Relevant bibliographies by topics / Fuzzy logic : Air conditioning

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Fuzzy logic : Air conditioning'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Fuzzy logic : Air conditioning"

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Moe, Maung Kyaw Soe. "Design and Simulation of Automatic Room Temperature by Using Fuzzy Control." ACMIT Proceedings 4, no. 1 (March 19, 2017): 67–78. http://dx.doi.org/10.33555/acmit.v4i1.61.

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In air conditioning system, efficient operation of air conditioning equipment to suit the user demand is important and to achieve that, Fuzzy Logic controller can play a key role in formulating the next generation of control technology for the traditional air conditioning equipment. The target of this research is to develop a fuzzy logic control which will allow less usage of energy by optimum operation of air conditioning which would also promote Conservation of Energy. The control system in this study also would need to achieve a Stable Climate Condition in the room within the limits of control set points and promote convenient to the users by automatic control. The control strategy proposed in this thesis work is fuzzy logic controller (FLC). A MATLAB fuzzy program tool is used to develop a fuzzy logic controller to achieve within the comfort parameters of temperature and artificial lighting as well as energy savings. Simulink program in MATLAB will also be used to simulate the fuzzy logic in this Thesis work. Based on the findings observed on the case study described in this Thesis Report, the savings achieved by the Fuzzy Logic Air Conditioning System is about 66%.With these results, it can be concluded that the objective of this Thesis work has been full filled)
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Rajagopalan, Parameshwaran, Karunakaran Rajasekaran, Senthilkumar Alagarsamy, S. Iniyan, and Mohal Lal. "Experimental analysis of fuzzy controlled energy efficient demand controlled ventilation economizer cycle variable air volume air conditioning system." Thermal Science 12, no. 3 (2008): 15–32. http://dx.doi.org/10.2298/tsci0803015r.

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In the quest for energy conservative building design, there is now a great opportunity for a flexible and sophisticated air conditioning system capable of addressing better thermal comfort, indoor air quality, and energy efficiency, that are strongly desired. The variable refrigerant volume air conditioning system provides considerable energy savings, cost effectiveness and reduced space requirements. Applications of intelligent control like fuzzy logic controller, especially adapted to variable air volume air conditioning systems, have drawn more interest in recent years than classical control systems. An experimental analysis was performed to investigate the inherent operational characteristics of the combined variable refrigerant volume and variable air volume air conditioning systems under fixed ventilation, demand controlled ventilation, and combined demand controlled ventilation and economizer cycle techniques for two seasonal conditions. The test results of the variable refrigerant volume and variable air volume air conditioning system for each techniques are presented. The test results infer that the system controlled by fuzzy logic methodology and operated under the CO2 based mechanical ventilation scheme, effectively yields 37% and 56% per day of average energy-saving in summer and winter conditions, respectively. Based on the experimental results, the fuzzy based combined system can be considered to be an alternative energy efficient air conditioning scheme, having significant energy-saving potential compared to the conventional constant air volume air conditioning system.
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Nan, Jin Rui, Yao Wang, Zhi Chai, and Jun Kui Huang. "Modeling of Electric Vehicle Air Conditioning System and Analysis of Energy Consumption." Advanced Materials Research 516-517 (May 2012): 1164–70. http://dx.doi.org/10.4028/www.scientific.net/amr.516-517.1164.

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An simulation model for pure electric vehicle air conditioning system is established in MATLAB/ Simulink environment. The critical component of air conditioning system is selected and simulated. Fuzzy logic control method is used in AC motor controlling strategy. Combined with ADVISOR, the total vehicle energy consumption and AC energy consumption are simulated and calculated. The research indicate that by using Fuzzy logic control led AC system, the vehicle’s economcial effeciency improved. Life mileage is longer than the EV with traditional AC system and a better effect of energy saving is achieved.
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Nasution, Henry. "DEVELOPMENT OF FUZZY LOGIC CONTROL FOR VEHICLE AIR CONDITIONING SYSTEM." TELKOMNIKA (Telecommunication Computing Electronics and Control) 6, no. 2 (August 1, 2008): 73. http://dx.doi.org/10.12928/telkomnika.v6i2.553.

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Nasution, Henry, Hishamuddin Jamaluddin, and Jamaluddin Mohd. Syeriff. "Energy Analysis for Air Conditioning System Using Fuzzy Logic Controller." TELKOMNIKA (Telecommunication Computing Electronics and Control) 9, no. 1 (April 1, 2011): 139. http://dx.doi.org/10.12928/telkomnika.v9i1.680.

