduce energy consumption as air conditioning has a high consumption value. Our main goal in this study is the application of neuro-fuzzy system-ANFIS with the adjustment of the rules made by a decision tree-CART algorithm in air conditioning system. We compared the results of the application of the ANFIS-CART system with the application of PID controllers and fuzzy control system for a central air conditioning.
引用
收藏
页码：929 / 937
页数：9
相关论文
共 50 条
  • [41] Multi-agent systems with reinforcement hierarchical neuro-fuzzy models
    Marcelo França Corrêa
    Marley Vellasco
    Karla Figueiredo
    Autonomous Agents and Multi-Agent Systems, 2014, 28 : 867 - 895
  • [42] A nonlinear method of learning neuro-fuzzy models for dynamic control systems
    Bobyr, Maxim V.
    Emelyanov, Sergey G.
    APPLIED SOFT COMPUTING, 2020, 88
  • [43] MULTIAGENT COORDINATION SYSTEMS BASED ON NEURO-FUZZY MODELS WITH REINFORCEMENT LEARNING
    Mendoza, Leonardo Forero
    Batista, Evelyn
    de Mello, Harold Dias
    Pacheco, Marco Aurelio
    2018 17TH IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA), 2018, : 931 - 937
  • [44] On Automatic Design of Neuro-fuzzy Systems
    Cpalka, Krzysztof
    Rutkowski, Leszek
    Er, Meng Joo
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, PT I, 2010, 6113 : 43 - 48
  • [45] Neuro-Fuzzy Systems for Learning Analytics
    Casalino, Gabriella
    Castellano, Giovanna
    Zaza, Gianluca
    INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, ISDA 2021, 2022, 418 : 1341 - 1350
  • [46] Compromise approach to neuro-fuzzy systems
    Rutkowski, L
    Cpalka, K
    INTELLIGENT TECHNOLOGIES - THEORY AND APPLICATIONS: NEW TRENDS IN INTELLIGENT TECHNOLOGIES, 2002, 76 : 85 - 90
  • [47] DESIGN OF EXPERIMENTS IN NEURO-FUZZY SYSTEMS
    Zanchettin, Cleber
    Minku, Leandro
    Ludermir, Teresa
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS, 2010, 9 (02) : 137 - 152
  • [48] Neuro-fuzzy systems for engineering applications
    Goser, K
    Schuhmacher, K
    Hartung, M
    Heesche, K
    Hesse, B
    Kanstein, A
    AFRICON '96 - 1996 IEEE AFRICON : 4TH AFRICON CONFERENCE IN AFRICA, VOLS I & II: ELECTRICAL ENERGY TECHNOLOGY; COMMUNICATION SYSTEMS; HUMAN RESOURCES, 1996, : 759 - 764
  • [49] Merging ensemble of neuro-fuzzy systems
    Korytkowski, Marcin
    Nowicki, Robert
    Rutkowski, Leszek
    Scherer, Rafal
    2006 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5, 2006, : 1954 - +
  • [50] Financial prediction with neuro-fuzzy systems
    Pokropinska, Agata
    Scherer, Rafal
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2008, PROCEEDINGS, 2008, 5097 : 1120 - +
12345