Optimization of Strategies and Models Review for Optimal Technologies - Based On Fuzzy Schemes for Green Architecture
Recently, the green architecture becomes a
significant way to a sustainable future. Green building designs
involve finding the balance between comfortable homebuilding and
sustainable environment. Moreover, the utilization of the new
technologies such as artificial intelligence techniques are used to
complement current practices in creating greener structures to keep
the built environment more sustainable. The most common objectives
in green buildings should be designed to minimize the overall impact
of the built environment that effect on ecosystems in general and in
particularly human health and natural environment. This will lead to
protecting occupant health, improving employee productivity,
reducing pollution and sustaining the environmental. In green
building design, multiple parameters which may be interrelated,
contradicting, vague and of qualitative/quantitative nature are
broaden to use. This paper presents a comprehensive critical state- ofart-
review of current practices based on fuzzy and its combination
techniques. Also, presented how green architecture/building can be
improved using the technologies that been used for analysis to seek
optimal green solutions strategies and models to assist in making the
best possible decision out of different alternatives.
[1] Wong, J. K. W. & Li, H., Application of the analytic hierarchy process
(AHP) in multi-criteria analysis of the selection of intelligent building
systems, Building and Environment, Vol. 43, Issue 1, pp. 108–125,
2008.
[2] Dutta, K. & Sarthak, S., Architectural space planning using evolutionary
computing approaches: a review, Artifi. Intell. Rev., 4(36), pp. 311-321,
2011.
[3] Airaksinen, M. & Matilainen, P., A carbon footprint of an office
building, Energies 4, pp. 1197–1210, 2011.
[4] Tsikaloudaki, K., Laskos, K. & Bikas, D., On the establishment of
climatic zones in Europe with regard to the energy performance of
buildings, Energies 5, pp. 32–44, 2012.
[5] Wright, C. et al, Residential energy performance metrics, Energies 3, pp.
1194–1211, 2010.
[6] Yang, Z. et al, Building space heating with a solar-assisted heat pump
using roof-integrated solar collectors, Energies, 4, pp. 504–516, 2011.
[7] Liao, K. S., Designs and architectures for the next generation of organic
solar cells, Energies 3, pp. 1212–1250, 2010.
[8] Jacob, B., Lamps for improving the energy efficiency of domestic
lighting, Light. Res. Technol., 41, pp. 219–228, 2009.
[9] Shaukat, A.K. & Kamal, M.A., Study of visco-elastic properties of
shoppers waste for its reuse as construction material, Constr. Build.
Mater. 24, pp. 1340 –1351, 2010.
[10] Begum, R.A., Siwar, C., Pereira, J.J. & Jaafar, A.H., Attitude and
behavioural factors in waste management in the construction industry of
Malaysia, Resour. Conserv. Recycl., 53, pp. 321–328, 2009.
[11] Kikegawa, Y., Development of a numerical simulation system toward
comprehensive assessments of urban warming countermeasures
including their impacts upon the urban buildings, energy demands. Appl.
Energy 76, pp. 449–466, 2003.
[12] Deru, M., Pless, S.D. & Torcellini, P.A., Bighorn home improvement
center energy performance, Proceedings of the ASHRAE Transactions
Annual Meeting, Quebec City, Canada, pp. 349–366, 24–28 June, 2006.
[13] Jalalzadeh-Azar, A. A., Experimental evaluation of a downsized
residential air distribution System: comfort and ventilation effectiveness,
ASHRAE J., 113, pp. 313–322, 2007.
[14] Tzempelikos, A. & Athienitis, A.K., The impact of shading design and
control on building cooling and lighting demand, Sol. Energy 81, pp.
369–382, 2007.
[15] Zago, M., Efficiency analysis of independent and centralized heating
systems for residential buildings in Italy, Energies 4, pp. 2115–2131,
2011.
[16] Pacheco, R., Ordez, J. & Martnez, G., Energy efficient design of
building: A review, Renew. Sustain. Energy Rev., 16, pp. 3559–3573,
2012.
[17] Sailor, D.J., A green roof model for building energy simulation
programs, Energy Build. 40, pp. 1466–1478, 2008.
