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In this study, we consider a firm in a monopoly environment which sells two types of perishable products using a commodity bundling practice. Our goal is to find the optimal strategy of selling these two products. We determine whether they should be offered separately or in a bundle, define their optimal prices and determine the initial amount of the bundle which should be made from components with...
In the real world encountering with noisy and corrupted data is unavoidable. Auto industry sector (AIS) as a one of the significant industry encounters with noisy and corrupted data regarding to its rapid development. Therefore, developing the performance assessment in this situation is so helpful for this industry. As Data envelopment Analysis (DEA) could not deal with noisy and corrupted data, the...
The lead time estimation is significant activity in each corporation that concerns with the breakdown of machines and maintenance. An integrated algorithm for forecasting weekly lead time based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed in this study. First, an ANFIS model is illustrated for the lead time forecasting simultaneously. The lowest Mean Absolute Percentage Error (MAPE)...
This study proposes a non-parametric efficiency frontier analysis method based on the adaptive neural network technique for measuring efficiency as a complementary tool for the common techniques of the efficiency studies in the previous studies. The proposed computational method is able to find a stochastic frontier based on a set of input-output observational data and do not require explicit assumptions...
This study proposes a non-parametric efficiency frontier analysis method based on artificial neural network (ANN) for measuring efficiency as a complementary tool for the common techniques of the efficiency studies in the previous studies. The proposed ANN algorithm is able to find a stochastic frontier based on a set of input-output observational data and do not require explicit assumptions about...
This paper presents an adaptive-network-based fuzzy inference system (ANFIS) for long-term natural Electric consumption prediction. Six models are proposed to forecast annual Electric demand. 104 ANFIS have been constructed and tested in order to finding best ANFIS for Electric consumption. The proposed models consist of input variables such as Gross Domestic Product (GDP) and Population (POP). All...
Performance of artificial neural network (ANN), one of the useful tools used for credit scoring models, is increased by proposed methodology in present study. Whereas reducing the rate of error, in order to obtaining the best possible result, and optimal network of ANN are very important, in this paper, for reducing the errors of the artificial neural networks, voting algorithm will be offered. Using...
This paper presents an adaptive-network-based fuzzy inference system (ANFIS)-fuzzy data envelopment analysis (FDEA)) for long-term natural gas (NG) consumption forecasting and analysis. Six models are proposed to forecast annual NG demand. 104 ANFIS have been constructed and tested in order to find the best ANFIS for natural gas (NG) consumption. Two parameters have been considered in construction...
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