Seyed Heydar Mirfakhraddiny; Hamid BabaeiMeybodi; Ali Morovati sharifabadi
Volume 17, Issue 2 , May 2013, , Pages 196-222
Abstract
During recent decades, Energy as one of the most important factors of production and also as one of the most important end products, a special place in the country's economic development and growth development. Hence, the country authorities should try to predict anything more precise energy consumption ...
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During recent decades, Energy as one of the most important factors of production and also as one of the most important end products, a special place in the country's economic development and growth development. Hence, the country authorities should try to predict anything more precise energy consumption in the proper planning and guidance consumption, to control the way they desired energy demand and supply parameters. The purpose of this paper is Evaluation Hybrid model of artificial neural networks and genetic algorithms in the forecast consumption energy of Iran. Therefore in this study, data from the annual energy consumption as the output forecasting model range and was used as input variables, data of the annual total population, GDP, imports and exports.The end results were assessed with of different models (RSE), (ME) and (RMSE). Evaluation results showed that the hybrid model of neural networks and genetic algorithm (ANN-GA), compared to other models with the highest accuracy in predicting consumption energy of Iran.
Hasan Gholi Pour Tahmouras; Seyed Mahdi Miri; Ali Morovati sharif Abadi
Volume 11, Issue 20 , December 2007, , Pages 59-80
Abstract
Market segmentation by artificial neural networks has no deep root in the history. Generally, this ever developing approach has started since several years ago, and developed to other marketing areas. Now, beside statistical techniques, it is considered as one of the most popular methods in Custamer ...
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Market segmentation by artificial neural networks has no deep root in the history. Generally, this ever developing approach has started since several years ago, and developed to other marketing areas. Now, beside statistical techniques, it is considered as one of the most popular methods in Custamer classification.
In Due to the necessity of recognizing the target market for a specific company, a need for the usage of an effective approach for customers grouping was recognized, in the Present research, and finally cluster analysis with SOM neural networks, was selected, and used for customers clustering.
Firstly, beneficent criteria for market segmentation were identified, and then a proper, questionnaire was designed. After gathering the questionnaires and collecting the data, using artificial neural networks, the customers were clustered, and the obtained, results were analyzed. At the end, the Findings of this method were compared with those of the traditional methods for clusteringusing K-means.
Ali Mohaghar; Ali Morovati Sharif Abadi
Volume 10, Issue 20 , June 2006, , Pages 269-292
Abstract
Just in Time (JIT) production systems are introduced for production and supply of goods and services with minimum inventory. The goal of this paper is present a sample of system dynamics modeling application for analysis and improvement of JIT system's behavior. In this paper relations between demand ...
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Just in Time (JIT) production systems are introduced for production and supply of goods and services with minimum inventory. The goal of this paper is present a sample of system dynamics modeling application for analysis and improvement of JIT system's behavior. In this paper relations between demand of products, quality of produced goods, inventory, maintenance of machines and facilities, production rate and supplier's efficiency are investigated in a dynamic system. In the first section problem definition, dynamic hypothesis, causal diagram and flow diagram of system are discussed. Afterwards behavior of the model is inspected from different views by developing a dynamic model.
