A fuzzy regression approach to a hierarchical evaluation model for oil palm fruit grading

• Abbas Z., Yeow Y. K., Shaari A. H., Khalid K., Hassan J., Saion E. (2005) Complex permittivity and moisture measurements of oil palm fruits using an open-ended coaxial sensor. IEEE Sensors Journal 5(6): 1281–1287

  Article  Google Scholar 

• Abdalla A., Buckley J. J. (2007) Monte Carlo methods in fuzzy linear regression. Soft Computing 11(10): 991–996

  Article  MATH  Google Scholar 

• Abdullah M. Z., Guan L. C., Karim A. A. (2004) The applications of computer vision system and tomographic radar imaging for assessing physical properties of food. Journal of Food Engineering 61(1): 125–135

  Article  Google Scholar 

• Abdullah M. Z., Guan L. C., Mohd Azemi B. M. N. (2001) Stepwise discriminant analysis for colour grading of oil palm using machine vision system. Institution of Chemical Engineers, Transaction of the IChemE 79(C): 223–231

  Google Scholar 

• Alfatni M. S. M., Shariff A. R. M., Shafri H. Z. M., Saaed O. B., Eshanta O. M. (2008) Oil palm fruit bunch grading system using red, green, and blue digital number. Journal of Applied Sciences 8(8): 1444–1452

  Article  Google Scholar 

• Byun H. S., Lee K. H. (2005) A decision support system for the selection of a rapid prototyping process using the modified TOPSIS method. International Journal of Advanced Manufacturing Technologies 26: 1338–1347

  Article  Google Scholar 

• Chen T.-Y., Tsao C.-Y. (2008) The interval-valued fuzzy TOPSIS method and experimental analysis. Fuzzy Sets and Systems 159(11): 1410–1428

  Article  MATH  MathSciNet  Google Scholar 

• Deng H. (1999) Multicriteria analysis with fuzzy pairwise comparison. International Journal of Approximate Reasoning 21(3): 215–231

  Article  Google Scholar 

• Divakaran L., Terence T. O. (2005) On policy capturing with fuzzy measures. European Journal of Operational Research 167(2): 461–474

  Article  MATH  Google Scholar 

• Eng T. G., Tat M. M. (1985) Quality control in food processing. Journal of the American Oil Chemists Society 62(2): 274–282

  Article  Google Scholar 

• Enea M., Piazza T. (2004) Project selection by constrained fuzzy AHP. Fuzzy Optimization and Decision Making 3(1): 39–62

  Article  MATH  Google Scholar 

• Girard N., Hubert B. (1999) Modeling expert knowledge with knowledge-based systems to design decision aids: The example of a knowledge-based model on grazing management. Agricultural Systems 59(2): 123–144

  Article  Google Scholar 

• He Y. Q., Chan L. K., Wu M. L. (2007) Balancing productivity and consumer satisfaction for profitability: Statistical and fuzzy regression analysis. European Journal of Operational Research 176(1): 252–263

  Article  MATH  Google Scholar 

• Hwang C. L., Yoon K. (1981) Multiple Attribute Decision Making Methods and Applications. Springer, New York, NY

  MATH  Google Scholar 

• Irfan, E., & Nilsen, K. (2006). The fuzzy analytic hierarchy process for supplier selection and an application in a textile company. In Proceedings of the 5th international symposium on intelligent manufacturing systems, pp. 195–207. Sakarya University.

• Ishak, W. H., & Siraj, F. (2002). Artificial intelligence in medical application: An exploration. Health Informatics Europe Journal.

• Kreng V. B., Wu C. Y. (2007) Evaluation of knowledge portal development tools using a fuzzy AHP approach: The case of Taiwanese stone industry. European Journal of Operational Research 176(3): 1795–1810

  Article  MATH  Google Scholar 

• Kuo T.-C., Chang S.-H., Huang S.H. (2006) Environmentally conscious design by using fuzzy multi-attribute decision-making. The International Journal of Advanced Manufacturing Technology 29(5): 419–425

  Article  Google Scholar 

• Li D. F. (2007) A fuzzy closeness approach to fuzzy multi-attribute decision making. Fuzzy Optimization Decision Making 6(3): 237–254

  Article  Google Scholar 

• McCown R. L. (2002) Changing systems for supporting farmers’ decisions: problems, paradigms, and prospects. Agricultural Systems 74(1): 179–220

  Article  Google Scholar 

• Mehran H., Bector C. R., Kamal S. (2005) A simple method for computation of fuzzy linear regression. European Journal of Operational Research 166(1): 172–184

  Article  MATH  MathSciNet  Google Scholar 

• MPOB: (2003) Oil palm fruit grading manual (2nd ed.). Malaysian Palm Oil Board Publisher, Kuala Lumpur

• Rashid, S., Nor, A. A., Radzali, M., Shattri, M., Rohaya, H., & Roop, G. (2002). Correlation between oil content and DN values, GISdevelopment.net.

