Comparison of Fuzzy Inference System and Multiple Regression to Predict Synthetic Envelopes Clogging
نویسندگان
چکیده
Geo-synthetic materials are being used with acceptable performance in soil and water projects worldwide. Geotextiles are one of the categories of geo-synthetics being used in drainage systems. First generation of geotextiles used in the late 1950’s as an alternative for gravel envelopes. In this research two methods (multiple regression and fuzzy interference system) evaluate to predict synthetic envelope clogging. In multiple regression method the correlation coefficients for PP450, PP700 and PP900 are 62.66%, 79.37% and 90.62%, respectively and results of fuzzy interference system and decision tree showed that this method have high potential in comparison with multiple regression and values of total classification accuracy for PP450, PP700 and PP900 are 98.6%, 97.3% and 98% respectively. Then final results of this research showed fuzzy interference systems by using decision tree have high potential to predict clogging in envelops.
منابع مشابه
Artificial intelligence-based approaches for multi-station modelling of dissolve oxygen in river
ABSTRACT: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water...
متن کاملPrediction of soil cation exchange capacity using support vector regression optimized by genetic algorithm and adaptive network-based fuzzy inference system
Soil cation exchange capacity (CEC) is a parameter that represents soil fertility. Being difficult to measure, pedotransfer functions (PTFs) can be routinely applied for prediction of CEC by soil physicochemical properties that can be easily measured. This study developed the support vector regression (SVR) combined with genetic algorithm (GA) together with the adaptive network-based fuzzy infe...
متن کاملThe use of wavelet-artificial neural network and adaptive neuro-fuzzy inference system models to predict monthly precipitation
In water supply systems, One of the most important components as safety unit and the current controller (Switching flow and regulate the amount of flow) used in the arrangement of lines of water. In this study, according to multiple ponds in Tanguiyeh dam water pipeline to industrial and mining company Gol Gohar Sirjan Butterfly valve used in these ponds using Fluent software simulation has bee...
متن کاملPrediction of slope stability using adaptive neuro-fuzzy inference system based on clustering methods
Slope stability analysis is an enduring research topic in the engineering and academic sectors. Accurate prediction of the factor of safety (FOS) of slopes, their stability, and their performance is not an easy task. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was utilized to build an estimation model for the prediction of FOS. Three ANFIS models were implemented including g...
متن کاملADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AND STEPWISE REGRESSION FOR COMPRESSIVE STRENGTH ASSESSMENT OF CONCRETE CONTAINING METAKAOLIN
In the current study two methods are evaluated for predicting the compressive strength of concrete containing metakaolin. Adaptive neuro-fuzzy inference system (ANFIS) model and stepwise regression (SR) model are developed as a reliable modeling method for simulating and predicting the compressive strength of concrete containing metakaolin at the different ages. The required data in training an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Computer and Information Science
دوره 3 شماره
صفحات -
تاریخ انتشار 2010