Results 1 - 10 of 1,422

A hidden Markov model for predicting transmembrane helices in protein sequences

by Erik L. L. Sonnhammer - In Proceedings of the 6th International Conference on Intelligent Systems for Molecular Biology (ISMB , 1998
"... A novel method to model and predict the location and orientation of alpha helices in membrane- spanning proteins is presented. It is based on a hidden Markov model (HMM) with an architecture that corresponds closely to the biological system. The model is cyclic with 7 types of states for helix core, ..."
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A novel method to model and predict the location and orientation of alpha helices in membrane- spanning proteins is presented. It is based on a hidden Markov model (HMM) with an architecture that corresponds closely to the biological system. The model is cyclic with 7 types of states for helix core

A Neuro-Fuzzy System for Ash Property Prediction

by Giovanna Castellano, Ciro Castiello, Anna M. Fanelli, Michele Giovannini - PROC. SECOND INTERNAT. WORKSHOP ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA2002 , 2002
"... This paper proposes a neuro-fuzzy approach to solve the problem of predicting the property of ashes originated from combustion processes for electric generation. The adopted approach uses fuzzy logic for modeling as well as neural networks for extraction and optimization of the fuzzy model via learn ..."
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This paper proposes a neuro-fuzzy approach to solve the problem of predicting the property of ashes originated from combustion processes for electric generation. The adopted approach uses fuzzy logic for modeling as well as neural networks for extraction and optimization of the fuzzy model via

A Neuro-Fuzzy Classifier for Customer Churn Prediction

by Hossein Abbasimehr, Mostafa Setak, M. J. Tarokh
"... Churn prediction is a useful tool to predict customer at churn risk. By accurate prediction of churners and non-churners, a company can use the limited marketing resource efficiently to target the churner customers in a retention marketing campaign. Accuracy is not the only important aspect in evalu ..."
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in evaluating a churn prediction models. Churn prediction models should be both accurate and comprehensible. Therefore, Adaptive Neuro Fuzzy Inference System (ANFIS) as neuro-fuzzy classifier is applied to churn prediction modeling and benchmarked to traditional rulebased classifier such as C4.5 and RIPPER

A Novel Neuro-Fuzzy Approach for Phishing Identification

by Luong Anh, Tuan Nguyen, Ba Lam To, Huu Khuong Nguyen, Chuan Pham, Choong Seon Hong
"... Abstract — Together with the growth of Internet, e-commerce transactions play an important role in the modern society. As a result, phishing is a deliberate act by an individual or a group of people to steal personal information such as password, banking account, credit card information, etc. Most o ..."
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increasing due to inefficient protection technique. Neural networks and fuzzy systems can be combined to join its advantages and to cure its individual illness. This paper proposed a new neuro-fuzzy model without using rule sets for phishing identification. Specifically, the proposed technique calculates

Electricity Consumption Prediction Model using Neuro-Fuzzy System

by Rahib Abiyev, Vasif H. Abiyev, Cemal Ardil
"... Abstract—In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type’s of customers, number of plants, etc. It is nonlinear proc ..."
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process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules

Neuro-Fuzzy Modeling of Nucleation Kinetics of Protein

by Devinder Kaur, Rajendrakumar Gosavi
"... Abstract:- The estimation of the nucleation kinetics of protein using a predictive model will greatly help in reducing the number of parameters for protein nucleation studies. In this paper a Fuzzy Inference Model has been developed using the observed data for nuclear kinetics. The model was trained ..."
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was trained using neuro fuzzy inference system. The results obtained from the fuzzy model were compared with the experimentally observed values from the data collected. Results show that a better fit can be obtained using the fuzzy logic technique and the nucleation kinetics can be very well estimated

Prediction of concrete elastic modulus using adaptive neuro-fuzzy inference system

by Abdulkadir Cüneyt Aydin, Ahmet Tortum, Murat Yavuz , 2006
"... The prediction of elastic modulus is one of the fundamental facts of structural engineering studies. The performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the elastic modulus of normal- and high-strength concrete was investigated. Results indicate that the proposed ANFIS mo ..."
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The prediction of elastic modulus is one of the fundamental facts of structural engineering studies. The performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the elastic modulus of normal- and high-strength concrete was investigated. Results indicate that the proposed ANFIS

Implementation of Neuro-Fuzzy Models with Analog Systolic Architectures

by J. M. Moreno, J. Madrenas, F. Guinjoan, J. Cabestany
"... this paper we shall propose a novel analog systolic architecture which is able to combine the main features of digital and analog solutions, providing in this way an efficient alternative for the implementation of fuzzy models. Furthermore, by using some of the organization principles of an existing ..."
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this paper we shall propose a novel analog systolic architecture which is able to combine the main features of digital and analog solutions, providing in this way an efficient alternative for the implementation of fuzzy models. Furthermore, by using some of the organization principles

Prediction of Surface Roughness in Turning Using Adaptive Neuro-Fuzzy Inference System

by B. Sidda Reddy A, J. Suresh Kumar B, K. Vijaya, Kumar Reddy
"... Due to the extensive use of highly automated machine tools in the industry, manufacturing requires reliable models for the prediction of output performance of machining processes. The prediction of surface roughness plays a very important role in the manufacturing industry. The present work deals wi ..."
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with the development of surface roughness prediction model for machining of aluminum alloys, using adaptive neuro-fuzzy inference system (ANFIS). The experimentation has been carried out on CNC turning machine with carbide cutting tool for machining aluminum alloys covering a wide range of machining conditions

Application of Neuro-Fuzzy Techniques for Solar Radiation

by W. A. Rahoma, U. Ali Rahoma, A. H. Hassan
"... Abstract: Problem statement: The prediction is very useful in solar energy applications because it permits to estimate solar data for locations where measurements are not available. The developed artificial intelligence models predict the solar radiation time series more effectively compared to the ..."
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is trained with the same data. Results: The comparison and the evaluation of both of the systems were done according to their predictions, using several error metrics. Fuzzy model was trained using data of daily solar radiation recorded on a horizontal surface in National Research Institute of Astronomy
Results 1 - 10 of 1,422