Data analysis and inference for an industrial deethanizer
نویسندگان
چکیده
a Dept. of Information and Computer Science, Helsinki University of Technology P.O. Box 5400, FI-02015 HUT, Finland b Biotecnology and Chemical Technology Dept., Helsinki University of Technology P.O. Box 6100, FI-02015 HUT, Finland c Dept. of Chemical Engineering and Materials, University of Cagliari Piazza d’Armi, I-09123 Cagliari, Italy d Cain Dept. of Chemical Engineering, Louisiana State Univesrity South Stadium Road, LA-70803 Baton Rouge, USA
منابع مشابه
A One-Stage Two-Machine Replacement Strategy Based on the Bayesian Inference Method
In this research, we consider an application of the Bayesian Inferences in machine replacement problem. The application is concerned with the time to replace two machines producing a specific product; each machine doing a special operation on the product when there are manufacturing defects because of failures. A common practice for this kind of problem is to fit a single distribution to the co...
متن کاملComparison of autoregressive integrated moving average (ARIMA) model and adaptive neuro-fuzzy inference system (ANFIS) model
Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...
متن کاملA Disease Outbreak Prediction Model Using Bayesian Inference: A Case of Influenza
Introduction: One major problem in analyzing epidemic data is the lack of data and high dependency among the available data, which is due to the fact that the epidemic process is not directly observable. Methods: One method for epidemic data analysis to estimate the desired epidemic parameters, such as disease transmission rate and recovery rate, is data ...
متن کاملForecasting Industrial Production in Iran: A Comparative Study of Artificial Neural Networks and Adaptive Nero-Fuzzy Inference System
Forecasting industrial production is essential for efficient planning by managers. Although there are many statistical and mathematical methods for prediction, the use of intelligent algorithms with desirable features has made significant progress in recent years. The current study compared the accuracy of the Artificial Neural Networks (ANN) and Adaptive Nero-Fuzzy Inference System (ANFIS) app...
متن کاملSales Budget Forecasting and Revision by Adaptive Network Fuzzy Base Inference System and Optimization Methods
The sales proceeds are the most important factors for keeping alive profitable companies. So sales and budget sales are considered as important parameters influencing all other decision variables in an organization. Therefore, poor forecasting can lead to great loses in organization caused by inaccurate and non-comprehensive production and human resource planning. In this research a coherent so...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009