[18] Lai, C. M. & Wang, Y. H., Energy-saving potential of building envelope
designs in residential houses in Taiwan, Energies 4, pp. 2061–2076,
2011.
[19] Shekarchian, M., The cost benefit analysis and potential emission
reduction evaluation of applying wall insulation for buildings in
Malaysia, Renew. Sustain. Energy Rev., 16, pp. 4708–4718, 2012.
[20] Roth, K., Lawrence, T. & Brodrick, J., Double-skin façades, ASHRAE
J., 49, pp. 70–73, 2007.
[21] Shameri, M. et al, Perspectives of double skin façade systems in
buildings and energy saving, Renew. Sustain. Energy Rev., 15, pp.
1468–1475, 2011.
[22] Yusuf S.A, Georgakis & P. Nwagboso, C., Review of modelling
visualisation and artificial intelligent methodologies for built
environment applications, Built & Human Environment Review, Vol. 3.
pp. 12-41, 2010.[23] Paulescu, M., Gravila, P. & Tulcan, E., Fuzzy logic algorithms for
atmospheric transmittances of use in solar energy estimation, Energy
Conversion and Management, Vol. 49, pp. 3691–3697, 2008.
[24] Bashiri, M., Badri, H. & Hejazi, T.H., Selecting optimum maintenance
strategy by fuzzy interactive linear assignment method, Applied
Mathematical Modelling, Vol. 35, issue 1, pp. 152-164, 2011.
[25] Naji, H.R., Meybodi, M.N. & Moghaddam, T.N., Intelligent building
management systems by using multi agents: fuzzy approach,
International Journal of Computer Applications; Vol. 14, Issue 6, pp. 9-
14, 2011.
[26] Hsueh, S.L., A fuzzy utility-based multi-criteria model for evaluating
households’ energy conservation performance: a Taiwanese case study,
Energies, 5, pp. 2818-2834, 2012.
[27] Hsueh, S.L., A fuzzy logic enhanced environmental protection education
model for policies decision support in green community development,
Scientific World Journal, 8 pages, 2013.
[28] Shaikh, P.H., Nor, N.B., Nallagownden, P. & Elamvazuthi, I., Indoor
building fuzzy control of energy and comfort management, Research
Journal of Applied Sciences, Engineering and Technology, Vol. 6, Issue
23, pp. 4445-4450, 2013.
[29] Chehri, A. & Mouftah, H. T., FEMAN: Fuzzy-based energy
management system for green houses using hybrid grid solar power,
Journal of Renewable Energy, Article ID 785636, 6 pages, 2013.
[30] Lei, C. & Cheng, W.L., Research on green evaluation system of harbor
engineering based on fuzzy analytic hierarchy process, Journal of Water
Resources and Architectural Engineering, 2013.
[31] Hu, M.H., Ku, M.Y., Liao, C.K. & Ding, P.Y., Evaluation of green
residence using integrated structural equation model with fuzzy theory,
19th International Conference on Industrial Engineering and
Engineering Management, pp. 333-344, 2013.
[32] Dou, Y. et al, Government green procurement: A fuzzy-DEMATEL
analysis of barriers, Supply Chain Management Under Fuzziness Studies
in Fuzziness and Soft Computing, Vol. 313, pp. 567-589, 2014.
[33] Lacagnina, V. et al, Comparison between statistical and fuzzy
approaches for improving diagnostic decision making in patients with
chronic nasal symptoms, Fuzzy Sets and Systems, Vol. 237, pp. 136–
150, 2014.
[34] Afful-Dadzie, E., Afful-Dadzie, A. & Oplatkova, Z.K., Measuring
progress of the millennium development goals: A fuzzy comprehensive
evaluation approach, Applied Artificial Intelligence: An International
Journal, Vol. 28, Issue 1, pp. 1-15, 2015.
[35] Hsueh, S.L., Hsu, K.S. & Liu, C.Y., A multi-criteria evaluation model
for developmental effectiveness in cultural and creative industries,
Procedia Engineering, Vo. 29, pp. 1755–1761, 2012.
