Abstract
In this paper, an intelligent predictor model for forecasting the behaviour of buyers in the product they would be interested to purchase using best customers and biggest customer index as inputs to the predictor. The model is based on fuzzy logic and Ordinal Structure Fuzzy Logic (OSFL). These intelligent models are developed based on the market survey data of the U.S. Bureau of Labour Statistics (BLS) data. The market survey data are sets of consumers categorized in various demographics their spending on the products. The association factors among the products and the consumer’s spending habits are determined using indexes as proposed by New Strategist in order to develop the Fuzzy predictor model. A software is developed to simulate he predictor based on the demographics. The software outputs a list of products based on probability priorities. The result of simulations of the software is compared with the BLA data and found to be quite accurate.
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References
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Yusof, R., Khalid, M., Yunus, M.R. (2010). Ordinal Structure Fuzzy Logic Predictor for Consumer Behaviour. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15390-7_48
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DOI: https://doi.org/10.1007/978-3-642-15390-7_48
Publisher Name: Springer, Berlin, Heidelberg
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