Open Access
Constructing a Customer's Satisfactory Evaluator System Using GA-Based Fuzzy Artificial Neural Networks
M. Reza Mashinchi,Ali Selamat +1 more
- 01 Jan 2008
TL;DR: A new approach has been proposed to provide the reliability of the strategic decisions for an enterprise that considers fuzzy artificial neural networks based on the genetic algorithm to construct a customer's satisfactory evaluator system in order to approximate the quality of the service.
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Abstract: In this paper, an important principle of economical survival in the business area has been studied. It has been considered by increasing the success rate in selling the products in order to overcome on other competitors. This can be achieved thereafter of taking suitable strategic decisions for the enterprise. It is while; the strategic decision determination is based on the quality analysis of the current organization. The analysis is based on the linguistic values received from the customers where the fuzzy modeling, as one of the possible ways, has been used to process these values. The customer's satisfaction has been considered as a key factor for the analysis based on his/her preference as the scope of the qualification for the organization service. In this paper, a new approach has been proposed to provide the reliability of the strategic decisions for an enterprise. This approach considers fuzzy artificial neural networks based on the genetic algorithm to construct a customer's satisfactory evaluator system in order to approximate the quality of the service. The proposed system is able to predict the quality values of the possible strategies according to customer's preference. Finally, the ability of this system in recognizing the customer's preference has been tested using some new assumed services.
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Citations
Predicting correlations properties of crude oil systems using type-2 fuzzy logic systems
TL;DR: A type-2 fuzzy logic based model is presented to improve PVT predictions and empirical results show that Type-2 FLS approach outperforms others in general and particularly in the area of stability, consistency and the ability to adequately handle uncertainties.
72
Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems
TL;DR: Empirical results from simulation show that type-2 fuzzy logic approach outperformed others in general and particularly in the area of stability and ability to handle data in uncertain situations, which are common characteristics of well logs data.
68
Improved sensitivity based linear learning method for permeability prediction of carbonate reservoir using interval type-2 fuzzy logic system
Sunday O. Olatunji,Ali Selamat,Abdul Azeez Abdul Raheem +2 more
- 01 Jan 2014
TL;DR: An improved sensitivity based linear learning method (SBLLM) model through the hybridization of type-2 fuzzy logic systems (type-2 FLS) and SBLLM is proposed and empirical results from simulation show that the proposed improved hybrid model has greatly improved upon the performance of the standard SB LLM.
51
Technological dimension of customer relationship management
Gholam Reza Hashemzadeh,Seyed Mohammad Sadegh Khaksar,Khaled Nawaser,Asghar Afshar Jahanshahi +3 more
TL;DR: In this paper, the authors reviewed the technological dimension of CRM on customer satisfaction and in the context of customer values (mediator variables) and found that the technological dimensions of the CRM in terms of customer value (functional value, social value, emotional value and customer perceived sacrifices) are influential on customer's satisfaction.
25
A hybrid model through the fusion of type-2 fuzzy logic systems and sensitivity-based linear learning method for modeling pvt properties of crude oil systems
TL;DR: Empirical results from simulation show that the proposed T2-SBLLM hybrid system has greatly improved upon the performance of SBLLM, while also maintaining a better performance above that of the type-2 FLS.
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