[36] Hsueh, S.L. & Yan, M.R., A multi methodology contractor assessment
model for facilitating green innovation: the view of energy and
environmental protection, Scientific World Journal., 14 pages, 2013.
[37] Hung, H.S. et al, An evaluation model of floor area incentive for urban
regeneration projects from the perspective of carbon emissions, Master
Program in Architecture and Urban Design, 2013.
[38] Hsueh, S.L., Evaluation of community energy-saving effects using fuzzy
logic model, Environmental Engineering & Management Journal
(EEMJ), Vol. 13, Issue 5, pp.1207-1212, 2014.
[39] Wu, K.Y., Applying the fuzzy Delphi method to analyze the sustainable
neighbourhood unit evaluation factors, Proceedings of the 15th WSEAS
international conference on Systems, pp. 23-28, 2011.
[40] Liu, L. & Zhang, T., Application of FCJ in the evaluation of low-carbon
construction program, Applied Mechanics and Materials, pp. 357-360,
2013.
[41] Lu, H., Phdungsilp, A. & Martinac, I., A study of the design criteria
affecting energy demand in new building clusters using fuzzy AHP,
Sustainability in Energy and Buildings Smart Innovation, Systems and
Technologies, Vol. 22, pp. 955-963, 2013.
[42] Chan, H.K., Wang, X. & Raffoni, A., An integrated approach for green
design: Life-cycle, fuzzy AHP and environmental management
accounting, Accounting for sustainability in production and supply
chains, Vol. 46, Issue 4, pp. 344–360, 2014.
[43] Lan, S.H. & Sheng, T.H., The study on key factors of influencing
consumers’ purchase of green buildings application of two-stage fuzzy
analytic hierarchy process, International Business Research, Vol. 7,
Issue 6, pp. 49-60, 2014.
[44] Feng, L., Zhu, X. & Sun, X., Assessing coastal reclamation suitability
based on a fuzzy-AHP comprehensive evaluation framework: A case
study of Lianyungang, China, Marine Pollution Bulletin Vol. 89, Issues
1, pp.102–111, 2014.
[45] Donevska, K.R., Gorsevski, P.V., Jovanovski, M. & Pesevski, I.,
Regional non-hazardous landfill site selection by integrating fuzzy logic,
AHP and geographic information systems, Environmental Earth
Sciences, Vol. 67, Issue 1, pp. 121-13, 2012.
[46] Huang, Y., Bao, T., Huang, Z. & Wang, H., Research on the weighting
coefficients of the lighting evaluation for the target lane, Advanced
Materials Research, pp. 1065-1069, 2015.
[47] Lee, S.K., Mogi, G. & Hui, K.S., A fuzzy analytic hierarchy process
(AHP)/data envelopment analysis (DEA) hybrid model for efficiently
allocating energy R&D resources: In the case of energy technologies
against high oil prices, Renewable and Sustainable Energy Reviews,
Vol. 21, pp. 347–355, 2013.
[48] Tang, Y., Xu, K. & Min, Y., AHP-based fuzzy comprehensive
evaluation for urbanization of mountainous area in Xianning, Advanced
Materials Research , pp. 1073 - 1076, 2015.
[49] Akadiri, P.O., Olomolaiye, P.O. & Chinyio, E.A., Multi-criteria
evaluation model for the selection of sustainable materials for building
projects, Automation in Construction, Vol. 30, pp. 113–125, 2013.
[50] Wang, J.L., Ma, R.H. & Dong, X.H., Research on energy saving of
appliances with evaluation method and application of appliances green
degree based on fuzzy-EAHP, Advanced Materials Research, Vol. 977,
pp. 155-160, 2014.
[51] Hsueh, S.L. & Yan, M.R., Enhancing sustainable community
developments: a multi-criteria evaluation model for energy efficient
project selection, International Conference on Energy, Environment and
Development, pp.135-144, 2011.
[52] Liu, K.S. et al, A DFuzzy-DAHP decision-making model for evaluating
energy-saving design strategies for residential buildings. Energies 5, pp.
4462-4480, 2012.