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Lygouras, J. N., P. N. Botsaris, J. Vourvoulakis, and V. Kodogiannis. "Fuzzy logic controller implementation for a solar air-conditioning system." Applied Energy 84, no. 12 (December 2007): 1305–18. http://dx.doi.org/10.1016/j.apenergy.2006.10.002.

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Attia, Abdel-Hamid, Sohair F. Rezeka, and Ahmed M. Saleh. "Fuzzy logic control of air-conditioning system in residential buildings." Alexandria Engineering Journal 54, no. 3 (September 2015): 395–403. http://dx.doi.org/10.1016/j.aej.2015.03.023.

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Dong, Jie. "Adaptive PID Control for the Air-Conditioning System in Spray-Paint Workshop Based on Fuzzy Logic." Advanced Materials Research 433-440 (January 2012): 5733–38. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.5733.

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As the improvement of the modern workshop’s demand for cool supply, heating system, how to effectively manage the air-conditioning equipments to satisfy the production skills for air-conditioning system has become an important subject for modern workshop design. This paper comes from the No.1 motorcar company’s project about the automatic air-conditioning system of the car spray-paint workshop. For many reasons, the conventional PID control is difficult to satisfy the car spray-paint production’s strictly demands of the temperature, after a careful research of the object, we utilize the principle of fuzzy PID adaptive control to design a fuzzy PID controller, then put it into the air-conditioning heater’s controlling, through the practice, we find the controller has a good robust property and realized a good control result.
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Abe, Yasunori, Toshio Fukuda, Kouetsu Tanaka, Yoshio Tanaka, Fumihito Arai, Koji Shimojima, and Shigenori Ito. "Navigation System for Air Conditioning Equipment Inspection Robot." Journal of Robotics and Mechatronics 7, no. 5 (October 20, 1995): 354–66. http://dx.doi.org/10.20965/jrm.1995.p0354.

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We have previously proposed a navigation system for autonomous mobile robots that can recognize regular ceiling landmarks. This system can find square air diffusers on ceilings by sensing their multiple-quadrangle characteristics. We have now developed a new system that is able to recognize circular air diffusers. In addition, certain lighting conditions which obstructed recognition in the original system do not interfere with the newly proposed system. Here we applied Fuzzy and Neural Network Logic technology. A pre-processed image of a landmark is compared with a fuzzy template made from the fuzzy membership function. In order to find specific landmarks, the system determines the degrees of similarity by comparing the sited object with a variety of templates stored in its memory. Then a Neural Network uses results of this calculation to hone in on its target. So, the system can recognize many different kinds of landmarks. This paper shows the principle of this system and experimental results.
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Rahman, Sam Matiur, Mohammad Fazle Rabbi, Omar Altwijri, Mahdi Alqahtani, Tasriva Sikandar, Izzeldin Ibrahim Abdelaziz, Md Asraf Ali, and Kenneth Sundaraj. "Fuzzy logic-based improved ventilation system for the pharmaceutical industry." International Journal of Engineering & Technology 7, no. 2 (April 29, 2018): 640. http://dx.doi.org/10.14419/ijet.v7i2.9985.

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Indoor air quality in pharmaceutical industry plays a vital role in the production and storing of medicine. Stable indoor environment including favorable temperature, humidity, air flow and number of microorganisms requires consistent monitoring. This paper aimed to develop a fuzzy logic-based intelligent ventilation system to control the indoor air quality in pharmaceutical sites. Specifically, in the proposed fuzzy inference system, the ventilation system can control the air flow and quality in accordance with the indoor temperature, humidity, air flow and microorganisms in the air. The MATLAB® fuzzy logic toolbox was used to simulate the performance of the fuzzy inference system. The results show that the efficiency of the system can be improved by manipulating the input-output parameters according to the user’s demands. Compared with conventional heating, ventilation and air-conditioning (HVAC) systems, the proposed ventilation system has the additional feature of the existence of microorganisms, which is a crucial criterion of indoor air quality in pharmaceutical laboratories.
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Dissertations / Theses on the topic "Fuzzy logic : Air conditioning"

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Thompson, Richard. "Neuro-fuzzy predictive control of an information-poor system." Thesis, University of Oxford, 2002. http://ora.ox.ac.uk/objects/uuid:e463774c-a1c6-439e-a7e6-3cbb7aec68e3.