• Saaty T. L. (1980) The analytic hierarchy process. McGraw-Hill, New York, NY

  MATH  Google Scholar 

• Saaty T. L. (1990) Multicriteria decision making: The analytic hierarchy process. RWS Publications, Pittsburgh, PA

  Google Scholar 

• Saaty T. L. (1994) How to make a decision: The analytic decision processes. Interfaces 24(6): 19–43

  Article  MathSciNet  Google Scholar 

• Siregar, I. M., (1976). Assessment of ripeness and crop control in oil palm. In Proceedings of the Malaysian international agricultural oil palm conference (pp. 711–723). Kuala Lumpur, Malaysia.

• Sugihara K., Tanaka H. (2001) Interval evaluations in the analytic hierarchy process by possibility analysis. Computational Intelligence 17(3): 567–579

  Article  Google Scholar 

• Takahagi E. (2008) A fuzzy measure identification method by diamond pairwise comparisons and sφ transformation. Fuzzy Optimization Decision Making 7(3): 219–232

  Article  MATH  MathSciNet  Google Scholar 

• Tanaka H., Watada J. (1988) Possibilistic linear systems and their Application to the linear regression model. Fuzzy Sets and Systems 27(3): 275–289

  Article  MATH  MathSciNet  Google Scholar 

• Toyoura Y., Watada J., Khalid M., Yusof R. (2004) Formulation of linguistic regression model based on natural words. Soft Computing Journal 8(10): 681–688

  Article  MATH  Google Scholar 

• Wang Y. M., Luo Y., Hua Z. (2008) On the extent analysis method for fuzzy AHP and its applications. European Journal of Operational Research 186(2): 735–747

  Article  MATH  Google Scholar 

• Watada J. (1994) Applications in business, multiattribute decision—making. In: Terano T., Asai K., Sugeno M. (eds) Applied fuzzy system. AP Professional, Boston, pp 244–252

  Google Scholar 

• Watada J. (1996) Possibilistic time-series analysis and its analysis of consumption. In: Dubois D., Yager M. M. (eds) Fuzzy information engineering. Wiley, New York, pp 187–200

  Google Scholar 

• Watada, J., et al. (2005). Trend of fuzzy multivariant analysis in management engineering. In R. Khosla (Ed.), KES2005, LNAI 3682 (pp. 1283–1290). Berlin: Springer.

• Watada, J., & Pedrycz, W. (2008). A fuzzy regression approach to acquisition of linguistic rules. In W. Pedrycz (Ed.), Handbook on granular commutation (pp. 719–730, Chap. 32). John Wiley & Sons Ltd (in press).

• Watada J., Toyoura Y. (2002) Formulation of fuzzy switching auto-regression model. International Journal of Chaos Theory and Applications 7(1, 2): 67–76

  Google Scholar 

• Yabuuchi Y., Watada J. (1996) Fuzzy robust regression analysis based on a hyper elliptic function. Journal of the Operations Research Society of Japan 39(4): 512–524

  MATH  Google Scholar 

• Yeh, C. H., & Chang, Y. H. (2008). Modeling subjective evaluation for fuzzy group multicriteria decision making. European Journal of Operational Research 2008 (in press).

• Yoon K. P., Hwang C. L. (1995) Multiple attribute decision making: An introduction. Sage Publications, Thousand Oaks, CA

  Google Scholar 

• Yusuf B., Chan K. W. (2004) The oil palm and its sustainability. Journal of Palm Oil Research 16(1): 1–10

  Google Scholar 

• Zadeh L. A. et al (1998) Roles of soft computing and fuzzy logic in the conception, design and deployment of information/intelligent systems. In: Kaynak O. (eds) Computational intelligence: Soft computing and fuzzy-neuro integration with applications. Springer, Germany, pp 1–9

  Google Scholar 

Download references