neuro-fuzzy based modeling
Modeling of Optimized Neuro-Fuzzy Logic Based Active Vibration Control Method for Automotive Suspension
... as neuro-fuzzy. Adaptive neuro-fuzzy inference system (ANFIS), was first proposed by Jang (1993) [22] and is based on the first-order Takagi-Sugeno fuzzy ...combining ...
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Modelling Metal cutting Parameters Using Intelligent Techniques
... the modeling of metal ...are based on artificial intelligence are often used for this ...hybrid, neuro-fuzzy model in the prediction of a workpiece temperature and surface ...is based ...
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A New Approach to Adaptive Neuro-fuzzy Modeling using Kernel based Clustering
... The fuzzy rule base for FIS can be constructed directly by domain experts a method that is usually error prone or by using fuzzy modelling ...approach. Fuzzy modelling also called fuzzy ...
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Uncertainty analysis through development of seismic fragility curve for an SMRF structure using an adaptive neuro-fuzzy inference system based on fuzzy C-means algorithm
... Adaptive Neuro Fuzzy Inference System (ANFIS) was not re- ported as far as the author's knowledge was ...by modeling parameters under ground motion excitation are acquired through application of ...
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Predictive modeling in food mycology using adaptive neuro-fuzzy systems
... (TSK) fuzzy system structure, Jang [12] developed an adaptive network -ANFIS (which can be regarded as a neural network) in which hybrid learning rules are ...input fuzzy partitions is large and hence the ...
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Neuro Fuzzy Modeling of Design Parameters of Connecting Rod
... the Neuro-Fuzzy modeling has received attention in the area of manufacturing processes, electrical power drive systems, electronics systems and mechanical design ...is based on the combination ...
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Dietary Fibers Effect from Mango Peels and Date Seeds on Rheological properties of Arabic Bread Quality: A Novel approach on applying Fuzzy Modeling in Studying Rolling/Folding and Tearing values
... approach based on fuzzy logic and genetic algorithms to control a crossflow microfiltration pilot ...using fuzzy and neuro-fuzzy techniques based on available expertise and ...
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Application of several data-driven techniques to predict a standardized precipitation index
... index modeling approach based on large-scale climate indices by using the adaptive neuro-fuzzy inference system (ANFIS), the M5P model tree and the multilayer perceptron ...
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Neuro-fuzzy-based Electronic Brake System Modeling using Real Time Vehicle Data
... and modeling process, the first step is choosing the right model structure, and the next step will be selecting appropriate optimization ...network- based fuzzy inference system ...
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Adaptive Neuro-Fuzzy Inference System For Rainfall-Runoff Modeling
... (ANN), fuzzy logic, genetic algorithm and chaos theory have been widely applied in the sphere of hydrology and water ...for modeling of complex hydrologic systems and widely used for ...include ...
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Multioutput Adaptive Neuro-Fuzzy Inference System Based Modeling of Heated Catalytic Converter Performance
... Adaptive neuro-fuzzy system makes use of a hybrid-learning rule to optimize the fuzzy system parameters of a first order Sugeno ...Sugeno fuzzy model is shown by Fig ...
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Dynamic neuro-fuzzy systems for rainfall-runoff modelling
... rainfall-runoff modeling the researchers are focusing to develop new algorithms, new software and procedures for designing future ...Network based Fuzzy Inference System (ANFIS) developed by Jang ...
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An FPGA-Based Neuro-Fuzzy Sensor for Personalized Driving Assistance
... DS modeling is ...adaptive neuro-fuzzy inference system (ANFIS) obtaining identification rates higher than ...The neuro-fuzzy intelligent sensor provided high speed for real-time active ...
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A Neuro Fuzzy System for Modeling the Depression Data
... Health informatics (HI) is an interdisciplinary domain, which attempts to merge ‘Healthcare’ and ‘Technology’, effectively. In addition to e-Health (i.e., applications of Information Communication Technology in ...
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Rainfall-runoff modelling of a watershed
... In this way the input vector was fed through the network layer by layer. The two major phases for implementing the ANFIS for applications are the structure identification phase and the parameter identification phase. The ...
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Prediction of Combine Harvester Performance Using Hybrid Machine Learning Modeling and Response Surface Methodology
... and modeling of the desired system (combine in this study) give better judge about the performance of various sectors [14, ...System modeling using conventional mathematical tools such as deferential ...
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Neuro-Fuzzy Based Performance Evaluation of Shunt Motor
... these neuro-adaptive learning techniques is to provide a method for the fuzzy modelling procedure to learn information about a data set, in order to automatically compute the membership function parameters ...
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Vol 12, No 1 (2014)
... SWT, fuzzy, Neuro-Fuzzy, Fuzzylet and Neuro-Fuzzylet algorithms has been discussed and tested with two datasets (mono-spectral and ...that Neuro-Fuzzy gives better results than ...
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Auto control of pumping operations in sewerage systems by rule based fuzzy neural networks
... In case of flood/flooding in urban areas, the operation strategy for sewerage systems in Taipei City is to set up pumping stations which are the major hydraulic facilities for inner rainwater discharges. Undoubtedly, ...
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Spike discharge prediction based on neuro-fuzzy system
... neural fuzzy inference system (HyFIS) and subtractive clustering and fuzzy c-means (SBC) algorithms and section 3 presents the performance of different neuro- fuzzy algorithms for analysis of ...
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