[53] Hsueh, S.L. et al, DFAHP multi-criteria risk assessment model for
redeveloping derelict public buildings, International Journal of Strategic
Property Management, Vol. 17, Issue 4, pp. 333-346, 2013.
[54] Alapure, G., George, D. & Bhattacharya S., Delphi-AHP-Fuzzy
computational approach to sustainability assessment model and Indian
traditional built forms, 2nd International Journal of Scientific
Engineering and Technology, Vol. 3, Issue 11, pp. 1330-1335, 2014.
[55] Gumus, A.T. et al, A combined fuzzy-AHP and fuzzy-GRA
methodology for hydrogen energy storage method selection in
Turkey, Energies. 6(6), pp. 3017–3032, 2013.
[56] Wang, Y. et al, Combination of extended fuzzy AHP and fuzzy GRA for
government E-tendering in hybrid fuzzy environment, The Scientific
World Journal, Vol. 2014, Article ID 123675, 11 pages, 2014.
[57] Liu, H.T., Product design and selection using fuzzy QFD and fuzzy
MCDM approaches, Applied Mathematical Modelling, Vol. 35, Issue 1,
pp. 482–496, 2011.
[58] Kabak, M. et al, A fuzzy multi-criteria decision making approach to
assess building energy performance, Energy and Buildings, Vol. 72, pp.
382–389, 2014.
[59] Tsai, W.H. et al, Construction method selection for green building
projects to improve environmental sustainability by using an MCDM
approach, Environmental Planning and Management, Vol. 56, Issue 10,
pp. 1487-1510, 2013.
[60] Rostamzadeh, R. et al, Application of fuzzy VIKOR for evaluation of
green supply chain management practices, Ecological Indicators, Vol.
49, pp. 188–203, 2015.
[61] Shaikh, P. et al, Building energy management through a distributed
fuzzy inference system, International Journal of Engineering and
Technology, 5 (4), pp. 3236-324, 2013.
[1] Wong, J. K. W. & Li, H., Application of the analytic hierarchy process
(AHP) in multi-criteria analysis of the selection of intelligent building
systems, Building and Environment, Vol. 43, Issue 1, pp. 108–125,
2008.
[2] Dutta, K. & Sarthak, S., Architectural space planning using evolutionary
computing approaches: a review, Artifi. Intell. Rev., 4(36), pp. 311-321,
2011.
[3] Airaksinen, M. & Matilainen, P., A carbon footprint of an office
building, Energies 4, pp. 1197–1210, 2011.
[4] Tsikaloudaki, K., Laskos, K. & Bikas, D., On the establishment of
climatic zones in Europe with regard to the energy performance of
buildings, Energies 5, pp. 32–44, 2012.
[5] Wright, C. et al, Residential energy performance metrics, Energies 3, pp.
1194–1211, 2010.
[6] Yang, Z. et al, Building space heating with a solar-assisted heat pump
using roof-integrated solar collectors, Energies, 4, pp. 504–516, 2011.
[7] Liao, K. S., Designs and architectures for the next generation of organic
solar cells, Energies 3, pp. 1212–1250, 2010.
[8] Jacob, B., Lamps for improving the energy efficiency of domestic
lighting, Light. Res. Technol., 41, pp. 219–228, 2009.
[9] Shaukat, A.K. & Kamal, M.A., Study of visco-elastic properties of
shoppers waste for its reuse as construction material, Constr. Build.
Mater. 24, pp. 1340 –1351, 2010.
[10] Begum, R.A., Siwar, C., Pereira, J.J. & Jaafar, A.H., Attitude and
behavioural factors in waste management in the construction industry of
Malaysia, Resour. Conserv. Recycl., 53, pp. 321–328, 2009.
[11] Kikegawa, Y., Development of a numerical simulation system toward
comprehensive assessments of urban warming countermeasures
including their impacts upon the urban buildings, energy demands. Appl.
Energy 76, pp. 449–466, 2003.
[12] Deru, M., Pless, S.D. & Torcellini, P.A., Bighorn home improvement
center energy performance, Proceedings of the ASHRAE Transactions
Annual Meeting, Quebec City, Canada, pp. 349–366, 24–28 June, 2006.