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While modern engineering systems have become increasingly integrated and complex over the years, interest in the application of control techniques which specifically attempt to formulate and solve the control problem in its inherently uncertain environment has been moderate, at best. More specifically, although many control schemes targeted at Heating, Ventilating and Air-Conditioning (HVAC) systems have been reported in the literature, most seem to rely on conventional techniques which assume that a detailed, precise model of the HVAC plant exists, and that the control objectives of the controller are clearly defined. Experience with HVAC systems shows that these assumptions are not always justifiable, and that, in practice, these systems are usually characterized by a lack of detailed design data and a lack of a robust understanding of the processes involved. Motivated by the need to more efficiently control complex, uncertain systems, this thesis focuses on the development and evaluation of a new neuro-fuzzy model-based predictive control scheme, where certain variables used in the optimization remain in the fuzzy domain. The method requires no training data from the actual plant under consideration, since detailed knowledge of the plant is unavailable. Results of the application of the control scheme to the control of thermal comfort in a simulated zone and to the control of the supply air temperature of an air-handling unit in the laboratory are presented. It is concluded that precious resources (as measured by actuator activity, for example) need not be wasted when controlling these systems. In addition, it is also shown that a very precise (and sometimes not necessarily accurate) control value computed at each sample is unnecessary. Rather, by defining the system and its environment in the fuzzy domain, the fuzzy decision algorithms developed here may be employed to get an "acceptable" control performance.
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Carvajal, Florez Fabio Alejandro. "Implementação de uma bancada de ensaios para analise de estrategias de controle de sistemas de refrigeração e ar condicionado." [s.n.], 2004. http://repositorio.unicamp.br/jspui/handle/REPOSIP/263357.

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Orientador: Luiz Felipe Mendes de Moura
Made available in DSpace on 2018-08-04T03:19:09Z (GMT). No. of bitstreams: 1 CarvajalFlorez_FabioAlejandro_D.pdf: 13507897 bytes, checksum: 763803f559424480cb0dc2207f08a244 (MD5) Previous issue date: 2004
Resumo: No presente trabalho se realiza o estudo do controle da válvula de expansão e da velocidade de rotação do motor do compressor para um sistema de ar condicionado com armazenamento térmico em banco de gelo. Utilizando os princípios de projeto térmico, projeto eletrônico, programação de computadores e técnicas de controle procuram-se o aumento da eficiência do sistema. Neste controle propostos usou-se a lógica difusa. Inicialmente controlou-se o grau de superaquecimento através do controle da abertura da válvula de expansão e trabalhando o compressor em sua rotação máxima. Em seguida foi implementado um controle que trabalha regulando simultaneamente a velocidade do compressor e a abertura da válvula de expansão
Abstract: In this work is realized a control analysis ofthe expansion valve and the rotacional speed of the compressor engine for an air conditioning system with thermal storage in an ice storage tank. The thermal project, electronical project, computer programming and control technics are integrated to increase the performance of the system. To implement the proposed controls the logic fuzzy is used. Inicially, the refrigerant superheat was controlled through the expansion valve with the compressor working at highest rotational speed. Then, it was implemented the control regulating simultananeously the compressor speed and the expansion valve
Doutorado
Termica e Fluidos
Doutor em Engenharia Mecânica
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Ghazali, Abu Baker Mhd. "Advanced controllers for building energy management systems : advanced controllers based on traditional mathematical methods (MIMO P+I, state-space, adaptive solutions with constraints) and intelligent solutions (fuzzy logic and genetic algorithms) are investigated for humidifying, ventilating and air-conditioning applications." Thesis, University of Bradford, 1996. http://hdl.handle.net/10454/4197.

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This thesis presents the design and implementation of control strategies for building energy management systems (BEMS). The controllers considered include the multi PI-loop controllers, state-space designs, constrained input and output MIMO adaptive controllers, fuzzy logic solutions and genetic algorithm techniques. The control performances of the designs developed using the various methods based on aspects such as regulation errors squared, energy consumptions and the settling periods are investigated for different designs. The aim of the control strategy is to regulate the room temperature and the humidity to required comfort levels. In this study the building system under study is a 3 input/ 2 output system subject to external disturbances/effects. The three inputs are heating, cooling and humidification, and the 2 outputs are room air temperature and relative humidity. The external disturbances consist of climatic effects and other stochastic influences. The study is carried out within a simulation environment using the mathematical model of the test room at Loughborough University and the designed control solutions are verified through experimental trials using the full-scale BMS facility at the University of Bradford.
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Ghazali, Abu Baker MHD. "Advanced controllers for building energy management systems. Advanced controllers based on traditional mathematical methods (MIMO P+I, state-space, adaptive solutions with constraints) and intelligent solutions (fuzzy logic and genetic algorithms) are investigated for humidifying, ventilating and air-conditioning applications." Thesis, University of Bradford, 1996. http://hdl.handle.net/10454/4197.

