Bibliography

  1. [ASH 02] ASHRAE Standards Committee, Guideline 14-2002, 2002.
  2. [ALH 01] AL-HOMOUD M.S., “Computer-aided building energy analysis techniques”, Building and Environment, vol. 36, no. 4, pp. 421–433, 2001.
  3. [ANS 05] ANSARI F.A., MOKHTAR A.S., ABBAS K.A. et al., “A simple approach for building cooling load estimation”, American Journal of Environmental Sciences, vol. 1, no. 3, pp. 209–212, 2005.
  4. [AYD 02] AYDINALP M., UGURSAL V.I., FUNG A.S., “Modeling of the appliance, lighting, and space-cooling energy consumptions in the residential sector using neural networks”, Applied Energy, vol. 71, no. 2, pp. 87–110, 2002.
  5. [AYD 04] AYDINALP M., UGURSAL V.I., FUNG A.S., “Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks”, Applied Energy, vol. 79, no. 2, pp. 159–178, 2004.
  6. [AYD 08] AYDINALP-KOKSAL M., UGURSAL V.I., “Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector”, Applied Energy, vol. 85, no. 4, pp. 271–296, 2008.
  7. [AZA 08] AZADEH A., GHADERI S.F., SOHRABKHANI S., “Annual electricity consumption forecasting by neural network in high energy consuming industrial sectors”, Energy Conversion and Management, vol. 49, no. 8, pp. 2272–2278, 2008.
  8. [BAI 03] BAILEY M.B., KREIDER J.F., “Creating an automated chiller fault detection and diagnostics tool using a data fault library”, ISA Transactions, vol. 42, no. 3, pp. 485–495, ...

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