[13] Jalalzadeh-Azar, A. A., Experimental evaluation of a downsized
residential air distribution System: comfort and ventilation effectiveness,
ASHRAE J., 113, pp. 313–322, 2007.
[14] Tzempelikos, A. & Athienitis, A.K., The impact of shading design and
control on building cooling and lighting demand, Sol. Energy 81, pp.
369–382, 2007.
[15] Zago, M., Efficiency analysis of independent and centralized heating
systems for residential buildings in Italy, Energies 4, pp. 2115–2131,
2011.
[16] Pacheco, R., Ordez, J. & Martnez, G., Energy efficient design of
building: A review, Renew. Sustain. Energy Rev., 16, pp. 3559–3573,
2012.
[17] Sailor, D.J., A green roof model for building energy simulation
programs, Energy Build. 40, pp. 1466–1478, 2008.
[18] Lai, C. M. & Wang, Y. H., Energy-saving potential of building envelope
designs in residential houses in Taiwan, Energies 4, pp. 2061–2076,
2011.
[19] Shekarchian, M., The cost benefit analysis and potential emission
reduction evaluation of applying wall insulation for buildings in
Malaysia, Renew. Sustain. Energy Rev., 16, pp. 4708–4718, 2012.
[20] Roth, K., Lawrence, T. & Brodrick, J., Double-skin façades, ASHRAE
J., 49, pp. 70–73, 2007.
[21] Shameri, M. et al, Perspectives of double skin façade systems in
buildings and energy saving, Renew. Sustain. Energy Rev., 15, pp.
1468–1475, 2011.
[22] Yusuf S.A, Georgakis & P. Nwagboso, C., Review of modelling
visualisation and artificial intelligent methodologies for built
environment applications, Built & Human Environment Review, Vol. 3.
pp. 12-41, 2010.[23] Paulescu, M., Gravila, P. & Tulcan, E., Fuzzy logic algorithms for
atmospheric transmittances of use in solar energy estimation, Energy
Conversion and Management, Vol. 49, pp. 3691–3697, 2008.
[24] Bashiri, M., Badri, H. & Hejazi, T.H., Selecting optimum maintenance
strategy by fuzzy interactive linear assignment method, Applied
Mathematical Modelling, Vol. 35, issue 1, pp. 152-164, 2011.
[25] Naji, H.R., Meybodi, M.N. & Moghaddam, T.N., Intelligent building
management systems by using multi agents: fuzzy approach,
International Journal of Computer Applications; Vol. 14, Issue 6, pp. 9-
14, 2011.
[26] Hsueh, S.L., A fuzzy utility-based multi-criteria model for evaluating
households’ energy conservation performance: a Taiwanese case study,
Energies, 5, pp. 2818-2834, 2012.
[27] Hsueh, S.L., A fuzzy logic enhanced environmental protection education
model for policies decision support in green community development,
Scientific World Journal, 8 pages, 2013.
[28] Shaikh, P.H., Nor, N.B., Nallagownden, P. & Elamvazuthi, I., Indoor
building fuzzy control of energy and comfort management, Research
Journal of Applied Sciences, Engineering and Technology, Vol. 6, Issue
23, pp. 4445-4450, 2013.
[29] Chehri, A. & Mouftah, H. T., FEMAN: Fuzzy-based energy
management system for green houses using hybrid grid solar power,
Journal of Renewable Energy, Article ID 785636, 6 pages, 2013.
[30] Lei, C. & Cheng, W.L., Research on green evaluation system of harbor
engineering based on fuzzy analytic hierarchy process, Journal of Water
Resources and Architectural Engineering, 2013.
[31] Hu, M.H., Ku, M.Y., Liao, C.K. & Ding, P.Y., Evaluation of green
residence using integrated structural equation model with fuzzy theory,
19th International Conference on Industrial Engineering and
Engineering Management, pp. 333-344, 2013.
[32] Dou, Y. et al, Government green procurement: A fuzzy-DEMATEL
analysis of barriers, Supply Chain Management Under Fuzziness Studies
in Fuzziness and Soft Computing, Vol. 313, pp. 567-589, 2014.