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This thesis presents the design and implementation of control strategies for building energy management systems (BEMS). The controllers considered include the multi PI-loop controllers, state-space designs, constrained input and output MIMO adaptive controllers, fuzzy logic solutions and genetic algorithm techniques. The control performances of the designs developed using the various methods based on aspects such as regulation errors squared, energy consumptions and the settling periods are investigated for different designs. The aim of the control strategy is to regulate the room temperature and the humidity to required comfort levels. In this study the building system under study is a 3 input/ 2 output system subject to external disturbances/effects. The three inputs are heating, cooling and humidification, and the 2 outputs are room air temperature and relative humidity. The external disturbances consist of climatic effects and other stochastic influences. The study is carried out within a simulation environment using the mathematical model of the test room at Loughborough University and the designed control solutions are verified through experimental trials using the full-scale BMS facility at the University of Bradford.
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Hawkins, M. E. "Fuzzy rule-based control of ducted air flows." Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334222.

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Liu, Xiong-Fu. "Fuzzy model-based fault-tolerant supervisory control of air-conditioning systems." Thesis, University of Oxford, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365359.

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Packirisamy, Muthukumaran. "Boundary conditioning concept applied to the synthesis of microsystems using fuzzy logic approach." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0015/NQ47713.pdf.

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Kung, Chi-yau, and 龔子游. "Fuzzy genetic modelling of air-conditioning systems for fault detection and diagnosis." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B43895682.

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Kung, Chi-yau. "Fuzzy genetic modelling of air-conditioning systems for fault detection and diagnosis." Click to view the E-thesis via HKUTO, 2004. http://sunzi.lib.hku.hk/hkuto/record/B43895682.

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Knall, Peter J. "Heating, Ventilation, and Air Conditioning Fault Detection Using the Fuzzy Jess Toolkit." University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1395094657.

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Book chapters on the topic "Fuzzy logic : Air conditioning"

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Kumari, Rajani, Sandeep Kumar, and Vivek Kumar Sharma. "Air Conditioning System with Fuzzy Logic and Neuro-Fuzzy Algorithm." In Advances in Intelligent Systems and Computing, 233–42. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1602-5_26.

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Song, Lepeng, Huanhuan Chen, Huiming Wu, and Zhiming Yang. "Adaptive Fuzzy Controller for Air Conditioning System." In Advances in Mechanical and Electronic Engineering, 255–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31507-7_42.

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Aguilar-Martin, Joseph. "Independence and Conditioning in a Connectivistic Fuzzy Logic Framework." In Advances in Intelligent and Soft Computing, 65–75. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1773-7_3.

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Zerrouki, Leïla, Bernadette Bouchon-Meunier, and Rémy Fondacci. "A fuzzy-neural model for co-ordination in air traffic flow management." In Fuzzy Logic in Artificial Intelligence, 190–204. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0095079.

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Hu, Rong, and Ye Xia. "Automotive Air-conditioning Systems Performance Prediction Using Fuzzy Neural Networks." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 291–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50212-0_35.

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Abdolkarimzadeh, Leila, Milad Azadpour, and M. H. Fazel Zarandi. "Two Hybrid Expert System for Diagnosis Air Quality Index (AQI)." In Fuzzy Logic in Intelligent System Design, 315–22. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67137-6_36.

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Glorennec, Pierre-Yves. "Forecasting Ozone Peaks Using Self-organizing Maps and Fuzzy Logic." In Air Pollution Modelling and Simulation, 544–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04956-3_52.

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Kshirsagar, Roshan, Chetankumar Patil, and Ashok Deshpande. "Development of Environment Friendly Air Conditioner Using Fuzzy logic." In Studies in Fuzziness and Soft Computing, 379–91. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06323-2_24.