[33] Lacagnina, V. et al, Comparison between statistical and fuzzy
approaches for improving diagnostic decision making in patients with
chronic nasal symptoms, Fuzzy Sets and Systems, Vol. 237, pp. 136–
150, 2014.
[34] Afful-Dadzie, E., Afful-Dadzie, A. & Oplatkova, Z.K., Measuring
progress of the millennium development goals: A fuzzy comprehensive
evaluation approach, Applied Artificial Intelligence: An International
Journal, Vol. 28, Issue 1, pp. 1-15, 2015.
[35] Hsueh, S.L., Hsu, K.S. & Liu, C.Y., A multi-criteria evaluation model
for developmental effectiveness in cultural and creative industries,
Procedia Engineering, Vo. 29, pp. 1755–1761, 2012.
[36] Hsueh, S.L. & Yan, M.R., A multi methodology contractor assessment
model for facilitating green innovation: the view of energy and
environmental protection, Scientific World Journal., 14 pages, 2013.
[37] Hung, H.S. et al, An evaluation model of floor area incentive for urban
regeneration projects from the perspective of carbon emissions, Master
Program in Architecture and Urban Design, 2013.
[38] Hsueh, S.L., Evaluation of community energy-saving effects using fuzzy
logic model, Environmental Engineering & Management Journal
(EEMJ), Vol. 13, Issue 5, pp.1207-1212, 2014.
[39] Wu, K.Y., Applying the fuzzy Delphi method to analyze the sustainable
neighbourhood unit evaluation factors, Proceedings of the 15th WSEAS
international conference on Systems, pp. 23-28, 2011.
[40] Liu, L. & Zhang, T., Application of FCJ in the evaluation of low-carbon
construction program, Applied Mechanics and Materials, pp. 357-360,
2013.
[41] Lu, H., Phdungsilp, A. & Martinac, I., A study of the design criteria
affecting energy demand in new building clusters using fuzzy AHP,
Sustainability in Energy and Buildings Smart Innovation, Systems and
Technologies, Vol. 22, pp. 955-963, 2013.
[42] Chan, H.K., Wang, X. & Raffoni, A., An integrated approach for green
design: Life-cycle, fuzzy AHP and environmental management
accounting, Accounting for sustainability in production and supply
chains, Vol. 46, Issue 4, pp. 344–360, 2014.
[43] Lan, S.H. & Sheng, T.H., The study on key factors of influencing
consumers’ purchase of green buildings application of two-stage fuzzy
analytic hierarchy process, International Business Research, Vol. 7,
Issue 6, pp. 49-60, 2014.
[44] Feng, L., Zhu, X. & Sun, X., Assessing coastal reclamation suitability
based on a fuzzy-AHP comprehensive evaluation framework: A case
study of Lianyungang, China, Marine Pollution Bulletin Vol. 89, Issues
1, pp.102–111, 2014.
[45] Donevska, K.R., Gorsevski, P.V., Jovanovski, M. & Pesevski, I.,
Regional non-hazardous landfill site selection by integrating fuzzy logic,
AHP and geographic information systems, Environmental Earth
Sciences, Vol. 67, Issue 1, pp. 121-13, 2012.
[46] Huang, Y., Bao, T., Huang, Z. & Wang, H., Research on the weighting
coefficients of the lighting evaluation for the target lane, Advanced
Materials Research, pp. 1065-1069, 2015.
[47] Lee, S.K., Mogi, G. & Hui, K.S., A fuzzy analytic hierarchy process
(AHP)/data envelopment analysis (DEA) hybrid model for efficiently
allocating energy R&D resources: In the case of energy technologies
against high oil prices, Renewable and Sustainable Energy Reviews,
Vol. 21, pp. 347–355, 2013.
[48] Tang, Y., Xu, K. & Min, Y., AHP-based fuzzy comprehensive
evaluation for urbanization of mountainous area in Xianning, Advanced
Materials Research , pp. 1073 - 1076, 2015.