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Li, Ziyang, Lijian Yang, Zhengtian Wu, Baoping Jiang, and Baochuan Fu. "Fuzzy Sliding Mode Control of a VAV Air-Conditioning Terminal Temperature System." In Advances in Intelligent Systems and Computing, 315–23. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4575-1_30.

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Pokrovsky, Oleg M., and Roger H. F. Kwok. "Modelling of Meteorological Factor Impacts on Urban Air Pollution Species by Fuzzy Logic Approach." In Air Pollution Modelling and Simulation, 513–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04956-3_49.

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Conference papers on the topic "Fuzzy logic : Air conditioning"

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Ahamed, Nizam Uddin, Zahari Bin Taha, Ismail Bin Mohd Khairuddin, M. F. Rabbi, S. A. M. Matiur Rahaman, and Kenneth Sundaraj. "Fuzzy logic controller design for intelligent air-conditioning system." In 2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE). IEEE, 2016. http://dx.doi.org/10.1109/ccsse.2016.7784388.

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Islam, Md Shabiul, Md Shakowat Zaman Sarker, Kazi Ashique Ahmed Rafi, and Masuri Othman. "Development of a Fuzzy Logic Controller Algorithm for Air-conditioning System." In 2006 IEEE International Conference on Semiconductor Electronics. IEEE, 2006. http://dx.doi.org/10.1109/smelec.2006.380753.

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Riadi, R., R. Tawegoum, A. Rachid, and G. Chasseriaux. "Decentralized temperature fuzzy logic control of a passive air conditioning unit." In 15th Mediterranean Conference on Control and Automation. IEEE, 2007. http://dx.doi.org/10.1109/med.2007.4433949.

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Pooja, V., P. Jayanthi, and K. L. Shunmuganathan. "Design of smart air-conditioning system using fuzzy logic and neural networks." In 2017 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC). IEEE, 2017. http://dx.doi.org/10.1109/iccpeic.2017.8290340.

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Gokilaveni, S., and P. Loganthurai. "Energy conservation possibilities in heating ventilating air conditioning system using fuzzy logic." In 2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO). IEEE, 2015. http://dx.doi.org/10.1109/isco.2015.7282343.

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Saha, Shumit, Sudip Kumar Saha, Ibnul Sanjid Iqbal, Anindya Kumar Kundu, MD Tofael Hossain Khan, and Sumit Kumar Pramanik. "Designing of a air-conditioning system using fuzzy logic with advantage of energy saving." In 2014 International Conference on Informatics, Electronics & Vision (ICIEV). IEEE, 2014. http://dx.doi.org/10.1109/iciev.2014.6850757.

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Khoo, Ivan, and Mark Cook. "Web-Based Occupant Feedback for Building Energy Management Systems Using Fuzzy Logic." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58137.

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This paper describes the development and validation of a novel web-based interface for the gathering of feedback from building occupants about their environmental discomfort including signs of Sick Building Syndrome (SBS). The gathering of such feedback may enable better targeting of environmental discomfort down to the individual as well as the early detection and subsequently resolution by building services of more complex issues such as SBS. The occupant’s discomfort is interpreted and converted to air-conditioning system set points using Fuzzy Logic. Experimental results from a multi-zone air-conditioning test rig have been included in this paper.
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Zain, Zainah Md, NorRul Hasma Abdullah, and Abdul Halim Mohd Hanafi. "Microcontroller-Based Energy Saving Control for Air - Conditioning System Using Fuzzy Logic Approaching: An Overview." In 2006 4th Student Conference on Research and Development. IEEE, 2006. http://dx.doi.org/10.1109/scored.2006.4339347.

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Javaid, Sakeena, Nadeem Javaid, Sohail Iqbal, Sheeraz Aslam, and Muhammad Hassan Rahim. "Optimizing energy consumption of air-conditioning systems with the fuzzy logic controllers in residential buildings: Optimizing energy consumption of air-conditioning systems in residential buildings." In 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). IEEE, 2018. http://dx.doi.org/10.1109/icomet.2018.8346336.

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Gacto, Maria Jose, Rafael Alcala, and Francisco Herrera. "Evolutionary Multi-Objective Algorithm to effectively improve the performance of the classic tuning of fuzzy logic controllers for a heating, ventilating and Air Conditioning system." In 2011 Ieee 5Th International Workshop On Genetic And Evolutionary Fuzzy Systems - Part Of 17273 - 2011 Ssci. IEEE, 2011. http://dx.doi.org/10.1109/gefs.2011.5949494.

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