[49] Akadiri, P.O., Olomolaiye, P.O. & Chinyio, E.A., Multi-criteria
evaluation model for the selection of sustainable materials for building
projects, Automation in Construction, Vol. 30, pp. 113–125, 2013.
[50] Wang, J.L., Ma, R.H. & Dong, X.H., Research on energy saving of
appliances with evaluation method and application of appliances green
degree based on fuzzy-EAHP, Advanced Materials Research, Vol. 977,
pp. 155-160, 2014.
[51] Hsueh, S.L. & Yan, M.R., Enhancing sustainable community
developments: a multi-criteria evaluation model for energy efficient
project selection, International Conference on Energy, Environment and
Development, pp.135-144, 2011.
[52] Liu, K.S. et al, A DFuzzy-DAHP decision-making model for evaluating
energy-saving design strategies for residential buildings. Energies 5, pp.
4462-4480, 2012.
[53] Hsueh, S.L. et al, DFAHP multi-criteria risk assessment model for
redeveloping derelict public buildings, International Journal of Strategic
Property Management, Vol. 17, Issue 4, pp. 333-346, 2013.
[54] Alapure, G., George, D. & Bhattacharya S., Delphi-AHP-Fuzzy
computational approach to sustainability assessment model and Indian
traditional built forms, 2nd International Journal of Scientific
Engineering and Technology, Vol. 3, Issue 11, pp. 1330-1335, 2014.
[55] Gumus, A.T. et al, A combined fuzzy-AHP and fuzzy-GRA
methodology for hydrogen energy storage method selection in
Turkey, Energies. 6(6), pp. 3017–3032, 2013.
[56] Wang, Y. et al, Combination of extended fuzzy AHP and fuzzy GRA for
government E-tendering in hybrid fuzzy environment, The Scientific
World Journal, Vol. 2014, Article ID 123675, 11 pages, 2014.
[57] Liu, H.T., Product design and selection using fuzzy QFD and fuzzy
MCDM approaches, Applied Mathematical Modelling, Vol. 35, Issue 1,
pp. 482–496, 2011.
[58] Kabak, M. et al, A fuzzy multi-criteria decision making approach to
assess building energy performance, Energy and Buildings, Vol. 72, pp.
382–389, 2014.
[59] Tsai, W.H. et al, Construction method selection for green building
projects to improve environmental sustainability by using an MCDM
approach, Environmental Planning and Management, Vol. 56, Issue 10,
pp. 1487-1510, 2013.
[60] Rostamzadeh, R. et al, Application of fuzzy VIKOR for evaluation of
green supply chain management practices, Ecological Indicators, Vol.
49, pp. 188–203, 2015.
[61] Shaikh, P. et al, Building energy management through a distributed
fuzzy inference system, International Journal of Engineering and
Technology, 5 (4), pp. 3236-324, 2013.
@article{"International Journal of Architectural, Civil and Construction Sciences:69599", author = "Ghada Elshafei and Abdelazim Negm", title = "Optimization of Strategies and Models Review for Optimal Technologies - Based On Fuzzy Schemes for Green Architecture", abstract = "Recently, the green architecture becomes a
significant way to a sustainable future. Green building designs
involve finding the balance between comfortable homebuilding and
sustainable environment. Moreover, the utilization of the new
technologies such as artificial intelligence techniques are used to
complement current practices in creating greener structures to keep
the built environment more sustainable. The most common objectives
in green buildings should be designed to minimize the overall impact
of the built environment that effect on ecosystems in general and in
particularly human health and natural environment. This will lead to
protecting occupant health, improving employee productivity,
reducing pollution and sustaining the environmental. In green
building design, multiple parameters which may be interrelated,
contradicting, vague and of qualitative/quantitative nature are
broaden to use. This paper presents a comprehensive critical state- ofart-
review of current practices based on fuzzy and its combination
techniques. Also, presented how green architecture/building can be
improved using the technologies that been used for analysis to seek
optimal green solutions strategies and models to assist in making the
best possible decision out of different alternatives.
", keywords = "Green architecture/building, technologies,
optimization, strategies, fuzzy techniques and models.", volume = "9", number = "4", pages = "444-6", }
